How are these figures produced?

Every row carries a provenance label. Sourced rows (47) are published figures from an accountable source — a vendor's model card or announcement, or a press review that documents its setup. Community rows (146) are one person's linked run. Estimated rows (287) are computed from the model's size at the row's stated quant and the chip's memory bandwidth with the published two-term model. Measured rows keep their source's own prompt length and settings, listed in the measured table; LLMCheck runs no tests of its own.

Why does tok/s vary between Ollama, LM Studio, MLX and llama.cpp?

Each runtime uses different kernels and quantization formats. MLX is Apple's own framework for Apple Silicon; llama.cpp runs GGUF files on Metal; LM Studio can run either engine. Since Ollama v0.40.0 (25 September 2026), Ollama runs supported models on MLX by default on Apple Silicon. The same model on the same chip can differ by tens of percent between runtimes and builds. In the index, Qwen 3 30B-A3B on an M4 Max runs at 110 tok/s (published, 4-bit, arxiv.org) on MLX and 90 tok/s (published, 4-bit, arxiv.org) on llama.cpp.

Which Apple Silicon chip is best for local AI?

It depends on the model size, because decode speed tracks memory bandwidth: in the index, an 8B model such as Qwen 3 8B runs at ~11 tok/s (estimated, Q4_K_M) on a base M1 and ~44 tok/s (estimated, Q4_K_M) on an M4 Pro; the dense Qwen3.8-27B runs at 48 tok/s (published, oQ4e, macstories.net) on an M5 Ultra; and Llama 3.3 70B runs at 13.1 tok/s (published, 4-bit, tbreak.com) on a 128 GB M5 Max. The M5 Max (614 GB/s) has about 3× the bandwidth of an M2 Pro (200 GB/s). 70B-class dense models need 64 GB or more, and the Mac Studio M5 Ultra (1,228 GB/s) and M3 Ultra (819 GB/s), with up to 512 GB, are for models above 128 GB. Best LLM for each Mac →

Can I submit my own benchmarks?

Yes. Run the model with Ollama, LM Studio, MLX or llama.cpp with speculative decoding (MTP) off, and record your chip and GPU core count, RAM, runtime and version, quant, prompt length and decode tok/s. Submit it through the contribution guide (GitHub issue or email). An accepted row is labelled community and links to your run.

What is the fastest local LLM on Apple Silicon?

In the LLMCheck index (data version 2026-10-24), the fastest figure is Maple Preview 20B-A1B at 387 tok/s (published, Ternary, github.com) on an M5 Pro (a sub-2-bit format, compute-bound); the fastest bandwidth-bound measured figure is LFM2.5-2.6B at 220 tok/s (published, Q4_K_M, liquid.ai) on an M5 Max; among models of 100B+ parameters, GPT-oss 120B reaches 120 tok/s (community run, MXFP4, bohemiansilicon.com) on an M5 Ultra; the fastest estimate is Gemma 4 E2B at ~261 tok/s (estimated, Q4_K_M) on an M5 Max.

How far off are the estimates?

Against the 137 measured rows the formula can cost, the median gap is 14%, and 87 of 137 land within 20% (35 dense rows: median 10%; 102 mixture-of-experts rows: median 19%, 63 of them faster than the formula). Large mixture-of-experts estimates are deliberately conservative. A model with a measured row has its other chips scaled from that row rather than from the formula. Every comparison is listed in the measured table.

How does LLMCheck calculate its composite score?

The LLMCheck Score is a 0–100 composite: 50 points for capability (Arena ELO, MMLU, HumanEval and SWE-Bench), 25 for speed (decode tok/s × 0.25 on an M5 Max, or the M5 Ultra for models above 128 GB — a measured row where one exists), 15 for accessibility (minimum RAM) and 10 for license openness. Full formula and sources: /methodology.

Apple Silicon LLM Benchmarks: Tokens per Second (2026)

Model↕	Params↕	Quant↕	Chip↕	RAM↕	Engine↕	tok/s↓	TTFT↕	Date↕
Maple Preview 20B-A1B	20B-A1B	Ternary	M5 Pro	48 GB	MLX	sourced387	—	2026-09-17
Gemma 4 E2B	2.3B	Q4_K_M	M5 Max	128 GB	MLX	estimated261	—	2026-04
LFM2.5-2.6B	2.6B	Q4_K_M	M5 Max	64 GB	MLX	sourced220	0.1s	2026-08
SmolLM3 3B	3B	Q4_K_M	M5 Max	64 GB	MLX	estimated199	—	2026-05
Nanbeige4.2-3B	3B	Q4_K_M	M5 Max	64 GB	MLX	estimated199	—	2026-08
LFM2.5-24B-A2B	24B-A2.45B	Q4_K_M	M5 Max	—	llama.cpp	sourced184	—	2026-10-13
GPT-oss 20B	21B-A3.6B	MXFP4	M5 Ultra	256 GB	MLX	community184	—	2026-10-15
Maple Preview 20B-A1B	20B-A1B	Ternary	M4	16 GB	MLX	sourced169	—	2026-08
Phi-4 Mini	3.8B	Q4_K_M	M5 Max	64 GB	Ollama	estimated168	—	2026-03
Qwen 3.5 9B	9B	4-bit	M5 Ultra	256 GB	MLX	community167	—	2026-10-15
Nemotron 3.5 Lightning	30B-A3B	4-bit	M5 Max	128 GB	MLX	community164.7	—	2026-10-18
Qwen 3.5 35B-A3B	35B	4-bit	M5 Ultra	256 GB	MLX	community162	—	2026-10-15
Qwen 3.5 4B	4B	Q4_K_M	M5 Max	64 GB	MLX	estimated161	—	2026-03
Gemma 4 E4B	4B	Q4_K_M	M5 Max	128 GB	MLX	estimated161	—	2026-04
Gemma 3 4B	4B	Q4_K_M	M5 Max	64 GB	Ollama	estimated161	—	2026-03
Qwen 3 4B	4B	Q4_K_M	M5 Max	64 GB	Ollama	estimated161	—	2026-03
Nemotron 3.5 Bolt E4B	4B	Q4_K_M	M5 Max	64 GB	llama.cpp	estimated161	—	2026-10
Spark-X2.6-4B	4.11B	Q4_K_M	M5 Max	64 GB	llama.cpp	estimated158	—	2026-10
Mellum2.1-12B-A2.5B-Thinking	12B-A2.5B	Q4_K_M	M5 Max	64 GB	llama.cpp	estimated154	—	2026-10
Qwen 3.6-35B-A3B	35B-A3B	4-bit	M5 Ultra	256 GB	MLX	community153.4	—	2026-09-20
Phi-4 Mini	3.8B	Q4_K_M	M4 Max	48 GB	MLX	estimated153	—	2026-02
Gemma 4 E2B	2.3B	Q4_K_M	M4 Pro	24 GB	Ollama	estimated147	—	2026-04
Nemotron 3.5 Lightning	30B-A3B	4-bit	M5 Max	128 GB	MLX	community139.3	—	2026-10-18
Qwen 3.5 35B-A3B	35B	Q4_K_M	M5 Max	64 GB	MLX	estimated136	—	2026-03
LFM2.5-24B-A2B	24B-A2.45B	8-bit	M5 Max	128 GB	MLX	community131.5	—	2026-10-20
Recursive Flint	39.8B-A2.5B	INT4	M4 Pro	48 GB	rec	sourced131.2	—	2026-10-21
Recursive Flint	39.8B-A2.5B	INT4	M5 Max	36 GB	MLX	community131	—	2026-10-22
Recursive Flint	39.8B-A2.5B	Q4_K_M	M5 Max	64 GB	llama.cpp	estimated131	—	2026-10
Qwen 3 30B-A3B	30B-A3B	unstated	M5 Max	128 GB	MLX	sourced130.63	—	2026-09-21
Qwen 3.5 35B-A3B	35B	Q4_K_M	M4 Max	48 GB	Ollama	estimated130	—	2026-02
Qwen3-Coder-Next	80B	Q4_K_M	M5 Ultra	96 GB	MLX	estimated130	—	2026-08
Qwen 3.6-35B-A3B	35B-A3B	4-bit	M5 Max	128 GB	MLX	community126	—	2026-08
Mellum2.1-12B-A2.5B-Thinking	12B-A2.5B	Q4_K_M	M4 Pro	24 GB	llama.cpp	estimated122	—	2026-10
LFM2.5-24B-A2B	24B-A2.45B	4-bit	M5 Pro	48 GB	MLX	community122	—	2026-10-19
Gemma 4 26B-A4B	26B-A4B	Q4_K_M	M1 Ultra	64 GB	Ollama	estimated120	—	2026-08
GPT-oss 120B	117B-A5.1B	MXFP4	M5 Ultra	96 GB	MLX	estimated120	—	2026-08
GPT-oss 120B	117B-A5.1B	MXFP4	M5 Ultra	256 GB	MLX	community120	—	2026-10-15
North Mini Code 1.0	30B-A3B	4-bit	M5 Max	64 GB	MLX	community119.7	—	2026-06-26
Qwen 3.6-35B-A3B	35B-A3B	Q4_K_M	M5 Max	—	llama.cpp	sourced118	—	2026-10-13
Nemotron-Cascade 2	30B	Q4_K_M	M5 Max	64 GB	Ollama	estimated117	—	2026-04
Nemotron 3.5 Lightning	30B-A3B	Q4_K_M	M4 Max	48 GB	MLX	estimated117	—	2026-08
Laguna XS 2.1	33B-A3B	Q4_K_M	M5 Max	64 GB	MLX	estimated117	—	2026-08
Nemotron 3.5 Lightning	30B-A3B	Q4_0	M5 Max	128 GB	llama.cpp	community116.8	—	2026-10-18
LFM2.5-24B-A2B	24B-A2.45B	Q4_K_M	M5 Pro	24 GB	MLX	estimated116	—	2026-10
LFM2.5-24B-A2B	24B-A2.45B	4-bit	M3 Ultra	96 GB	MLX	community115.6	—	2026-10-21
Qwen 3.5 35B-A3B	35B	Q4_K_M	M3 Max	64 GB	Ollama	estimated115	—	2026-01
Recursive Flint	39.8B-A2.5B	4-bit	M5 Pro	64 GB	Ollama	community115	—	2026-10-21
Nemotron 3.5 Lightning	30B-A3B	Q4_K_M	M5 Max	—	llama.cpp	sourced114	—	2026-10-13
North Mini Code 1.0	30B-A3B	Q4_K_M	M4 Max	64 GB	MLX	estimated114	—	2026-10
LFM2.5-24B-A2B	24B-A2.45B	oQ4e	M5 Pro	48 GB	MLX	community113.5	—	2026-10-19
Mellum2.1-12B-A2.5B-Thinking	12B-A2.5B	6-bit	M5 Pro	64 GB	MLX	community112.7	—	2026-10-23
Nemotron-Cascade 2	30B	Q4_K_M	M4 Max	48 GB	MLX	estimated111	—	2026-04
Recursive Flint	39.8B-A2.5B	oQ6e	M5 Max	128 GB	MLX	community110.2	—	2026-10-22
Qwen 3 30B-A3B	30B-A3B	4-bit	M4 Max	128 GB	MLX	sourced110	—	2026-01
GPT-oss 20B	21B-A3.6B	MXFP4	M5 Max	64 GB	MLX	estimated108	—	2026-10
GPT-oss 20B	21B-A3.6B	unstated	M5 Max	128 GB	Ollama	sourced107.51	—	2026-09-21
Gemma 4 26B-A4B	26B-A4B	Q4_K_M	M5 Max	—	llama.cpp	sourced107	—	2026-10-13
Qwen 3.6-35B-A3B	35B-A3B	4-bit	M3 Ultra	512 GB	MLX	community106.4	—	2026-09-20
SmolLM3 3B	3B	Q4_K_M	M4 Pro	24 GB	Ollama	estimated106	—	2026-05
Qwen 3.6-35B-A3B	35B	Q4_K_M	M4 Max	48 GB	MLX	estimated105	—	2026-04
Qwen 3.6-35B-A3B	35B-A3B	Q4_K_M	M1 Ultra	64 GB	MLX	estimated105	—	2026-08
Recursive Flint	39.8B-A2.5B	INT4	M3 Ultra	—	MLX	community104.5	—	2026-10-21
Mistral 7B	7B	Q4_K_M	M5 Max	64 GB	Ollama	estimated102	—	2026-03
Phi-4 Mini	3.8B	Q8_0	M5 Max	64 GB	MLX	estimated102	—	2026-03
GPT-oss 20B	21B-A3.6B	MXFP4	M4 Max	64 GB	MLX	estimated102	—	2026-10
Gemma 4 26B-A4B	26B	Q4_K_M	M4 Max	48 GB	MLX	estimated101	—	2026-04
MiniCPM-V 4.7 35B-A3B	35B-A3B	MXFP4	M5 Max	64 GB	MLX	community100.2	—	2026-10-17
Raon-1 mini preview	28.8B-A4.3B	Q4_K_M	M5 Max	64 GB	llama.cpp	estimated99	—	2026-10
Mellum2.1-12B-A2.5B-Thinking	12B-A2.5B	BF16	M5 Max	64 GB	LM Studio	community96.8	—	2026-10-09
Qwen 3 30B-A3B	30B	Q4_K_M	M5 Max	64 GB	Ollama	estimated96	—	2026-03
Qwen 3.6-35B-A3B	35B-A3B	4-bit	M5 Pro	48 GB	LM Studio	community95.62	—	2026-10-19
Qwen 3.6-35B-A3B	35B-A3B	4-bit	M5 Pro	48 GB	MLX	community94.3	—	2026-10-19
Nemotron 3.5 Lightning	30B-A3B	4-bit	M5 Pro	48 GB	MLX	community93.73	—	2026-10-19
GPT-oss 120B	117B-A5.1B	MXFP4	M1 Ultra	128 GB	Ollama	estimated93	—	2026-08
Qwen 3.6-35B-A3B	35B-A3B	Q8_0	M5 Max	128 GB	llama.cpp	community92.9	—	2026-06-14
Recursive Flint	39.8B-A2.5B	Q4_1	M5 Pro	48 GB	llama.cpp	community92.36	—	2026-10-22
Qwen 3.6-35B-A3B	35B-A3B	Q4_K_M	M2 Max	64 GB	MLX	estimated92	—	2026-08
Gemma 4 E4B	4B	Q4_K_M	M5 Pro	24 GB	Ollama	estimated91	—	2026-04
Qwen 3 8B	8B	Q4_K_M	M5 Max	128 GB	Ollama	estimated91	—	2026-03
DeepSeek R1 8B	8B	Q4_K_M	M5 Max	64 GB	Ollama	estimated91	—	2026-03
Llama 3.1 8B	8B	Q4_K_M	M5 Max	128 GB	MLX	estimated91	—	2026-03
Ministral 8B	8B	Q4_K_M	M5 Max	64 GB	Ollama	estimated91	—	2026-03
Apertus 1.5 8B	8B	Q4_K_M	M5 Max	64 GB	MLX	estimated91	—	2026-08
Recursive Flint	39.8B-A2.5B	4-bit	M3 Ultra	—	MLX	community90.6	—	2026-10-21
Qwen 3 30B-A3B	30B-A3B	4-bit	M4 Max	128 GB	llama.cpp	sourced90	—	2026-01
LFM2.5-24B-A2B	24B-A2.45B	Q4_K_M	M4 Pro	24 GB	Ollama	estimated90	—	2026-10
LFM2.5-24B-A2B	24B-A2.45B	5-bit	M4 Max	48 GB	MLX	community89.7	—	2026-10-15
KAT-Coder-V2.5	35B-A3B	OptiQ-4bit	M5 Max	128 GB	MLX	community89.3	—	2026-08-07
Recursive Flint	39.8B-A2.5B	4-bit	M4 Pro	48 GB	llama.cpp	sourced88	—	2026-10-21
Gemma 4 26B-A4B	26B-A4B	MXFP4_MOE	M3 Ultra	512 GB	llama.cpp	community87.8	—	2026-10-13
Qwen 3.5 122B-A10B	122B-A10B	4-bit	M5 Ultra	256 GB	MLX	community87.7	—	2026-09-20
MiniCPM-V 4.7 35B-A3B	35B-A3B	MXFP4	M4 Max	64 GB	MLX	community86.9	—	2026-10-23
Spark-X2.6-4B	4.11B	INT4	M5 Pro	—	MLX	sourced86.58	—	2026-10-21
Phi-4 Mini	3.8B	Q4_K_M	M4 Pro	24 GB	Ollama	estimated86	—	2026-03
MiniCPM-V 4.7 35B-A3B	35B-A3B	8-bit	M5 Max	128 GB	MLX	community84.7	—	2026-10-21
Qwen3-Coder-Next	80B-A3B	Q4_K_M	M5 Max	64 GB	MLX	estimated84	—	2026-08
MiniCPM-V 4.7 35B-A3B	35B-A3B	Q4_K_M	M4 Max	64 GB	MLX	estimated84	—	2026-10
Granite 4.2 8B	8.8B	Q4_K_M	M5 Max	64 GB	Ollama	estimated84	—	2026-10
Qwen 3 4B	4B	Q4_K_M	M4 Pro	24 GB	MLX	estimated82	—	2026-02
Qwen 3.5 9B	9B	Q4_K_M	M5 Max	64 GB	Ollama	estimated82	—	2026-03
North Mini Code 1.0	30B-A3B	Q4_K_M	M3 Max	64 GB	MLX	estimated82	—	2026-10
Qwen 3.6-35B-A3B	35B-A3B	Q4_K_M	M5 Pro	48 GB	llama.cpp	community81.96	—	2026-10-19
MiniCPM-V 4.7 35B-A3B	35B-A3B	oQ4e	M4 Pro	48 GB	MLX	community81.8	—	2026-10-22
Qwen 3.6-35B-A3B	35B-A3B	Q8_0	M3 Ultra	512 GB	llama.cpp	community81.2	—	2026-10-14
Recursive Flint	39.8B-A2.5B	oQ4e	M5 Pro	48 GB	MLX	community80.7	—	2026-10-22
KAT-Coder-V2.5	35B-A3B	Q4_K_M	M4 Max	48 GB	MLX	estimated80	—	2026-08
Qwen 3.5 122B-A10B	122B-A10B	unstated	M5 Ultra	256 GB	LM Studio	sourced80	—	2026-09
Recursive Flint	39.8B-A2.5B	Q4_1	M4 Pro	48 GB	llama.cpp	community79.57	—	2026-10-22
Qwen 3.6-35B-A3B	35B-A3B	Q4_K_M	M5 Pro	48 GB	Ollama	community79.48	—	2026-10-19
LFM2.5-2.6B	2.6B	Q4_K_M	M6	24 GB	MLX	estimated79	—	2026-08
Mistral Small 4	119B	Q4_K_M	M5 Ultra	96 GB	MLX	estimated79	—	2026-08
LFM2.5-24B-A2B	24B-A2.45B	Q4_K_M	M6	24 GB	MLX	estimated79	—	2026-10
MiMo-V2.6-Distill-Qwen-9B	9.4B	Q4_K_M	M5 Max	64 GB	llama.cpp	estimated79	—	2026-10
Kolibri-1	78B-A3.5B	8-bit	M5 Max	128 GB	MLX	community78.9	—	2026-10-17
Gemma 4 26B-A4B	26B	Q4_K_M	M5 Pro	24 GB	Ollama	estimated78	—	2026-04
Qwen 3.6-35B-A3B	35B-A3B	4-bit	M5 Pro	48 GB	MLX	community77.8	—	2026-10-19
Nemotron-Cascade 2	30B	Q4_K_M	M4 Pro	24 GB	Ollama	estimated77	—	2026-04
Laguna XS 2.1	33B-A3B	Q4_K_M	M4 Pro	24 GB	Ollama	estimated77	—	2026-08
Qwen3-Coder-Next	80B-A3B	Q4_K_M	M4 Max	64 GB	MLX	estimated77	—	2026-08
Ternary Bonsai 2 9B	9.41B	PQ2_0	M5 Pro	—	llama.cpp	sourced76.5	—	2026-10
MiMo-V2.6-Flash	309B-A15B	4-bit	M5 Ultra	256 GB	MLX	community76.4	—	2026-09-26
Spark-X2.6-4B	4.11B	Q4_K_M	M5 Pro	—	llama.cpp	sourced76.14	—	2026-10-21
GPT-oss 120B	117B-A5.1B	MXFP4	M5 Max	128 GB	Ollama	estimated76	—	2026-03
Qwen 3.6-35B-A3B	35B-A3B	4-bit	M5 Pro	48 GB	MLX	community75.66	—	2026-10-19
GPT-oss 120B	117B-A5.1B	unstated	M5 Max	128 GB	Ollama	sourced75.65	—	2026-09-21
MiniCPM-V 4.7 35B-A3B	35B-A3B	oQ4e	M4 Pro	48 GB	MLX	community75.2	—	2026-10-22
Qwen 3 30B-A3B	30B	Q4_K_M	M3 Max	64 GB	Ollama	estimated75	—	2026-01
Kolibri-1	78B-A3.5B	Q4_K_M	M5 Max	64 GB	MLX	estimated75	—	2026-10
Nemotron 3.5 Bolt 74B-A9B	74B-A9B	IQ2_XXS	M3 Ultra	512 GB	MLX	community74.5	—	2026-10-18
Nemotron 3.5 Super VL 120B-A12B	120B-A12B	4-bit	M5 Ultra	96 GB	MLX	community74.3	—	2026-10-19
KAT-Coder-V2.5	35B-A3B	unstated	M4 Max	48 GB	LM Studio	community74.2	—	2026-09-19
LFM2.5-24B-A2B	24B-A2.45B	4-bit	M5	32 GB	MLX	community74.2	—	2026-10-17
Qwen 3.6-35B-A3B	35B	Q4_K_M	M4 Pro	24 GB	Ollama	estimated74	—	2026-04
Nemotron 3.5 Super VL 120B-A12B	120B-A12B	Q4_K_M	M5 Ultra	256 GB	llama.cpp	estimated74	—	2026-10
Nemotron 3.5 Bolt 74B-A9B	74B-A9B	IQ2_XXS	M5 Max	64 GB	MLX	community73	—	2026-10-23
Nemotron 3.5 Bolt E4B	4B	4-bit	M3 Max	36 GB	MLX	community72.98	—	2026-10-23
Nemotron 3.5 Lightning	30B-A3B	Q4_K_M	M5 Pro	48 GB	LM Studio	community72.3	—	2026-10-19
Gemma 4 26B-A4B	26B	Q4_K_M	M4 Pro	24 GB	Ollama	estimated72	—	2026-04
Nemotron 3.5 Bolt 74B-A9B	74B-A9B	4-bit	M5 Max	128 GB	MLX	community71.7	—	2026-10-16
North Mini Code 1.0	30B-A3B	4-bit	M5 Pro	64 GB	MLX	community69.8	—	2026-06-13
Qwen3.8-Flash-Next	125B-A6B	oQ4e	M5 Max	128 GB	MLX	community69.7	—	2026-10-18
KAT-Coder-V2.5	35B-A3B	6-bit	M3 Max	48 GB	MLX	community69.5	—	2026-08-13
Kolibri-1	78B-A3.5B	Q4_K_M	M4 Max	64 GB	MLX	estimated69	—	2026-10
Qwen 3.6-35B-A3B	35B-A3B	4-bit	M5 Pro	48 GB	llama.cpp	sourced68.7	—	2026-10-15
Laguna S 2.1	118B	Q4_K_M	M5 Ultra	96 GB	MLX	estimated68	—	2026-08
Ling-3.0 Flash	124B-A5B	4-bit	M5 Max	128 GB	MLX	community68	—	2026-08-07
Nemotron 3.5 Lightning	30B-A3B	Q4_K_M	M4 Pro	24 GB	Ollama	estimated67	—	2026-08
Bonsai 27B	27B	Q1_0_g128	M5 Max	—	llama.cpp	sourced66.4	—	2026-07
KAT-Coder-V2.5	35B-A3B	Q4_K_M	M4 Pro	24 GB	Ollama	estimated66	—	2026-08
Qwen 3.5 4B	4B	Q4_K_M	M5 Pro	—	llama.cpp	sourced65.82	—	2026-10-21
MiMo-V2.6-Flash	309B-A15B	MXFP4	M5 Ultra	256 GB	MLX	estimated65	—	2026-09
North Mini Code 1.0	30B-A3B	Q4_K_M	M4 Pro	24 GB	Ollama	estimated65	—	2026-10
Gemma 3 12B	12B	Q4_K_M	M5 Max	64 GB	Ollama	estimated64	—	2026-03
Qwen 3.6-35B-A3B	35B-A3B	4-bit	M6	32 GB	MLX	community64	—	2026-10
GPT-oss 20B	21B-A3.6B	MXFP4	M4 Pro	24 GB	MLX	estimated64	—	2026-10
Gemma 4 12B	12B	Q4_K_M	M5 Max	64 GB	MLX	estimated64	—	2026-10
Nemotron 3.5 Bolt 74B-A9B	74B-A9B	5-bit	M5 Max	128 GB	MLX	community63.6	—	2026-10-16
Gemma 4 E4B	4B	Q4_K_M	M5 Pro	—	llama.cpp	sourced62.15	—	2026-10-21
Qwen 3 30B-A3B	30B-A3B	unstated	M6	32 GB	MLX	sourced62.01	—	2026-09-21
Gemma 4 E2B	2.3B	Q4_K_M	M3	16 GB	Ollama	estimated62	—	2026-04
Gemma 4 E4B	4B	Q4_K_M	M4 Pro	24 GB	MLX	estimated62	—	2026-04
Llama 3.1 8B	8B	Q4_K_M	M2 Max	32 GB	Ollama	estimated62	—	2026-08
MiMo-V2.6-Flash	309B-A15B	4-bit	M5 Ultra	256 GB	MLX	community61.7	—	2026-09-26
GLM-5.3-Flash	320B-A18B	MLX mixed 4/8-bit	M5 Ultra	256 GB	MLX	community61.7	—	2026-10-23
LFM2.5-2.6B	2.6B	FP16	M4 Max	—	llama.cpp	sourced61	—	2026-08-20
Qwen 3.5 122B-A10B	122B-A10B	unstated	M3 Ultra	96 GB	LM Studio	sourced60	—	2026-09
MiniMax-M3	428B-A23B	IQ3_XXS	M5 Ultra	256 GB	llama.cpp	estimated60	—	2026-10
Mellum2.1-12B-A2.5B-Thinking	12B-A2.5B	Q4_K_M	M6	24 GB	llama.cpp	estimated60	—	2026-10
LFM2.5-24B-A2B	24B-A2.45B	4-bit	M4	24 GB	MLX	community59.9	—	2026-10-16
MiMo-V2.6-Flash	309B-A15B	4-bit	M3 Ultra	256 GB	MLX	community59.4	—	2026-09-23
LFM2.5-24B-A2B	24B-A2.45B	4-bit	M4	32 GB	MLX	community59.3	—	2026-10-22
Mistral 7B	7B	Q8_0	M5 Max	64 GB	MLX	estimated59	—	2026-03
MiMo-V2.6-Flash	309B-A15B	4-bit	M3 Ultra	256 GB	MLX	community59	—	2026-09
Nemotron 3.5 Super VL 120B-A12B	120B-A12B	Q4_K_M	M3 Ultra	256 GB	llama.cpp	estimated59	—	2026-10
Qwen3.8-Flash-Next	125B-A6B	oQ4e	M5 Max	128 GB	MLX	community58.7	—	2026-10-24
Qwen 3.5 122B-A10B	122B-A10B	4-bit	M3 Ultra	512 GB	MLX	community58.6	—	2026-09-20
Qwen 3 30B-A3B	30B	Q4_K_M	M4 Pro	24 GB	MLX	estimated58	—	2026-02
Nemotron 3.5 Bolt 74B-A9B	74B-A9B	4-bit	M5 Max	128 GB	MLX	community57.9	—	2026-10-20
Gemma 4 12B	12B	Q4_K_M	M4 Max	64 GB	MLX	estimated57	—	2026-10
MiniMax M2.5	230B-A10B	Q4_K_M	M5 Ultra	256 GB	MLX	estimated57	—	2026-10
Qwen3.8-Flash-Next	125B-A6B	IQ4_NL	M5 Ultra	256 GB	llama.cpp	community57	—	2026-10-11
MiniMax-M2.7	229B-A10B	Q4_K_M	M5 Ultra	256 GB	llama.cpp	estimated57	—	2026-10
MiniCPM-V 4.7 35B-A3B	35B-A3B	MXFP4	M5 Pro	64 GB	MLX	community56.6	—	2026-10-22
Nemotron 3.5 Bolt 74B-A9B	74B-A9B	4-bit	M3 Ultra	256 GB	MLX	community56.5	—	2026-10-15
Nemotron 3.5 Bolt E4B	4B	6-bit	M3 Max	36 GB	MLX	community55.22	—	2026-10-23
MiMo-V2.6-Flash	309B-A15B	4-bit	M3 Ultra	512 GB	MLX	community55.1	—	2026-10-19
Qwen 3 14B	14B	Q4_K_M	M5 Max	64 GB	Ollama	estimated55	—	2026-03
Phi-4 14B	14B	Q4_K_M	M5 Max	64 GB	MLX	estimated55	—	2026-03
Ministral 3 14B	14B	Q4_K_M	M5 Max	64 GB	Ollama	estimated55	—	2026-03
Qwen3.8-27B	27.8B	Q4_K_M	M5 Ultra	256 GB	LM Studio	sourced55	0.5s	2026-09
Qwen 2.5 14B	14B	Q4_K_M	M5 Max	64 GB	llama.cpp	estimated55	—	2026-10
Qwen 3.5 27B	27B	4-bit	M5 Ultra	256 GB	MLX	community55	—	2026-10-15
Qwen3.8-27B	27.8B	4-bit	M5 Ultra	256 GB	MLX	community54.7	—	2026-09-20
Qwen 3 8B	8B	4-bit	M5 Pro	48 GB	llama.cpp	sourced54.4	—	2026-10-15
Gemma 4 E4B	4B	Q4_K_M	M6	24 GB	MLX	estimated54	—	2026-08
MiniCPM-V 4.7 35B-A3B	35B-A3B	Q4_K_M	M5 Pro	24 GB	MLX	estimated54	—	2026-10
MiniCPM-V 4.7 35B-A3B	35B-A3B	Q4_K_M	M6	24 GB	MLX	estimated54	—	2026-10
Qwen 3 4B	4B	unstated	M6	32 GB	MLX	sourced53.35	—	2026-09-21
Granite 4.2 30B	29.3B	Q4_K_M	M5 Ultra	96 GB	MLX	estimated53	—	2026-10
Gemma 4 26B-A4B	26B-A4B	4-bit	M6	32 GB	MLX	community52.2	—	2026-09-24
Llama 3.1 8B	8B	Q8_0	M5 Max	64 GB	Ollama	estimated52	—	2026-03
DeepSeek R1 8B	8B	Q8_0	M5 Max	64 GB	MLX	estimated52	—	2026-03
Kolibri-1	78B-A3.5B	4-bit	M1 Max	64 GB	MLX	community52	—	2026-10-03
Nemotron 3.5 Bolt 74B-A9B	74B-A9B	4-bit	M4 Max	64 GB	MLX	estimated52	—	2026-10
Nemotron 3.5 Super VL 120B-A12B	120B-A12B	4-bit	M5 Max	128 GB	MLX	community51.8	—	2026-10-18
Recursive Flint	39.8B-A2.5B	BF16	M3 Ultra	512 GB	MLX	community51.3	—	2026-10-21
Nanbeige4.2-3B	3B	Q4_K_M	M4	16 GB	Ollama	estimated51	—	2026-08
Recursive Flint	39.8B-A2.5B	Q4_1	M3 Pro	36 GB	llama.cpp	community50.87	—	2026-10-22
Nemotron 3.5 Bolt 74B-A9B	74B-A9B	IQ2_XXS	M3 Max	128 GB	MLX	community50.8	—	2026-10-22
Nemotron 3.5 Super VL 120B-A12B	120B-A12B	4-bit	M4 Max	128 GB	MLX	community50.8	—	2026-10-18
Qwen3.8-Flash-Next	125B-A6B	Q4_K_M	M5 Max	128 GB	Ollama	community50.1	—	2026-10-18
Mistral 7B	7B	Q4_K_M	M4 Pro	24 GB	MLX	estimated50	—	2026-02
Mellum2.1-12B-A2.5B-Thinking	12B-A2.5B	Q4_K_M	M4	16 GB	llama.cpp	community50	—	2026-10-08
KAT-Coder-V2.5	35B-A3B	oQ2e	M5	32 GB	MLX	community49.5	—	2026-08
Inkling-Small	276B	Q4_K_M	M5 Ultra	256 GB	MLX	estimated49	—	2026-08
GLM-4.5-Air	106B	Q4_K_M	M5 Ultra	96 GB	MLX	estimated49	—	2026-08
MiniCPM-V 4.7 35B-A3B	35B-A3B	5-bit	M4 Pro	64 GB	MLX	community48.2	—	2026-10-16
Gemma 3 4B	4B	Q4_K_M	M3 Pro	18 GB	MLX	estimated48	—	2026-01
Gemma 4 26B-A4B	26B-A4B	QAT	M6	32 GB	LM Studio	community48	—	2026-10
Qwen3.8-27B	27.8B	oQ4e	M5 Ultra	256 GB	MLX	sourced48	—	2026-09
Qwen 3.5 9B	9B	Q8_0	M5 Max	128 GB	MLX	estimated47	—	2026-03
Gemma 3 4B	4B	Q8_0	M4 Pro	24 GB	MLX	estimated47	—	2026-02
KAT-Coder-V2.5	35B	Q4_K_M	M6	24 GB	MLX	estimated47	—	2026-08
Qwen3.8-Flash-Next	125B-A6B	4-bit	M5 Max	128 GB	MLX	community47	—	2026-08-29
Ternary Bonsai 2 27B	27.36B	PQ2_0	M5 Max	—	llama.cpp	sourced46.8	—	2026-09-16
Nemotron 3.5 Bolt E4B	4B	oQ8e	M5 Pro	64 GB	MLX	community46.4	—	2026-10-23
Qwen3.8-Flash-Next	125B-A6B	IQ4_NL	M5 Max	128 GB	llama.cpp	community46.4	—	2026-10-18
Qwen3.8-27B	27.8B	Q4_K_M	M5 Ultra	256 GB	llama.cpp	sourced46.27	—	2026-09-21
Mistral Small 4	119B	Q4_K_M	M5 Max	128 GB	MLX	estimated46	—	2026-04
DeepSeek V4 Flash Vision-Exp	305B-A13B	Q4_K_M	M5 Ultra	256 GB	llama.cpp	estimated46	—	2026-09
Nemotron 3.5 Super VL 120B-A12B	120B-A12B	4-bit	M5 Max	128 GB	MLX	community45.5	—	2026-10-18
Nemotron 3.5 Bolt E4B	4B	8-bit	M3 Max	36 GB	MLX	community45.26	—	2026-10-23
DeepSeek V4 Flash	284B-A13B	Q4_K_M	M5 Ultra	256 GB	MLX	estimated45	—	2026-08
Nemotron 3.5 Lightning	30B-A3B	Q4_K_M	M6	32 GB	llama.cpp	community45	—	2026-10
GPT-oss 20B	21B-A3.6B	unstated	M6	32 GB	LM Studio	community45	—	2026-10
MiniMax-M2.7	229B-A10B	IQ3_XXS	M5 Max	128 GB	llama.cpp	estimated45	—	2026-10
Bonsai 27B	27B	Q1_0_g128	M5 Pro	—	llama.cpp	sourced44.2	—	2026-07
Gemma 4 E2B	2.3B	Q4_K_M	M1	8 GB	Ollama	estimated44	—	2026-04
Qwen 3 8B	8B	Q4_K_M	M4 Pro	24 GB	Ollama	estimated44	—	2026-02
Nemotron 3.5 Bolt 74B-A9B	74B-A9B	4-bit	M3 Max	128 GB	MLX	community44	—	2026-10-16
Ling-3.0 Flash	124B-A5B	oQ4e	M2 Max	96 GB	MLX	community44	—	2026-10-23
Qwen3.8-Flash-Next	125B-A6B	4-bit	M5 Max	128 GB	MLX	community43.8	—	2026-08-29
Ternary Bonsai 2 27B	27.36B	Ternary	M5 Max	48 GB	MLX	community43.4	—	2026-10-20
SmolLM3 3B	3B	Q4_K_M	M3	16 GB	Ollama	estimated43	—	2026-05
SmolLM3 3B	3B	Q4_K_M	M2	8 GB	Ollama	estimated43	—	2026-05
Nanbeige4.2-3B	3B	Q4_K_M	M2	8 GB	Ollama	estimated43	—	2026-08
Qwen3.8-Flash-Next	125B-A6B	Q4_K_M	M4 Max	128 GB	MLX	estimated43	—	2026-09
Kolibri-1	78B-A3.5B	Q4_K_M	M5 Pro	64 GB	MLX	estimated43	—	2026-10
Qwen 3.5 122B-A10B	122B-A10B	Q4_K_M	M5 Max	128 GB	llama.cpp	community42.9	—	2026-04-05
Inkling-Small	276B-A12B	Q2_K	M5 Max	128 GB	MLX	estimated42	—	2026-08
MiniMax-M3	428B-A23B	Q4_K_M	M5 Ultra	512 GB	MLX	estimated42	—	2026-10
Nemotron 3.5 Bolt 74B-A9B	74B-A9B	Q4_K_M	M3 Ultra	96 GB	llama.cpp	community41.61	—	2026-10-16
MiniMax M2.5	230B-A10B	Q4_K_M	M3 Ultra	256 GB	MLX	estimated41	—	2026-10
MiniMax-M2.7	229B-A10B	IQ3_XXS	M4 Max	128 GB	llama.cpp	estimated41	—	2026-10
MiMo-V2-Flash	309B-A15B	Q4_K_M	M5 Ultra	256 GB	llama.cpp	estimated41	—	2026-10
Ternary Bonsai 2 9B	9.41B	Ternary	M6	16 GB	MLX	community40.2	—	2026-10-21
Qwen3.8-27B	27.8B	Q4_K_M	M3 Ultra	96 GB	LM Studio	sourced40	—	2026-09
Granite 4.2 8B	8.8B	Q4_K_M	M4 Pro	24 GB	Ollama	estimated40	—	2026-10
GLM-5.3-Flash	320B-A18B	unstated	M5 Ultra	256 GB	llama.cpp	community39.7	—	2026-10-11
Qwen 3.5 4B	4B	Q4_K_M	M4	16 GB	Ollama	estimated39	—	2026-02
Qwen 3.5 9B	9B	Q4_K_M	M4 Pro	24 GB	MLX	estimated39	—	2026-03
DeepSeek V4 Flash	284B-A13B	Q2_K	M5 Max	128 GB	MLX	community39	0.4s	2026-08
DeepSeek V4 Flash Vision-Exp	305B-A13B	Q2_K	M5 Max	128 GB	llama.cpp	estimated39	—	2026-09
Qwen 3.5 122B-A10B	122B-A10B	Q4_K_M	M4 Max	128 GB	MLX	estimated39	—	2026-09
Beam 1.0	501B-A23B	IQ3_XXS	M5 Ultra	256 GB	llama.cpp	estimated39	—	2026-10
Nemotron 3.5 Bolt 74B-A9B	74B-A9B	4-bit	M3 Max	64 GB	MLX	estimated39	—	2026-10
Kolibri-1	78B-A3.5B	Q4_K_M	M4 Pro	64 GB	llama.cpp	estimated39	—	2026-10
Nemotron 3.5 Bolt 74B-A9B	74B-A9B	IQ2_XXS	M5 Pro	48 GB	MLX	community39	—	2026-10-19
DeepSeek V4.1 Flash	552B-A16B	oQ4e	M3 Ultra	512 GB	MLX	community38.7	—	2026-10-21
Laguna S 2.1	118B-A8B	Q4_K_M	M5 Max	128 GB	MLX	estimated38	—	2026-08
Qwen 3.6-27B	27B	Q4_K_M	M1 Ultra	64 GB	MLX	estimated38	—	2026-08
MiMo-V2.6-Distill-Qwen-9B	9.4B	Q4_K_M	M4 Pro	24 GB	llama.cpp	estimated38	—	2026-10
Qwen3.8-27B	27.8B	4-bit	M3 Ultra	512 GB	MLX	community37.6	—	2026-09-20
Nemotron 3.5 Bolt 74B-A9B	74B-A9B	8-bit	M5 Max	128 GB	MLX	community37	—	2026-10-15
North Mini Code 1.0	30B-A3B	Q4_K_M	M6	24 GB	Ollama	estimated37	—	2026-10
Nemotron 3.5 Super VL 120B-A12B	120B-A12B	Q4_K_M	M4 Max	128 GB	llama.cpp	estimated36	—	2026-10
Llama 4 Maverick	400B-A17B	Q4_K_M	M5 Ultra	256 GB	llama.cpp	estimated36	—	2026-10
Qwen 3.5 397B-A17B	397B-A17B	Q4_K_M	M5 Ultra	256 GB	llama.cpp	estimated36	—	2026-10
Mellum2.1-12B-A2.5B-Thinking	12B-A2.5B	6-bit	M4	32 GB	MLX	community35.9	—	2026-10-10
Nemotron 3.5 Super VL 120B-A12B	120B-A12B	Q4_0	M5 Max	128 GB	llama.cpp	community35.9	—	2026-10-18
Laguna S 2.1	118B-A8B	Q4_K_M	M4 Max	128 GB	MLX	estimated35	—	2026-08
Inkling-Small	276B-A12B	Q4_K_M	M3 Ultra	512 GB	MLX	estimated35	—	2026-08
GLM-5.3-Flash	320B-A18B	Q4_K_M	M5 Ultra	256 GB	MLX	estimated35	—	2026-09
Nemotron 3.5 Bolt 74B-A9B	74B-A9B	IQ2_XXS	M4 Pro	48 GB	MLX	community34.6	—	2026-10-19
MiniMax-M3.1-Flash	428B-A23B	oQ3e	M5 Ultra	256 GB	MLX	community34.5	—	2026-10-24
Ternary Bonsai 2 27B	27.36B	PQ2_0	M4 Max	128 GB	llama.cpp	community34.5	—	2026-09-17
North Mini Code 1.0	30B-A3B	4-bit	M5	32 GB	MLX	community34.2	—	2026-09-18
Phi-4 Mini	3.8B	Q4_K_M	M3	16 GB	MLX	estimated34	—	2026-02
Phi-4 Mini	3.8B	Q4_K_M	M2	8 GB	Ollama	estimated34	—	2026-01
GPT-oss 20B	21B-A3.6B	MXFP4	M4	16 GB	MLX	estimated34	—	2026-10
Qwen 3 4B	4B	Q4_K_M	M2	8 GB	Ollama	estimated33	—	2026-01
Gemma 4 E4B	4B	Q4_K_M	M3	16 GB	Ollama	estimated33	—	2026-04
Mistral Small 3.2 24B	24B	Q4_K_M	M5 Max	128 GB	MLX	estimated33	—	2026-05
Devstral Small 24B	24B	Q4_K_M	M5 Max	128 GB	MLX	estimated33	—	2026-05
DeepSeek V4 Flash	284B-A13B	Q4_K_M	M3 Ultra	256 GB	MLX	estimated32	—	2026-08
DeepSeek V4 Flash Vision-Exp	305B-A13B	Q4_K_M	M3 Ultra	256 GB	llama.cpp	estimated32	—	2026-09
Qwen 3 4B	4B	8-bit	M6	24 GB	LM Studio	community31.47	0.64s	2026-09-22
Qwen 3 14B	14B	Q8_0	M5 Max	128 GB	MLX	estimated31	—	2026-03
Qwen3.8-27B	27.8B	oQ4e	M3 Ultra	512 GB	MLX	sourced31	—	2026-09
Muse Spark Open	816B-A42B	oQ3e	M5 Ultra	512 GB	MLX	estimated31	—	2026-10
Nemotron 3.5 Bolt 74B-A9B	74B-A9B	4-bit	M5 Pro	48 GB	MLX	estimated31	—	2026-10
Gemma 4 31B	31B	QAT	M5 Ultra	256 GB	MLX	community31	—	2026-10-15
Nemotron 3.5 Super VL 120B-A12B	120B-A12B	NVFP4	M5 Max	128 GB	MLX	community30.6	—	2026-10-16
Gemma 3 12B	12B	Q4_K_M	M4 Pro	24 GB	MLX	estimated30	—	2026-02
Gemma 3 27B	27B	Q4_K_M	M5 Max	64 GB	Ollama	estimated30	—	2026-03
Mistral Small 3.2 24B	24B	Q4_K_M	M4 Max	48 GB	MLX	estimated30	—	2026-05
SmolLM3 3B	3B	Q4_K_M	M1	8 GB	Ollama	estimated30	—	2026-05
Devstral Small 24B	24B	Q4_K_M	M4 Max	48 GB	MLX	estimated30	—	2026-05
Qwen 3.6-27B	27B	Q4_K_M	M5 Max	64 GB	MLX	estimated30	—	2026-08
Gemma 4 12B	12B	Q4_K_M	M4 Pro	24 GB	MLX	estimated30	—	2026-10
Hunyuan Hy3	295B-A21B	Q4_K_M	M5 Ultra	256 GB	llama.cpp	estimated30	—	2026-10
Qwen 3.5 27B	27B	Q4_K_M	M5 Max	64 GB	llama.cpp	estimated30	—	2026-10
DeepSeek V4.1 Flash	552B-A16B	Q2 GGUF	M5 Max	128 GB	ds4	community29.6	—	2026-10-11
Qwen3-235B-A22B	235B	Q4_K_M	M5 Ultra	256 GB	MLX	estimated29	—	2026-08
Qwen3.8-27B	27.8B	Q4_K_M	M5 Max	128 GB	MLX	estimated29	—	2026-09
Qwen 3.5 122B-A10B	122B-A10B	Q4_K_M	M3 Max	128 GB	MLX	estimated29	—	2026-09
DeepSeek V4.1 Flash	552B-A16B	oQ4e	M5 Ultra	512 GB	MLX	estimated29	—	2026-10
Step-3.5-Flash	196B-A11B	Q4_K_M	M5 Max	128 GB	llama.cpp	estimated29	—	2026-10
MiniMax-M3	428B-A23B	4-bit	M3 Ultra	512 GB	MLX	community28.9	—	2026-06-15
Muse Glimmer 30B	30B	oQ4e	M4 Max	64 GB	MLX	community28.9	—	2026-10-21
Qwen3.8-Flash-Next	125B-A6B	oQ4e	M5 Max	128 GB	MLX	community28.5	—	2026-08-28
Ternary Bonsai 2 27B	27.36B	PQ2_0	M5 Pro	—	llama.cpp	sourced28.1	—	2026-09
Mistral 7B	7B	Q8_0	M4 Pro	24 GB	Ollama	estimated28	—	2026-02
DeepSeek R1 8B	8B	Q4_K_M	M6	24 GB	MLX	estimated28	—	2026-08
Granite 4.2 30B	29.3B	Q4_K_M	M5 Max	64 GB	Ollama	estimated28	—	2026-10
Kimi K2.5	1000B-A32B	3.5 bpw	M5 Ultra	512 GB	llama.cpp	estimated28	—	2026-10
Gemma 3 27B	27B	Q4_K_M	M4 Max	48 GB	MLX	estimated27	—	2026-02
GLM-4.5-Air	106B	Q4_K_M	M5 Max	128 GB	MLX	estimated27	—	2026-07
DeepSeek V4 Flash	284B-A13B	Q2_K	M3 Max	128 GB	MLX	community27	0.6s	2026-08
Muse Glimmer 30B	30B	Q4_K_M	M5 Max	64 GB	MLX	sourced27	0.4s	2026-08
Qwen 3.6-27B	27B	Q4_K_M	M4 Max	64 GB	MLX	estimated27	—	2026-08
GLM-5.3-Flash	320B-A18B	IQ3_XXS	M5 Max	128 GB	MLX	estimated27	—	2026-09
GLM-5.3	753B-A40B	Q2_K	M5 Ultra	256 GB	MLX	estimated27	—	2026-09
Beam 1.0	501B-A23B	Q4_K_M	M5 Ultra	512 GB	llama.cpp	estimated27	—	2026-10
Kimi K2.7 Code	1T-A32B	IQ3_S	M5 Ultra	512 GB	llama.cpp	estimated27	—	2026-10
Kimi K2.6	1000B-A32B	3.6 bpw	M5 Ultra	512 GB	llama.cpp	estimated27	—	2026-10
MiniMax-M3.1-Flash	428B-A23B	Q4_K_M	M5 Ultra	256 GB	llama.cpp	estimated27	—	2026-10
Nemotron 3.5 Bolt E4B	4B	OptiQ mixed 4/8-bit	M4	24 GB	MLX	community26.6	—	2026-10-24
Nemotron 3.5 Bolt E4B	4B	Q4_K_M	M4	16 GB	llama.cpp	community26.6	—	2026-10-24
Nemotron 3.5 Bolt E4B	4B	BF16	M3 Max	36 GB	MLX	community26.53	—	2026-10-23
Qwen3.8-Flash-Next	125B-A6B	4-bit	M3 Ultra	512 GB	MLX	community26.5	—	2026-08-31
Gemma 4 31B	31B	Q4_K_M	M5 Max	128 GB	MLX	estimated26	—	2026-04
Qwen 3 14B	14B	Q4_K_M	M4 Pro	24 GB	LM Studio	estimated26	—	2026-02
Ministral 3 14B	14B	Q4_K_M	M4 Pro	24 GB	Ollama	estimated26	—	2026-02
GLM-4.7-Flash	31B	Q4_K_M	M5 Max	64 GB	MLX	estimated26	—	2026-08
Qwen3.8-27B	27.8B	Q4_K_M	M4 Max	64 GB	MLX	estimated26	—	2026-09
Bonsai 27B	27B	Q1_0_g128	M4 Pro	—	llama.cpp	sourced26	—	2026-07
Ling-3.1-flash	560B-A25B	Q4_K_M	M5 Ultra	512 GB	llama.cpp	estimated26	—	2026-10
Granite 4.2 8B	8.8B	Q4_K_M	M6	24 GB	Ollama	estimated26	—	2026-10
MiniMax-M3.1-Flash	428B-A23B	oQ3e	M3 Ultra	256 GB	MLX	community25.3	—	2026-10-24
Qwen3.8-Flash-Next	125B-A6B	4-bit	M3 Ultra	512 GB	MLX	community25.1	—	2026-09-02
Llama 3.1 8B	8B	Q4_K_M	M3 Pro	18 GB	Ollama	estimated25	—	2026-01
Qwen 3 32B	32B	Q4_K_M	M5 Max	128 GB	Ollama	estimated25	—	2026-03
DeepSeek R1 32B	32B	Q4_K_M	M5 Max	64 GB	Ollama	estimated25	—	2026-03
Qwen 3.5 9B	9B	Q4_K_M	M6	24 GB	MLX	estimated25	—	2026-08
Granite 4.2 30B	29.3B	Q4_K_M	M4 Max	64 GB	MLX	estimated25	—	2026-10
QwQ 32B	32B	Q4_K_M	M5 Max	64 GB	llama.cpp	estimated25	—	2026-10
Qwen 3 32B	32B	unstated	M5 Max	128 GB	Ollama	sourced24.88	—	2026-09-21
Nemotron 3.5 Bolt 74B-A9B	74B-A9B	IQ2_XXS + Q8_0	M5 Pro	64 GB	llama.cpp	community24.6	—	2026-10-16
Phi-4 Mini	3.8B	Q4_K_M	M1	16 GB	Ollama	estimated24	—	2025-12
Qwen 3 8B	8B	Q8_0	M4 Pro	24 GB	MLX	estimated24	—	2026-02
GLM-4.5-Air	106B	Q4_K_M	M4 Max	128 GB	MLX	estimated24	—	2026-07
Muse Glimmer 30B	30B	Q4_K_M	M4 Max	48 GB	MLX	sourced24	0.5s	2026-08
GLM-5.3-Flash	320B-A18B	Q4_K_M	M3 Ultra	256 GB	MLX	estimated24	—	2026-09
MiMo-V2.6-Distill-Qwen-9B	9.4B	Q4_K_M	M6	24 GB	llama.cpp	estimated24	—	2026-10
Ternary Bonsai 2 27B	27.36B	Ternary	M5 Pro	48 GB	MLX	community23.6	—	2026-10-19
Gemma 4 E4B	4B	Q4_K_M	M1	8 GB	Ollama	estimated23	—	2026-04
Gemma 4 31B	31B	Q4_K_M	M4 Max	48 GB	MLX	estimated23	—	2026-04
Gemma 3 4B	4B	Q4_K_M	M1	8 GB	Ollama	estimated23	—	2025-12
Qwen 3 32B	32B	Q4_K_M	M4 Max	64 GB	MLX	estimated23	—	2026-02
DeepSeek R1 32B	32B	Q4_K_M	M4 Max	48 GB	LM Studio	estimated23	—	2026-01
GLM-4.7-Flash	31B	Q4_K_M	M4 Max	48 GB	MLX	estimated23	—	2026-08
Llama 3.3 70B	70B	Q4_K_M	M5 Ultra	96 GB	MLX	estimated23	—	2026-08
DeepSeek R1 70B	70B	Q4_K_M	M5 Ultra	96 GB	MLX	estimated23	—	2026-08
Qwen 2.5 72B	72B	Q4_K_M	M5 Ultra	96 GB	MLX	estimated23	—	2026-08
GLM 5.2	753B-A40B	IQ1_S	M3 Ultra	256 GB	LM Studio	community22	1.5s	2026-07
Mistral Small 3.2 24B	24B	Q4_K_M	M2 Max	32 GB	Ollama	estimated22	—	2026-08
GLM 5.2	753B-A40B	Q4_K_M	M5 Ultra	256 GB	llama.cpp	estimated22	—	2026-10
Hunyuan Hy3	295B-A21B	Q4_K_M	M3 Ultra	256 GB	LM Studio	estimated21	—	2026-08
Muse Spark Open	816B-A42B	oQ3e	M3 Ultra	512 GB	MLX	sourced21	—	2026-10-15
GLM-4.7	355B-A32B	Q4_K_M	M5 Ultra	256 GB	llama.cpp	estimated21	—	2026-10
Ternary Bonsai 2 27B	27.36B	PQ2_0	M4 Pro	64 GB	llama.cpp	community20.53	—	2026-09-22
DeepSeek V4.1 Flash	552B-A16B	oQ4e	M3 Ultra	512 GB	MLX	community20.23	—	2026-09-11
DeepSeek R1 8B	8B	Q4_K_M	M4	16 GB	MLX	estimated20	—	2026-02
Llama 3.1 8B	8B	Q4_K_M	M4	16 GB	Ollama	estimated20	—	2026-02
Ministral 8B	8B	Q4_K_M	M4	16 GB	MLX	estimated20	—	2026-02
Gemma 3 27B	27B	Q4_K_M	M3 Max	64 GB	MLX	estimated20	—	2026-01
Qwen 3.6-27B	27B	Q4_K_M	M3 Max	64 GB	Ollama	estimated20	—	2026-08
Apertus 1.5 8B	8B	Q4_K_M	M4	16 GB	Ollama	estimated20	—	2026-08
Qwen 3.6-27B	27B	Q4_K_M	M2 Max	32 GB	MLX	estimated20	—	2026-08
Gemma 3 27B	27B	Q4_K_M	M2 Max	32 GB	Ollama	estimated20	—	2026-08
Qwen3-235B-A22B	235B-A22B	Q4_K_M	M3 Ultra	256 GB	MLX	estimated20	—	2026-08
Qwen3.8-27B	27.8B	BF16	M5 Ultra	512 GB	MLX	sourced19.69	—	2026-10-15
Ling-3.1-flash	560B-A25B	MLX mixed 4/8-bit	M3 Ultra	512 GB	MLX	community19.5	—	2026-10-18
Mistral 7B	7B	Q4_K_M	M3	16 GB	Ollama	estimated19	—	2026-01
Llama 4 Scout	109B	Q4_K_M	M5 Max	128 GB	MLX	estimated19	—	2026-03
Qwen3.8-27B	27.8B	Q4_K_M	M3 Max	64 GB	MLX	estimated19	—	2026-09
GLM-5.3	753B-A40B	Q2_K	M3 Ultra	256 GB	MLX	estimated19	—	2026-09
Gemma 4 12B	12B	QAT	M6	32 GB	LM Studio	community19	—	2026-10
Beam 1.0	501B-A23B	Q4_K_M	M3 Ultra	512 GB	llama.cpp	estimated19	—	2026-10
Qwen 3.5 9B	9B	Q4_K_M	M4	16 GB	LM Studio	estimated18	—	2026-02
Muse Spark Open	816B-A42B	Q2_K	M3 Ultra	512 GB	llama.cpp	sourced18	—	2026-10-15
Ling-3.1-flash	560B-A25B	Q4_K_M	M3 Ultra	512 GB	llama.cpp	estimated18	—	2026-10
Granite 4.2 8B	8.8B	Q4_K_M	M4	16 GB	Ollama	estimated18	—	2026-10
DeepSeek V3.2-Speciale	685B-A37B	Q4_K_M	M5 Ultra	512 GB	llama.cpp	estimated18	—	2026-10
DeepSeek V3	685B-A37B	Q4_K_M	M5 Ultra	512 GB	llama.cpp	estimated18	—	2026-10
DeepSeek V3.2	685B-A37B	Q4_K_M	M5 Ultra	512 GB	llama.cpp	estimated18	—	2026-10
DeepSeek R1	671B-A37B	Q4_K_M	M5 Ultra	512 GB	llama.cpp	estimated18	—	2026-10
Qwen3.8-27B	27.8B	8-bit	M5 Max	128 GB	MLX	community17.9	—	2026-08-20
Qwen 3 8B	8B	Q4_K_M	M2	16 GB	Ollama	estimated17	—	2026-01
DeepSeek R1 8B	8B	Q4_K_M	M2	16 GB	Ollama	estimated17	—	2026-01
Ministral 8B	8B	Q4_K_M	M3	16 GB	LM Studio	estimated17	—	2026-01
DeepSeek R1 32B	32B	Q4_K_M	M3 Max	64 GB	Ollama	estimated17	—	2025-12
Llama 3.1 8B	8B	Q4_K_M	M2	8 GB	Ollama	estimated17	—	2025-12
GLM-5.3	753B-A40B	Q4_K_M	M5 Ultra	512 GB	MLX	estimated17	—	2026-09
MiMo-V2.6-Distill-Qwen-9B	9.4B	Q4_K_M	M4	16 GB	llama.cpp	estimated17	—	2026-10
GLM-5.1	754B-A40B	Q4_K_M	M5 Ultra	512 GB	llama.cpp	estimated17	—	2026-10
Qwen3.8-27B	27.8B	4-bit	M5 Pro	48 GB	LM Studio	community16.81	—	2026-10-19
Qwen3.8-27B	27.8B	4-bit	M5 Pro	48 GB	llama.cpp	sourced16.5	—	2026-10-15
Qwen3.8-27B	27.8B	4-bit	M5 Pro	48 GB	MLX	community16.33	—	2026-10-19
Llama 3.3 70B	70B	Q4_K_M	M3 Ultra	256 GB	Ollama	estimated16	—	2026-08
Phi-4 14B	14B	Q4_K_M	M6	24 GB	MLX	estimated16	—	2026-08
Mistral Large 3	675B-A41B	Q4_K_M	M5 Ultra	512 GB	llama.cpp	estimated16	—	2026-10
Qwen3-235B-A22B	235B-A22B	4.5 bpw	M5 Max	128 GB	llama.cpp	estimated16	—	2026-10
Qwen 3.5 9B	9B	Q4_K_M	M3	16 GB	Ollama	estimated15	—	2026-01
Qwen3-235B-A22B	235B	Q4_K_M	M5 Max	128 GB	MLX	estimated15	—	2026-04
Mistral Small 3.2 24B	24B	Q4_K_M	M4 Pro	32 GB	Ollama	estimated15	—	2026-05
Devstral Small 24B	24B	Q4_K_M	M4 Pro	32 GB	Ollama	estimated15	—	2026-05
GLM 5.2	753B-A40B	Q4_K_M	M3 Ultra	512 GB	MLX	community15	2.0s	2026-07
Qwen 3.6-27B	27B	Q4_K_M	M5 Pro	24 GB	MLX	estimated15	—	2026-08
Llama 3.3 70B	70B	Q4_K_M	M1 Ultra	128 GB	Ollama	estimated15	—	2026-08
DeepSeek R1 70B	70B	Q4_K_M	M1 Ultra	128 GB	Ollama	estimated15	—	2026-08
Gemma 3 27B	27B	Q4_K_M	M4 Pro	24 GB	LM Studio	estimated14	—	2026-02
Qwen 3.6-27B	27B	Q4_K_M	M4 Pro	24 GB	Ollama	estimated14	—	2026-08
Granite 4.2 30B	29.3B	Q4_K_M	M5 Pro	24 GB	Ollama	estimated14	—	2026-10
Ternary Bonsai 2 27B	27.36B	Ternary	M6	32 GB	MLX	community13.3	—	2026-10-23
Llama 3.3 70B	70B	4-bit	M5 Max	128 GB	MLX	sourced13.1	—	2026-09-21
Mistral 7B	7B	Q4_K_M	M1	16 GB	Ollama	estimated13	—	2025-12
Qwen3.8-27B	27.8B	Q4_K_M	M4 Pro	48 GB	Ollama	estimated13	—	2026-09
Gemma 4 12B	12B	Q4_K_M	M4	16 GB	MLX	estimated13	—	2026-10
Mistral Medium 3.5	128B	Q4_K_M	M5 Ultra	96 GB	MLX	estimated13	—	2026-10
Granite 4.2 30B	29.3B	Q4_K_M	M4 Pro	24 GB	Ollama	estimated13	—	2026-10
Qwen3.8-27B	27.8B	BF16	M3 Ultra	512 GB	MLX	sourced12.46	—	2026-10-15
Gemma 4 31B	31B	Q4_K_M	M4 Pro	24 GB	Ollama	estimated12	—	2026-04
Phi-4 14B	14B	Q4_K_M	M4	16 GB	Ollama	estimated12	—	2026-02
Qwen 3 32B	32B	Q4_K_M	M4 Pro	32 GB	Ollama	estimated12	—	2026-01
DeepSeek R1 70B	70B	Q4_K_M	M5 Max	128 GB	Ollama	estimated12	—	2026-03
Qwen 2.5 72B	72B	Q4_K_M	M5 Max	128 GB	Ollama	estimated12	—	2026-03
Hermes 4 70B	70B	Q4_K_M	M5 Max	128 GB	MLX	estimated12	—	2026-05
Apertus 1.5 70B	70B	Q4_K_M	M5 Max	128 GB	MLX	estimated12	—	2026-08
GLM-4.7-Flash	31B	Q4_K_M	M4 Pro	24 GB	Ollama	estimated12	—	2026-08
Ternary Bonsai 2 27B	27.36B	Ternary	M5	32 GB	MLX	community12	—	2026-10-04
DeepSeek R1 8B	8B	Q4_K_M	M1	16 GB	Ollama	estimated11	—	2025-11
Llama 3.1 8B	8B	Q4_K_M	M1	16 GB	Ollama	estimated11	—	2025-12
Gemma 3 12B	12B	Q4_K_M	M3	16 GB	Ollama	estimated11	—	2026-01
Gemma 3 12B	12B	Q4_K_M	M2	16 GB	Ollama	estimated11	—	2025-12
Qwen 3 8B	8B	Q4_K_M	M1	16 GB	Ollama	estimated11	—	2025-12
Hermes 4 70B	70B	Q4_K_M	M4 Max	128 GB	MLX	estimated11	—	2026-05
GLM-5.3	753B-A40B	Q4_K_M	M3 Ultra	512 GB	MLX	estimated11	—	2026-09
Qwen 3.5 9B	9B	Q4_K_M	M1	16 GB	Ollama	estimated10	—	2025-12
Qwen 3 14B	14B	Q4_K_M	M3	16 GB	Ollama	estimated10	—	2026-01
Phi-4 14B	14B	Q4_K_M	M2	16 GB	MLX	estimated10	—	2026-01
Ministral 3 14B	14B	Q4_K_M	M3	16 GB	LM Studio	estimated10	—	2026-01
Muse Glimmer 30B	30B	Q4_K_M	M4 Pro	24 GB	LM Studio	community10	0.8s	2026-08
Granite 4.2 8B	8.8B	Q4_K_M	M1	8 GB	Ollama	estimated10	—	2026-10
MiMo-V2.6-Distill-Qwen-9B	9.4B	Q4_K_M	M1	8 GB	llama.cpp	estimated10	—	2026-10
Qwen3.8-27B	27.8B	4-bit	M6	24 GB	MLX	community9.8	—	2026-10-09
Qwen3.8-27B	27.8B	QAT	M6	24 GB	LM Studio	community9.42	12.28s	2026-09-22
Qwen 3.6-27B	27B	Q4_K_M	M6	24 GB	MLX	estimated9	—	2026-08
Muse Glimmer 30B	30B	unstated	M6	32 GB	LM Studio	community9	—	2026-10
Mixtral 8x22B	141B-A39B	Q4_K_M	M5 Max	128 GB	llama.cpp	estimated9	—	2026-10
Llama 3.3 70B	70B	Q4_K_M	M2 Max	96 GB	Ollama	estimated8	—	2026-08
Gemma 4 31B	31B	QAT	M6	32 GB	LM Studio	community8	—	2026-10
Granite 4.2 30B	29.3B	Q4_K_M	M6	24 GB	MLX	estimated8	—	2026-10
Mistral Medium 3.5	128B	FP8	M5 Ultra	512 GB	MLX	sourced7.7	—	2026-10-15
Mistral Medium 3.5	128B	Q4_K_M	M5 Max	128 GB	MLX	estimated7	—	2026-10
DeepSeek V4.1 Flash	552B-A16B	4/8-bit mixed	M3 Ultra	512 GB	MLX	community6.53	—	2026-09-10
Mistral Medium 3.5	128B	Q4_K_M	M4 Max	128 GB	MLX	estimated6	—	2026-10
Mistral Medium 3.5	128B	FP8	M3 Ultra	512 GB	MLX	sourced4.95	—	2026-10-15
Llama 3.1 405B	405B	Q4_K_M	M5 Ultra	512 GB	MLX	estimated4	—	2026-08

Measured figures, and how far the estimate was off

Every row in the table above that is not an estimate: 47 published figures (vendor or press review) and 146 linked community runs, with the source, quant, runtime and prompt context each one reported. Formula is what the index's estimator gives for the same model, chip and quant with no measurement to anchor it; gap is how far the measured figure sits above (+) or below (−) that. Across the 137 rows the formula can cost, the median gap is 14% (87 within 20%). Sub-2-bit formats are compute-bound, so the bandwidth formula does not apply to them.

Model	Chip	RAM	Quant	Runtime	Context	tok/s	Formula	Gap	Source
Bonsai 27B	M4 Pro	—	Q1_0_g128	llama.cpp	tg128	sourced26	— compute-bound format	—	huggingface.coVendor model card: PrismML llama.cpp fork (Metal), llama-bench; 3.9 GB.
Bonsai 27B	M5 Pro	—	Q1_0_g128	llama.cpp	tg128	sourced44.2	— compute-bound format	—	huggingface.coVendor model card: PrismML llama.cpp fork (Metal), llama-bench; 3.9 GB.
Bonsai 27B	M5 Max	—	Q1_0_g128	llama.cpp	tg128	sourced66.4	— compute-bound format	—	huggingface.coVendor model card: PrismML llama.cpp fork (Metal), llama-bench; 3.9 GB.
DeepSeek V4 Flash	M3 Max	128 GB	Q2_K	MLX	not stated	community27	~27	0%	modelfit.io
DeepSeek V4 Flash	M5 Max	128 GB	Q2_K	MLX	not stated	community39	~39	-1%	modelfit.io
DeepSeek V4.1 Flashnot used to scale	M3 Ultra	512 GB	oQ4e	MLX	16K prompt	community38.7	~26	+51%	github.comoMLX 0.7.2 release notes (fused decode kernels, PR #4722): the 1017 -mtp checkpoint at oQ4e with MTP off, 32.8 -> 38.7 tok/s, measured at a 16K-token prompt. A long-prompt figure is a different workload from the index's plain-decode rows, so it is shown but does not anchor; the model's estimates still follow the 11 Sep 4K run (20.23).
DeepSeek V4.1 Flash	M3 Ultra	512 GB	oQ4e	MLX	4K	community20.23	~26	-21%	github.comBase V4.1 checkpoint (the 1017 snapshot has the same architecture). oMLX 0.7.0.dev2, -mtp checkpoint run with MTP off, Engram tables in RAM. 19.67 tok/s at 64K.
DeepSeek V4.1 Flashnot used to scale	M3 Ultra	512 GB	4/8-bit mixed	MLX	8K	community6.53	— quant not costable	—	huggingface.coPipeNetwork custom V4.1 runtime on mlx 0.32.2 / mlx-lm 0.31.3 (immature loader); 427.6 GB.
DeepSeek V4.1 Flashnot used to scale · SSD-streamed	M5 Max	128 GB	Q2 GGUF	ds4	2K	community29.6	— SSD-streamed	—	github.comSSD-streamed: 341 GiB Q2 GGUF with an 82 GB expert cache on a 128 GB Mac (sf-ds4-1flash fa51b38, Metal, no speculation); steady decode, median of 3.
Gemma 4 12B	M6	32 GB	QAT	LM Studio	not stated	community19	~19	0%	github.com
Gemma 4 26B-A4Bnot used to scale	M3 Ultra	512 GB	MXFP4_MOE	llama.cpp	TG32, depth 0	community87.8	~122	-28%	llamaperf.comllama.cpp b8783, llama-bench, flash attention on, mean of 5, MTP off; anonymous llamaperf submission.
Gemma 4 26B-A4B	M5 Max	—	Q4_K_M	llama.cpp	4K-token input	sourced107	~106	+1%	huggingface.coCompetitor baseline on Liquid AI's LFM2.5-24B-A2B card (Pipette, llama.cpp).
Gemma 4 26B-A4B	M6	32 GB	4-bit	MLX	~530-token prompt	community52.2	~47	+11%	github.comMac mini M6, 12-core GPU. SwiftLM (MLX-Swift) main@318f712 + PR #172; mlx-community/gemma-4-26b-a4b-it-4bit.
Gemma 4 26B-A4B	M6	32 GB	QAT	LM Studio	not stated	community48	~48	+1%	github.com
Gemma 4 31B	M5 Ultra	256 GB	QAT	MLX	512-token random prompt, 128 generated, empty context, mean of 2	community31	~51	-39%	bohemiansilicon.comMac Studio, mlx-lm 0.32 on macOS 27.0.1, mlx-community QAT 4-bit build. 27 tok/s at 8K and 21 at 32K. Published by Bohemian Silicon, which rents out this Mac.
Gemma 4 31B	M6	32 GB	QAT	LM Studio	not stated	community8	~8	0%	github.com
Gemma 4 E4B	M5 Pro	—	Q4_K_M	llama.cpp	decode at 4K context depth	sourced62.15	~91	-32%	huggingface.coCompetitor baseline on SparkLLM's Spark-X2.6-4B card chart 'Mac M5 Pro · 16-core' (the 16-core-GPU M5 Pro has the same 307 GB/s); llama.cpp build not stated.
GLM 5.2	M3 Ultra	256 GB	IQ1_S	LM Studio	not stated	community22	— compute-bound format	—	codersera.com
GLM 5.2	M3 Ultra	512 GB	Q4_K_M	MLX	not stated	community15	~11	+32%	kingy.ai
GLM-5.3-Flash	M5 Ultra	256 GB	MLX mixed 4/8-bit	MLX	1k	community61.7	— quant not costable	—	omlx.ai80-core GPU. oMLX v0.7.2, MTP/DFlash/SpecPrefill off; pipenetwork GLM-5.3-Flash-MLX-mixed-4_8bit (181.9 GB: routed experts 4-bit, the rest 8-bit; the card states no bpw, so the index cannot cost it and it does not anchor); 174.2 GB peak. 59.3 tok/s at 4k, 58.1 at 64k.
GLM-5.3-Flashnot used to scale	M5 Ultra	256 GB	unstated	llama.cpp	not stated	community39.7	~35 at Q4_K_M; source quant unstated	+15%	llamaperf.comllama.cpp (Metal), MTP off (61 tok/s with the 3-token MTP head, a different workload), 262K allocated; one user's r/LocalLLM post as summarised by llamaperf. Quantization not stated. Not used to scale other chips: the run may have used a branch build (MTP and a Metal deep-context fix were unmerged PRs when it ran) and its quant is unconfirmed.
GPT-oss 120B	M5 Max	128 GB	unstated	Ollama	not stated	sourced75.65	~56 at Q4_K_M; source quant unstated	+35%	tbreak.comMac Studio, 40-core GPU. tbreak review: Ollama (version not stated), 65 GB model file; the source does not state a quantization, so the row says 'unstated'. Ollama's gpt-oss:120b is the MXFP4 build OpenAI released (65 GB), so where this run scales the model's other chips it is costed at MXFP4. Repeated at 75.60 tok/s after a 20-run stress test.
GPT-oss 120B	M5 Ultra	256 GB	MXFP4	MLX	512-token random prompt, 128 generated, empty context, mean of 2	community120	~97	+24%	bohemiansilicon.comMac Studio, mlx-lm 0.32 on macOS 27.0.1, mlx-community MXFP4-Q8 build (MXFP4 experts, 8-bit elsewhere). 113 tok/s at 8K and 96 at 32K. Published by Bohemian Silicon, which rents out this Mac.
GPT-oss 20B	M5 Max	128 GB	unstated	Ollama	not stated	sourced107.51	~108 at Q4_K_M; source quant unstated	-1%	tbreak.comMac Studio, 40-core GPU. tbreak review: Ollama (version not stated); quantization not stated. Ollama's gpt-oss:20b is the MXFP4 build OpenAI released, so where this run scales the model's other chips it is costed at MXFP4.
GPT-oss 20B	M5 Ultra	256 GB	MXFP4	MLX	512-token random prompt, 128 generated, empty context, mean of 2	community184	~143	+29%	bohemiansilicon.comMac Studio, mlx-lm 0.32 on macOS 27.0.1, mlx-community MXFP4-Q8 build (MXFP4 experts, 8-bit elsewhere). 172 tok/s at 8K and 145 at 32K. Published by Bohemian Silicon, which rents out this Mac.
GPT-oss 20B	M6	32 GB	unstated	LM Studio	not stated	community45	~49 at Q4_K_M; source quant unstated	-8%	github.com
KAT-Coder-V2.5	M3 Max	48 GB	6-bit	MLX	1k	community69.5	~80	-14%	omlx.ai40-core GPU. oMLX v0.5.8.dev3, MTP/DFlash off; KAT-Coder-V2.5-Dev-6bit-XL-mlx. 67.7 tok/s at 4k.
KAT-Coder-V2.5	M4 Max	48 GB	unstated	LM Studio	up to ~5.9k tokens used	community74.2	~111 at Q4_K_M; source quant unstated	-33%	llm-bench.io40-core GPU part (16-core CPU), one anonymous llm-bench.io run. LM Studio with MLX-format OptiQ weights by model id; the source's quantization field is empty, so the row says 'unstated'. Thinking on; the figure is the mean of four task scenarios (73.2-75.6 tok/s each, at most 5,907 context tokens), with prefill reported separately.
KAT-Coder-V2.5not used to scale	M5	32 GB	oQ2e	MLX	pp1024/tg128	community49.5	~77	-36%	huggingface.coMacBook Air. oMLX v0.5.4, TurboQuant 4-bit KV cache, thinking off; 2-bit oQ2e (47.1 tok/s at pp4096).
KAT-Coder-V2.5	M5 Max	128 GB	OptiQ-4bit	MLX	1k	community89.3	~121	-26%	omlx.ai40-core GPU. oMLX v0.5.7, MTP/DFlash off; mlx-community/KAT-Coder-V2.5-Dev-OptiQ-4bit (mixed 4/8-bit). 84.8 tok/s at 4k.
Kolibri-1not used to scale	M1 Max	64 GB	4-bit	MLX	not stated	community52	~57	-9%	huggingface.comlx 0.32.3 / mlx-lm 0.32.0 with the repo's bundled kolibri1 loader (mlx-lm PR #1945 unmerged); 4-bit mixed, 4.54 bpw; lower bound of 52–56.
Kolibri-1not used to scale	M5 Max	128 GB	8-bit	MLX	1k	community78.9	~46	+71%	omlx.ai40-core GPU. oMLX v0.7.1rc1+omni (an unexplained build; mlx-lm support, PR #1945, is unmerged), so it does not anchor; Kolibri-1-mlx-8bit; 77.7 GB peak. 73.3 tok/s at 4k.
LFM2.5-2.6Bnot used to scale	M4 Max	—	FP16	llama.cpp	batch 1, temperature 0, up to 256 generated	sourced61	~73	-16%	liquid.aiLiquid AI's DSpark post: target-only decode on an M4 Max MacBook Pro, mean of five prompt sets (60–62), llama.cpp with Metal kernels from then-unmerged PRs #27383 / #27441, so it does not anchor. The 139 tok/s with the DSpark drafter is speculative decoding, not this row.
LFM2.5-2.6B	M5 Max	64 GB	Q4_K_M	MLX	not stated	sourced220	~220	0%	liquid.ai
LFM2.5-24B-A2B	M3 Ultra	96 GB	4-bit	MLX	4k	community115.6	~140	-17%	omlx.ai60-core GPU (819 GB/s, the same as the 80-core part). oMLX v0.7.1, MTP/DFlash off; LFM2.5-24B-A2B-MLX-4bit; 13.6 GB peak.
LFM2.5-24B-A2B	M4	24 GB	4-bit	MLX	1k	community59.9	~50	+19%	omlx.ai10-core GPU. oMLX v0.7.0, MTP/DFlash off; LiquidAI/LFM2.5-24B-A2B-MLX-4bit. 57.4 tok/s at 4k.
LFM2.5-24B-A2B	M4	32 GB	4-bit	MLX	1k	community59.3	~50	+18%	omlx.ai10-core GPU. oMLX v0.7.2, MTP/DFlash off; LFM2.5-24B-A2B-MLX-4bit; 13.1 GB peak. 58.2 tok/s at 4k.
LFM2.5-24B-A2B	M4 Max	48 GB	5-bit	MLX	4k	community89.7	~114	-21%	omlx.ai40-core GPU. oMLX v0.7.0, TurboQuant 8-bit KV cache, MTP/DFlash off; LiquidAI/LFM2.5-24B-A2B-MLX-5bit. 78.3 tok/s at 16k.
LFM2.5-24B-A2B	M5	32 GB	4-bit	MLX	4k	community74.2	~60	+23%	omlx.ai10-core GPU. oMLX v0.7.1rc1, all speculative options off; LiquidAI/LFM2.5-24B-A2B-MLX-4bit. The linked page features the 32k run (56.0 tok/s); 74.2 is the session's 4k row.
LFM2.5-24B-A2B	M5 Pro	48 GB	4-bit	MLX	4k	community122	~93	+32%	omlx.ai20-core GPU. oMLX v0.7.0, MTP/DFlash off; LFM2.5-24B-A2B-MLX-4bit; 13.7 GB peak. 104.3 tok/s at 16k.
LFM2.5-24B-A2B	M5 Pro	48 GB	oQ4e	MLX	1k	community113.5	~90	+26%	omlx.ai16-core GPU (the same 307 GB/s as the 20-core part). oMLX v0.6.4, MTP/DFlash off; LFM2.5-24B-A2B-oQ4e; 13.6 GB peak. 108.1 tok/s at 4k.
LFM2.5-24B-A2B	M5 Max	—	Q4_K_M	llama.cpp	4K-token input	sourced184	~127	+45%	huggingface.coVendor model card: Liquid AI's Pipette device-benchmarking infrastructure on llama.cpp (build not stated).
LFM2.5-24B-A2B	M5 Max	128 GB	8-bit	MLX	1k	community131.5	~96	+36%	omlx.ai40-core GPU. oMLX v0.7.1, MTP/DFlash off; LFM2.5-24B-A2B-MLX-8bit; 24.3 GB peak. 130.1 tok/s at 4k. Above 5 bits, so shown but never the reference.
Ling-3.0 Flash	M2 Max	96 GB	oQ4e	MLX	1k	community44	~38	+16%	omlx.ai38-core GPU. oMLX v0.7.2, MTP off (head bundled, not executed); Ling-3.0-flash-oQ4e-fp16-mtp; 68.3 GB peak. 40.9 tok/s at 4k, 32.7 at 32k.
Ling-3.0 Flash	M5 Max	128 GB	4-bit	MLX	1k	community68	~57	+20%	omlx.ai40-core GPU. oMLX v0.5.7, MTP/DFlash off; Ling-3.0-flash-MLX-4bit, 66.7 GB peak. 66.8 tok/s at 4k.
Ling-3.1-flashnot used to scale	M3 Ultra	512 GB	MLX mixed 4/8-bit	MLX	4k	community19.5	— quant not costable	—	omlx.ai80-core GPU. oMLX v0.7.1rc1, MTP/DFlash/expert offload off; Ling-3.1-flash-MLX-mixed-4_8bit, a conversion with no public repo (the page labels it 8-bit; bpw not published), running its KDA layers on a release candidate, so it does not anchor; 312.3 GB peak. The first Mac measurement of this model.
Llama 3.3 70B	M5 Max	128 GB	4-bit	MLX	not stated	sourced13.1	~12	+9%	tbreak.comMac Studio, 40-core GPU. tbreak review: 4-bit MLX, 41.2 GB peak; MLX 0.32.2 / mlx-lm 0.31.3 per the section's setup.
Maple Preview 20B-A1B	M4	16 GB	Ternary	MLX	not stated	sourced169	— compute-bound format	—	github.comDeepGrove's mlx-lm fork (mlx-lm-deepgrove) README, exact output head; its approximate --flash-head mode reaches 218, the figure behind the model card's '200+ tokens/sec on a Mac mini M4'. The README says the M4 figures come from an earlier version of the fork and does not state the M4 run's prompt length.
Maple Preview 20B-A1B	M5 Pro	48 GB	Ternary	MLX	512-token prompt, 256 generated	sourced387	— compute-bound format	—	github.comDeepGrove's mlx-lm fork (mlx-lm-deepgrove) README: 20-core GPU, 48 GB, macOS 26.4, MLX 0.32.0, battery power; exact output head, temperature 1.0, top-p 0.95, median of 6 runs. Its approximate --flash-head mode (477) is a different workload and is not entered. The fork is DeepGrove's only published MLX route.
Mellum2.1-12B-A2.5B-Thinkingnot used to scale	M4	16 GB	Q4_K_M	llama.cpp	short coding prompts	community50	~50	+1%	note.comMac mini M4, 10-core GPU. Homebrew llama.cpp llama-server, -ngl 99, -c 16384; official Q4_K_M (8.07 GB). Approximate figure, run before the Metal NaN fix (b11681).
Mellum2.1-12B-A2.5B-Thinking	M4	32 GB	6-bit	MLX	4k	community35.9	~39	-8%	omlx.ai10-core GPU. oMLX v0.7.1.dev1, MTP off; MLX 6-bit g64.
Mellum2.1-12B-A2.5B-Thinking	M5 Pro	64 GB	6-bit	MLX	1k	community112.7	~76	+47%	omlx.ai20-core GPU. oMLX v0.7.2, MTP/DFlash off; Mellum2.1-12B-A2.5B-Thinking-mlx-6bit-g64; 9.8 GB peak. 110.7 tok/s at 4k. Above 5 bits, so shown but never the reference.
Mellum2.1-12B-A2.5B-Thinking	M5 Max	64 GB	BF16	LM Studio	short prompts, long generations	community96.8	~65	+49%	llm-bench.ioLM Studio (llama.cpp engine), speculative decoding off; BF16 GGUF; median of 3.
MiMo-V2.6-Flash	M3 Ultra	256 GB	4-bit	MLX	128-token serial decode	community59.4	~32	+86%	huggingface.coRL checkpoint (same architecture as MOPD). oMLX 0.7.0.dev2 / MLX 0.32.2 / mlx-lm 0.31.3, MTP not executed; 4-bit affine dense + MXFP4 experts.
MiMo-V2.6-Flash	M3 Ultra	256 GB	4-bit	MLX	4K	community59	~28	+108%	github.comrapid-mlx 0.15.0, no MTP or speculative execution; mimo-v2.6-flash-4bit (171.7 GB). 49 tok/s at 30K.
MiMo-V2.6-Flash	M3 Ultra	512 GB	4-bit	MLX	1k	community55.1	~28	+94%	omlx.ai80-core GPU. oMLX v0.7.0, MTP/DFlash off; MiMo-V2.6-Flash-RL-MLX-4bit-MTP (the RL checkpoint, same architecture as MOPD); 154.3 GB peak. 53.7 tok/s at 4k in the same session (twfrx909).
MiMo-V2.6-Flashnot used to scale	M5 Ultra	256 GB	4-bit	MLX	1k	community76.4	~41	+88%	omlx.aiThe page reports a 64-core GPU with 256 GB, a configuration Apple does not offer (bandwidth is 1.2 TB/s either way), so it does not anchor or set the reference. oMLX v0.7.0rc1, MTP off; RL-MLX-4bit-MTP checkpoint (RL, same architecture as MOPD); 154.2 GB peak. 75.1 tok/s at 4k, 56.4 at 64k.
MiMo-V2.6-Flash	M5 Ultra	256 GB	4-bit	MLX	1k	community61.7	~41	+52%	omlx.ai80-core GPU. oMLX v0.7.0rc1, MTP/DFlash off; MiMo-V2.6-Flash-RL-MLX-4bit (the RL checkpoint, same architecture as MOPD); 156.7 GB peak.
MiniCPM-V 4.7 35B-A3B	M4 Pro	48 GB	oQ4e	MLX	1k	community81.8	~75	+10%	omlx.ai20-core GPU. oMLX v0.7.2, MTP/DFlash off; MiniCPM-V-4.7-35B-A3B-oQ4e; 20.9 GB peak. 80.4 tok/s at 4k.
MiniCPM-V 4.7 35B-A3B	M4 Pro	48 GB	oQ4e	MLX	1k	community75.2	~75	+1%	omlx.ai20-core GPU; the same machine as k6tli2pp, a second session. oMLX v0.7.2, MTP/DFlash off; MiniCPM-V-4.7-35B-A3B-oQ4e; 21.0 GB peak. 75.0 tok/s at 4k.
MiniCPM-V 4.7 35B-A3B	M4 Pro	64 GB	5-bit	MLX	1k	community48.2	~70	-31%	omlx.ai16-core GPU. oMLX v0.7.1.dev2, MTP/DFlash off. 47.9 tok/s at 4k.
MiniCPM-V 4.7 35B-A3B	M4 Max	64 GB	MXFP4	MLX	1k	community86.9	~114	-24%	omlx.ai40-core GPU. oMLX v0.7.1rc1, MTP/DFlash off; MiniCPM-V-4.7-35B-A3B-mxfp4; 22.1 GB peak.
MiniCPM-V 4.7 35B-A3B	M5 Pro	64 GB	MXFP4	MLX	1k	community56.6	~85	-34%	omlx.ai20-core GPU. oMLX v0.7.2, MTP/DFlash off; MiniCPM-V-4.7-35B-A3B-mxfp4; 22.1 GB peak. 50.3 tok/s at 32k.
MiniCPM-V 4.7 35B-A3B	M5 Max	64 GB	MXFP4	MLX	1k	community100.2	~120	-16%	omlx.ai40-core GPU. oMLX v0.7.1rc1, MTP/DFlash/SpecPrefill off; MiniCPM-V-4.7-35B-A3B-mxfp4. 101.6 tok/s at 4k.
MiniCPM-V 4.7 35B-A3B	M5 Max	128 GB	8-bit	MLX	1k	community84.7	~86	-2%	omlx.ai40-core GPU. oMLX v0.7.1, MTP/DFlash off; MiniCPM-V-4.7-35B-A3B-8bit; 38.2 GB peak. Above 5 bits, so shown but never the reference.
MiniMax-M3	M3 Ultra	512 GB	4-bit	MLX	1k	community28.9	~19	+51%	omlx.ai80-core GPU. oMLX v0.4.4rc2; MLX 4-bit. 20.8 tok/s at 4k, 18.9 at 32k.
MiniMax-M3.1-Flash	M3 Ultra	256 GB	oQ3e	MLX	1k	community25.3	~25	+1%	omlx.ai60-core GPU (819 GB/s, the same as the 80-core part). oMLX v0.7.2; mlx-community MiniMax-M3.1-Flash-oQ3e-mtp with MTP/DSpark, DFlash and expert offload off; 182.1 GB peak. 18.0 tok/s at 4k, 17.3 at 8k.
MiniMax-M3.1-Flash	M5 Ultra	256 GB	oQ3e	MLX	1k	community34.5	~36	-4%	omlx.ai80-core GPU. oMLX v0.7.2 on macOS 27.0.1; the oQ3e-mtp build (as the M3 Ultra row) with MTP, DFlash and expert offload off; 182.1 GB peak. 24.5 tok/s at 8k, 21.3 at 32k.
Mistral Medium 3.5	M3 Ultra	512 GB	FP8	MLX	8,192-token context, 128 generated	sourced4.95	~5	-1%	machinelearning.apple.comApple ML Research: mlx_lm.benchmark -p 8192 -g 128 -b 1 on one Mac Studio, native FP8.
Mistral Medium 3.5	M5 Ultra	512 GB	FP8	MLX	8,192-token context, 128 generated	sourced7.7	~7	+10%	machinelearning.apple.comApple ML Research: mlx_lm.benchmark -p 8192 -g 128 -b 1 on one Mac Studio, native FP8.
Muse Glimmer 30B	M4 Pro	24 GB	Q4_K_M	LM Studio	not stated	community10	~12	-17%	kingy.ai
Muse Glimmer 30B	M4 Max	64 GB	oQ4e	MLX	1k	community28.9	~23	+26%	omlx.ai40-core GPU. oMLX v0.7.2, MTP/DFlash off; Muse-Glimmer-30B-oQ4e; 15.9 GB peak. 26.2 tok/s at 32k.
Muse Glimmer 30B	M4 Max	48 GB	Q4_K_M	MLX	not stated	sourced24	~24	0%	huggingface.co
Muse Glimmer 30B	M5 Max	64 GB	Q4_K_M	MLX	not stated	sourced27	~27	0%	huggingface.co
Muse Glimmer 30B	M6	32 GB	unstated	LM Studio	not stated	community9	~8 at Q4_K_M; source quant unstated	+12%	github.com
Muse Spark Open	M3 Ultra	512 GB	oQ3e	MLX	1024-token prompt, 128 generated	sourced21	~14	+55%	huggingface.coHugging Face launch post: MLX (oMLX/mlx-lm, app not named); the pre-16-Oct oQ3e upload (369.5 GB = 344 GiB; the 16 Oct re-upload is 371.5 GB, 3.62 bpw), ~225 tok/s prefill.
Muse Spark Open	M3 Ultra	512 GB	Q2_K	llama.cpp	not stated	sourced18	~18	+2%	huggingface.coHugging Face launch post: llama serve -hf ggml-org/Muse-Spark-Open-816B-A42B-GGUF:Q2_K (imatrix, 304 GB); prompt length not stated.
Nemotron 3.5 Bolt 74B-A9Bnot used to scale	M3 Max	128 GB	IQ2_XXS	MLX	1k	community50.8	~50	+1%	omlx.ai40-core GPU. oMLX v0.7.2 with the bundle's custom loader, NVIDIA's 24 GB checkpoint, so it does not anchor; 23.9 GB peak. 47.5 tok/s at 4k.
Nemotron 3.5 Bolt 74B-A9Bnot used to scale	M3 Max	128 GB	4-bit	MLX	generation length not stated	community44	~24	+87%	blog.bytebunkerlabs.aimlx_lm with a ported nemotron_h_puzzle loader (stock mlx-lm cannot build Bolt), so it does not anchor; rapid-mlx MLX-4bit conversion with the MTP head dropped; 43.6 GB resident. The post is undated (about 16 Oct, updated 17 Oct).
Nemotron 3.5 Bolt 74B-A9Bnot used to scale	M3 Ultra	512 GB	IQ2_XXS	MLX	1k	community74.5	~87	-14%	omlx.ai80-core GPU. oMLX v0.7.1.dev1 with the bundle's custom loader, NVIDIA's 24 GB checkpoint (LiLiCorr bundle, DFlash off), so it does not anchor; 23.8 GB peak. 72.8 tok/s at 4k.
Nemotron 3.5 Bolt 74B-A9B	M3 Ultra	256 GB	4-bit	MLX	1024-token prompt, 96 generated	community56.5	~44	+27%	github.comRapid-MLX text loader (PR #4679, released in Rapid-MLX 0.16.2 on 16 Oct), MLX 0.32.4; 4-bit g64 with BF16 head, router and latent projections; batch 1, temperature 0, no speculation or KV quantization; median of three runs (56.29 / 56.50 / 56.50) on a 60-core GPU, shared machine. Published by the runtime's developers.
Nemotron 3.5 Bolt 74B-A9Bnot used to scale	M3 Ultra	96 GB	Q4_K_M	llama.cpp	tg128	community41.61	~44	-6%	github.comPatched build: llama.cpp f12aaa3 + the then-unmerged <9> map0 Metal fix (PR #30699, merged 20 Oct in b11755), llama-bench -fa 1 -r 3; community Q4_K_M from BF16 (45 GiB).
Nemotron 3.5 Bolt 74B-A9Bnot used to scale	M4 Pro	48 GB	IQ2_XXS	MLX	512-token coding answers, median of 5 at T 0.6	community34.6	~36	-5%	github.comMacBook Pro, 20-core GPU. oMLX 0.7.1rc1 (no drafter) loading NVIDIA's 24 GB checkpoint through the bundle's model file, so it does not anchor; the 19 Oct re-run with no run flagged (greedy 34.1; the 18 Oct run read 33.9 under desktop GPU load); 30.4 GB peak. Run by the Kapitsa engine's developers with their own harness.
Nemotron 3.5 Bolt 74B-A9Bnot used to scale	M5 Pro	48 GB	IQ2_XXS	MLX	512-token coding answers, median of 5 at T 0.6	community39	~40	-3%	github.comMacBook Pro, 20-core GPU. oMLX 0.7.1rc1 (no drafter) loading NVIDIA's 24 GB checkpoint through the bundle's model file, so it does not anchor; greedy 39.8; 30.3 GB peak. Run by the Kapitsa engine's developers with their own harness.
Nemotron 3.5 Bolt 74B-A9Bnot used to scale	M5 Pro	64 GB	IQ2_XXS + Q8_0	llama.cpp	random-text prompts, greedy, -c 262144	community24.6	— quant not costable	—	huggingface.co20-core GPU. llama-server 0.7.0-dev 620d222 (LM Studio Metal backend 2.59.0), built before PR #30699; UraionLabs' rewrite of NVIDIA's 24 GB GGUF with the 80 NVFP4 ssm tensors converted to Q8_0 (24.2 GB), so it does not anchor. NVIDIA's own file ran 12.8 tok/s on the same Mac (NVFP4 CPU fallback).
Nemotron 3.5 Bolt 74B-A9Bnot used to scale	M5 Max	64 GB	IQ2_XXS	MLX	1k	community73	~71	+4%	omlx.ai40-core GPU. oMLX v0.7.2 with the remote-code loader from NVIDIA's MLX bundle (txgsync ...-24GB-LiLiCorr-MLX, weights byte-identical to NVIDIA's 24 GB checkpoint: IQ2_XXS experts at ~2.06 bpw, NVFP4 Mamba, Q8_0 embedding/output), so it does not anchor; MTP/DFlash off; 23.9 GB peak. 66.2 tok/s at 64k.
Nemotron 3.5 Bolt 74B-A9B	M5 Max	128 GB	4-bit	MLX	128-token greedy sample	community71.7	~35	+107%	huggingface.coCommunity MLX port: MLX-VLM e17c49a on MLX 0.32.4; 4-bit affine g64 (43.15 GB), no MTP head in the checkpoint; 46.6 GB peak. Same figure in mlx-vlm PR #2528.
Nemotron 3.5 Bolt 74B-A9B	M5 Max	128 GB	5-bit	MLX	64-token greedy sample	community63.6	~30	+109%	huggingface.coCommunity MLX port: MLX-VLM e17c49a on MLX 0.32.4; 5-bit affine g64, vision encoder BF16; 59.6 GB peak.
Nemotron 3.5 Bolt 74B-A9B	M5 Max	128 GB	4-bit	MLX	4k	community57.9	~35	+67%	omlx.ai40-core GPU. oMLX v0.7.1rc1, MTP/DFlash/SpecPrefill off; NVIDIA-Nemotron-3.5-Bolt-74B-A9B-4bit; 47.4 GB peak. 56.3 tok/s at 16k.
Nemotron 3.5 Bolt 74B-A9Bnot used to scale	M5 Max	128 GB	8-bit	MLX	not stated	community37	~20	+88%	huggingface.coCommunity MLX port: mlx-vlm 0.7.8 + the uploader's nemotron_h_omni port; 8-bit g64 (~81 GB); lower bound of 37–41.
Nemotron 3.5 Bolt E4Bbinned GPU	M3 Max	36 GB	4-bit	MLX	short chat prompt, 256 generated, greedy	community72.98	— binned GPU	—	huggingface.coThe 36 GB M3 Max is the binned 30-core-GPU, 300 GB/s part. mlx-vlm 0.7.10 on MLX 0.32.4, 4-bit affine g64; decode-only gen_tps_reported from results/kl_results_release.json (the card table's 68.1 is wall-clock with prefill). The quantizer reports only 71.7% top-1 agreement with BF16 for this build.
Nemotron 3.5 Bolt E4Bbinned GPU	M3 Max	36 GB	6-bit	MLX	short chat prompt, 256 generated, greedy	community55.22	— binned GPU	—	huggingface.coThe 36 GB M3 Max is the binned 30-core-GPU, 300 GB/s part. mlx-vlm 0.7.10 on MLX 0.32.4, 6-bit affine g64; decode-only gen_tps_reported (wall-clock 46.8). 92.5% top-1 agreement with BF16, the quality-safe build.
Nemotron 3.5 Bolt E4Bbinned GPU	M3 Max	36 GB	8-bit	MLX	short chat prompt, 256 generated, greedy	community45.26	— binned GPU	—	huggingface.coThe 36 GB M3 Max is the binned 30-core-GPU, 300 GB/s part. mlx-vlm 0.7.10 on MLX 0.32.4, 8-bit affine g64; decode-only gen_tps_reported (wall-clock 36.6).
Nemotron 3.5 Bolt E4Bbinned GPU	M3 Max	36 GB	BF16	MLX	short chat prompt, 256 generated, greedy	community26.53	— binned GPU	—	huggingface.coThe 36 GB M3 Max is the binned 30-core-GPU, 300 GB/s part. mlx-vlm 0.7.10 on MLX 0.32.4; decode-only gen_tps_reported (wall-clock 11.4).
Nemotron 3.5 Bolt E4B	M4	24 GB	OptiQ mixed 4/8-bit	MLX	code prompt, batch 1, greedy, thinking off, best of 3	community26.6	— quant not costable	—	huggingface.comlx-optiq (optiq serve). OptiQ mixed precision: 124 of 345 language-tower layers at 4-bit and 221 at 8-bit (6.53 GB language tower), vision tower BF16; 26.3–26.6 tok/s across four tasks. The card's drafter and n-gram columns (45–94 tok/s) are speculative decoding, not this row.
Nemotron 3.5 Bolt E4Bnot used to scale	M4	16 GB	Q4_K_M	llama.cpp	short Japanese prompt, ~400 characters generated, -c 8192	community26.6	~39	-32%	note.comMac mini M4. Homebrew llama.cpp build 10964, NVIDIA's official 6.18 GB Q4_K_M GGUF, no draft model; a single run, and the article does not name the tool or timing field behind the figure, so it does not anchor.
Nemotron 3.5 Bolt E4B	M5 Pro	64 GB	oQ8e	MLX	1k	community46.4	— quant not costable	—	omlx.ai20-core GPU. oMLX v0.7.2, MTP/DFlash off; NVIDIA-Nemotron-3.5-Bolt-E4B-oQ8e; 8.1 GB peak. 42.3 tok/s at 4k (uhc5jo38).
Nemotron 3.5 Lightning	M5 Pro	48 GB	4-bit	MLX	512-token coding answers, median of 5 at T 0.6	community93.73	~83	+13%	github.comMacBook Pro, 20-core GPU. mlx-lm 0.32.2 (MLX 0.32.4), mlx-community 4-bit, no MTP path; greedy 96.76; no contention. Run by the Kapitsa engine's developers with their own harness.
Nemotron 3.5 Lightning	M5 Pro	48 GB	Q4_K_M	LM Studio	512-token coding answers, median of 5 at T 0.6	community72.3	~83	-13%	github.comMacBook Pro, 20-core GPU. LM Studio llama.cpp runtime 2.60.0 (b11698), lmstudio-community Q4_K_M (no MTP head); greedy 72.2. Run by the Kapitsa engine's developers with their own harness.
Nemotron 3.5 Lightning	M5 Max	128 GB	4-bit	MLX	512-token coding answers, median of 5 at T 0.6, thinking off	community164.7	~117	+40%	github.com40-core GPU. oMLX 0.7.1rc1, mlx-community 4-bit, no MTP or speculation; greedy 166.6. Run by the Kapitsa engine's developers with their own harness.
Nemotron 3.5 Lightning	M5 Max	128 GB	4-bit	MLX	512-token coding answers, median of 5 at T 0.6, thinking off	community139.3	~117	+19%	github.com40-core GPU. mlx-lm 0.32.2, mlx-community 4-bit (no MTP path); greedy 145.6. Run by the Kapitsa engine's developers with their own harness.
Nemotron 3.5 Lightning	M5 Max	128 GB	Q4_0	llama.cpp	512-token coding answers, median of 5 at T 0.6, thinking off	community116.8	~118	-1%	github.com40-core GPU. llama.cpp 0.7.0 (b11669), ggml-org Q4_0, no speculation; greedy 113.2. WebKit GPU contention flagged in the prefill phases only. Run by the Kapitsa engine's developers with their own harness.
Nemotron 3.5 Lightning	M5 Max	—	Q4_K_M	llama.cpp	4K-token input	sourced114	~117	-3%	huggingface.coCompetitor baseline on Liquid AI's LFM2.5-24B-A2B card (Pipette, llama.cpp).
Nemotron 3.5 Lightning	M6	32 GB	Q4_K_M	llama.cpp	not stated	community45	~56	-20%	github.com
Nemotron 3.5 Super VL 120B-A12B	M4 Max	128 GB	4-bit	MLX	1k	community50.8	~25	+100%	omlx.ai40-core GPU. oMLX v0.7.0, MTP/DFlash off; Duckets MLX-4bit (group 64, 4.57 bpw); 69.8 GB peak. 50.2 tok/s at 4k.
Nemotron 3.5 Super VL 120B-A12B	M5 Max	128 GB	4-bit	MLX	512-token coding answers, median of 5 at T 0.6	community51.8	~27	+94%	github.com40-core GPU. oMLX 0.7.1rc1, no speculation; rapid-mlx text-only MLX 4-bit (69.5 GB); greedy 50.4; 74.8 GB peak. The session's only engine run without a contention flag. Run by the Kapitsa engine's developers with their own harness.
Nemotron 3.5 Super VL 120B-A12B	M5 Max	128 GB	4-bit	MLX	512-token coding answers, median of 5 at T 0.6	community45.5	~27	+70%	github.com40-core GPU. mlx-lm 0.32.2 on the same rapid-mlx text-only 4-bit build; greedy 45.4; GPU contention flagged in that session. Run by the Kapitsa engine's developers with their own harness.
Nemotron 3.5 Super VL 120B-A12B	M5 Max	128 GB	Q4_0	llama.cpp	512-token coding answers, median of 5 at T 0.6	community35.9	~27	+32%	github.com40-core GPU. llama.cpp 0.7.0, ggml-org Q4_0, no speculation; greedy 35.4. Run by the Kapitsa engine's developers with their own harness.
Nemotron 3.5 Super VL 120B-A12B	M5 Max	128 GB	NVFP4	MLX	160 generated tokens, greedy	community30.6	~27	+13%	github.commlx-vlm PR #2528 (merged 16 Oct) on MLX 0.32.4, MTP off; NVFP4 weights 75.0 GB. 57.1 tok/s with the native MTP head (not a plain-decode figure).
Nemotron 3.5 Super VL 120B-A12B	M5 Ultra	96 GB	4-bit	MLX	1k	community74.3	~49	+52%	omlx.ai64-core GPU (1.2 TB/s, the same as the 80-core part). oMLX v0.7.1rc1, MTP/DFlash off; NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-MLX-4bit; 70.0 GB peak.
North Mini Code 1.0	M5	32 GB	4-bit	MLX	1k	community34.2	~52	-34%	omlx.ai10-core GPU. oMLX v0.6.4, TurboQuant 4-bit KV cache, MTP/DFlash off. 30.5 tok/s at 4k.
North Mini Code 1.0	M5 Pro	64 GB	4-bit	MLX	1k	community69.8	~83	-16%	omlx.ai20-core GPU. oMLX v0.4.4rc1; MLX 4-bit. 61.8 tok/s at 4k.
North Mini Code 1.0	M5 Max	64 GB	4-bit	MLX	1k	community119.7	~117	+2%	omlx.ai40-core GPU. oMLX v0.4.4; MLX 4-bit (repo not stated). 106.8 tok/s at 4k.
Qwen 3 30B-A3B	M4 Max	128 GB	4-bit	MLX	not stated	sourced110	~111	-1%	arxiv.orgvllm-mlx serving on MLX (paper's figure 109.7); the paper's plain mlx-lm run is 107.4 tok/s.
Qwen 3 30B-A3B	M4 Max	128 GB	4-bit	llama.cpp	not stated	sourced90	~111	-19%	arxiv.org
Qwen 3 30B-A3B	M5 Max	128 GB	unstated	MLX	not stated	sourced130.63	~117 at Q4_K_M; source quant unstated	+11%	tbreak.comMac Studio, 40-core GPU. tbreak review: MLX 0.32.2 / mlx-lm 0.31.3; quantization not stated.
Qwen 3 30B-A3B	M6	32 GB	unstated	MLX	not stated	sourced62.01	~56 at Q4_K_M; source quant unstated	+11%	tbreak.comMac mini M6, 12-core GPU. tbreak review: MLX 0.32.2 / mlx-lm 0.31.3; quantization not stated (18.0 GB peak).
Qwen 3 32B	M5 Max	128 GB	unstated	Ollama	not stated	sourced24.88	~25 at Q4_K_M; source quant unstated	0%	tbreak.comMac Studio, 40-core GPU. tbreak review: Ollama (version not stated); quantization not stated.
Qwen 3 4B	M6	32 GB	unstated	MLX	not stated	sourced53.35	~54 at Q4_K_M; source quant unstated	-1%	tbreak.comMac mini M6, 12-core GPU. tbreak review: MLX 0.32.2 / mlx-lm 0.31.3; quantization not stated.
Qwen 3 4B	M6	24 GB	8-bit	LM Studio	short prompt	community31.47	~30	+5%	nyaa.shMac mini M6. Qwen3-4B-Thinking-2507; LM Studio (engine not stated); single run.
Qwen 3 8B	M5 Pro	48 GB	4-bit	llama.cpp	single stream; prompt length not stated	sourced54.4	~49	+11%	frandroid.comFrandroid's RTX Spark review: MacBook Pro 14 M5 Pro (18-core CPU, 48 GB), llama.cpp b11582 on Metal, a 5 GB 4-bit GGUF whose type the review does not name.
Qwen 3.5 122B-A10B	M3 Ultra	96 GB	unstated	LM Studio	not stated	sourced60	~41 at Q4_K_M; source quant unstated	+48%	bgr.com
Qwen 3.5 122B-A10B	M3 Ultra	512 GB	4-bit	MLX	512-token prompt, 128 generated	community58.6	~41	+44%	github.comMac Studio, 80-core GPU, 512 GB, macOS 26.5.1. mlx_lm.benchmark -p 512 -g 128 -n 5 (mlx-lm 0.31.3, MLX 0.32.2): plain decode with no HTTP server or chat template, median of the five trial lines in the repo's engine.json; mlx-community/Qwen3.5-122B-A10B-4bit. The repo's headline test streams the same cell through mlx_lm.server (thinking and prompt cache off): 51.3 tok/s. The source discloses a stuck background process on one of the M3 Ultra's 32 CPU cores during these runs, which can only have slowed it.
Qwen 3.5 122B-A10B	M5 Max	128 GB	Q4_K_M	llama.cpp	~64-token prompt, 512 generated	community42.9	~32	+36%	github.comMacBook Pro 14, 40-core GPU. llama.cpp b8500 llama-server, unsloth Q4_K_M, median of 5; other sessions on the same machine gave 38.5–39.4.
Qwen 3.5 122B-A10B	M5 Ultra	256 GB	4-bit	MLX	512-token prompt, 128 generated	community87.7	~57	+54%	github.comMac Studio, 80-core GPU, 256 GB, macOS 27.0. mlx_lm.benchmark -p 512 -g 128 -n 5 (mlx-lm 0.31.3, MLX 0.32.2): plain decode with no HTTP server or chat template, median of the five trial lines in the repo's engine.json; mlx-community/Qwen3.5-122B-A10B-4bit. The repo's headline test streams the same cell through mlx_lm.server (thinking and prompt cache off): 77.5 tok/s.
Qwen 3.5 122B-A10B	M5 Ultra	256 GB	unstated	LM Studio	not stated	sourced80	~57 at Q4_K_M; source quant unstated	+41%	bgr.com
Qwen 3.5 27B	M5 Ultra	256 GB	4-bit	MLX	512-token random prompt, 128 generated, empty context, mean of 2	community55	~57	-4%	bohemiansilicon.comMac Studio, mlx-lm 0.32 on macOS 27.0.1, mlx-community 4-bit MLX conversion. Published by Bohemian Silicon, which rents out this Mac.
Qwen 3.5 35B-A3B	M5 Ultra	256 GB	4-bit	MLX	512-token random prompt, 128 generated, empty context, mean of 2	community162	~148	+9%	bohemiansilicon.comMac Studio, mlx-lm 0.32 on macOS 27.0.1, mlx-community 4-bit MLX conversion. Published by Bohemian Silicon, which rents out this Mac.
Qwen 3.5 4B	M5 Pro	—	Q4_K_M	llama.cpp	decode at 4K context depth	sourced65.82	~91	-28%	huggingface.coCompetitor baseline on SparkLLM's Spark-X2.6-4B card chart 'Mac M5 Pro · 16-core' (the 16-core-GPU M5 Pro has the same 307 GB/s); llama.cpp build not stated.
Qwen 3.5 9B	M5 Ultra	256 GB	4-bit	MLX	512-token random prompt, 128 generated, empty context, mean of 2	community167	~147	+14%	bohemiansilicon.comMac Studio, mlx-lm 0.32 on macOS 27.0.1, mlx-community 4-bit MLX conversion. Published by Bohemian Silicon, which rents out this Mac.
Qwen 3.6-35B-A3B	M3 Ultra	512 GB	4-bit	MLX	512-token prompt, 128 generated	community106.4	~131	-19%	github.comMac Studio, 80-core GPU, 512 GB, macOS 26.5.1. mlx_lm.benchmark -p 512 -g 128 -n 5 (mlx-lm 0.31.3, MLX 0.32.2): plain decode with no HTTP server or chat template, median of the five trial lines in the repo's engine.json; mlx-community/Qwen3.6-35B-A3B-4bit. The repo's headline test streams the same cell through mlx_lm.server (thinking and prompt cache off): 86.3 tok/s. The source discloses a stuck background process on one of the M3 Ultra's 32 CPU cores during these runs, which can only have slowed it.
Qwen 3.6-35B-A3Bnot used to scale	M3 Ultra	512 GB	Q8_0	llama.cpp	TG128 from empty context	community81.2	~101	-19%	llamaperf.comllama.cpp b49650adb, flash attention on, F16 KV; anonymous llamaperf submission.
Qwen 3.6-35B-A3B	M5 Pro	48 GB	4-bit	LM Studio	~85-token prompt, 512-token coding answers, median of 5 at T 0.6	community95.62	~83	+16%	github.comMacBook Pro, 20-core GPU. LM Studio MLX runtime 1.13.1, lmstudio-community MLX 4-bit; greedy 97.85; flagged for 511 of 512 completion tokens. Run by the Kapitsa engine's developers with their own harness.
Qwen 3.6-35B-A3B	M5 Pro	48 GB	4-bit	MLX	~85-token prompt, 512-token coding answers, median of 5 at T 0.6	community94.3	~83	+14%	github.comMacBook Pro, 20-core GPU. mlx-vlm server 0.7.8, no speculation; greedy 97.43. Only the session's cached 16K follow-up phase was invalid; the decode phase is valid. Run by the Kapitsa engine's developers with their own harness.
Qwen 3.6-35B-A3B	M5 Pro	48 GB	Q4_K_M	llama.cpp	~85-token prompt, 512-token coding answers, median of 5 at T 0.6	community81.96	~83	-1%	github.comMacBook Pro, 20-core GPU. llama.cpp b11669 llama-server on Ollama's qwen3.6:35b-a3b-mtp-q4_K_M GGUF with drafting off (MTP n-max 2 reached 107.3, a different workload); greedy 82.19. Run by the Kapitsa engine's developers with their own harness.
Qwen 3.6-35B-A3B	M5 Pro	48 GB	Q4_K_M	Ollama	~85-token prompt, 512-token coding answers, median of 5 at T 0.6	community79.48	~83	-4%	github.comMacBook Pro, 20-core GPU. Ollama 0.40.6 on its qwen3.6:35b-a3b-mtp-q4_K_M GGUF with drafting off (draft_num_predict 0; the shipped MTP depth 2 reached 102.4, a different workload); greedy 81.24. Run by the Kapitsa engine's developers with their own harness.
Qwen 3.6-35B-A3B	M5 Pro	48 GB	4-bit	MLX	~85-token prompt, 512-token coding answers, median of 5 at T 0.6	community77.8	~83	-6%	github.comMacBook Pro, 20-core GPU. mlx-lm 0.32.2 (MLX 0.32.4), no MTP path; greedy 83.75. Run by the Kapitsa engine's developers with their own harness.
Qwen 3.6-35B-A3B	M5 Pro	48 GB	4-bit	MLX	~85-token prompt, 512-token coding answers, median of 5 at T 0.6	community75.66	~83	-9%	github.comMacBook Pro, 20-core GPU. Rapid-MLX 0.16.3 (mlx 0.32.4, mlx-lm 0.31.3), MLX 4-bit, no speculation (its catalog turns it off for this MoE); greedy 77.64. Run last in the session (15:27). Run by the Kapitsa engine's developers with their own harness.
Qwen 3.6-35B-A3B	M5 Pro	48 GB	4-bit	llama.cpp	single stream; prompt length not stated	sourced68.7	~83	-17%	frandroid.comFrandroid's RTX Spark review: MacBook Pro 14 M5 Pro (18-core CPU, 48 GB), llama.cpp b11582 on Metal (llama-bench), a 22 GB 4-bit GGUF whose type the review does not name.
Qwen 3.6-35B-A3B	M5 Max	128 GB	4-bit	MLX	not stated	community126	~117	+7%	omlx.ai
Qwen 3.6-35B-A3B	M5 Max	—	Q4_K_M	llama.cpp	4K-token input	sourced118	~117	+1%	huggingface.coCompetitor baseline on Liquid AI's LFM2.5-24B-A2B card (Pipette, llama.cpp).
Qwen 3.6-35B-A3B	M5 Max	128 GB	Q8_0	llama.cpp	128-token prompt	community92.9	~86	+8%	github.com40-core GPU. llama-server (Homebrew Metal build), -fa on, -c 16384, MTP flags off; 400 tokens, median of 3. 86.9 tok/s at 8k.
Qwen 3.6-35B-A3B	M5 Ultra	256 GB	4-bit	MLX	512-token prompt, 128 generated	community153.4	~148	+4%	github.comMac Studio, 80-core GPU, 256 GB, macOS 27.0. mlx_lm.benchmark -p 512 -g 128 -n 5 (mlx-lm 0.31.3, MLX 0.32.2): plain decode with no HTTP server or chat template, median of the five trial lines in the repo's engine.json; mlx-community/Qwen3.6-35B-A3B-4bit. The repo's headline test streams the same cell through mlx_lm.server (thinking and prompt cache off): 126.0 tok/s.
Qwen 3.6-35B-A3B	M6	32 GB	4-bit	MLX	not stated	community64	~56	+14%	github.com
Qwen3.8-27B	M3 Ultra	96 GB	Q4_K_M	LM Studio	not stated	sourced40	~38	+5%	bgr.com
Qwen3.8-27B	M3 Ultra	512 GB	4-bit	MLX	512-token prompt, 128 generated	community37.6	~38	-1%	github.comMac Studio, 80-core GPU, 512 GB, macOS 26.5.1. mlx_lm.benchmark -p 512 -g 128 -n 5 (mlx-lm 0.31.3, MLX 0.32.2): plain decode with no HTTP server or chat template, median of the five trial lines in the repo's engine.json; mlx-community/Qwen3.8-27B-4bit. The repo's headline test streams the same cell through mlx_lm.server (thinking and prompt cache off): 32.8 tok/s. The source discloses a stuck background process on one of the M3 Ultra's 32 CPU cores during these runs, which can only have slowed it.
Qwen3.8-27B	M3 Ultra	512 GB	oQ4e	MLX	6,091-token prompt	sourced31	~36	-14%	macstories.netMacStories review: oMLX 0.7.0.dev2, MTP off, thinking off, single run; Qwen3.8-27B-oQ4e-mtp checkpoint.
Qwen3.8-27B	M3 Ultra	512 GB	BF16	MLX	8,192-token context, 128 generated	sourced12.46	~11	+13%	machinelearning.apple.comApple ML Research: mlx_lm.benchmark -p 8192 -g 128 -b 1 on one Mac Studio.
Qwen3.8-27B	M5 Pro	48 GB	4-bit	LM Studio	512-token coding answers, median of 5 at T 0.6	community16.81	~15	+12%	github.comMacBook Pro, 20-core GPU. LM Studio MLX runtime 1.13.1, lmstudio-community MLX 4-bit; greedy 16.88; flagged for 511 of 512 completion tokens. Run by the Kapitsa engine's developers with their own harness.
Qwen3.8-27B	M5 Pro	48 GB	4-bit	llama.cpp	single stream; prompt length not stated	sourced16.5	~15	+10%	frandroid.comFrandroid's RTX Spark review: MacBook Pro 14 M5 Pro (18-core CPU, 48 GB), llama.cpp b11582 on Metal, a 16.5 GB 4-bit GGUF whose type the review does not name.
Qwen3.8-27B	M5 Pro	48 GB	4-bit	MLX	512-token coding answers, median of 5 at T 0.6	community16.33	~15	+9%	github.comMacBook Pro, 20-core GPU. mlx-lm 0.32.2 (MLX 0.32.4), no MTP path; greedy 16.92. Run by the Kapitsa engine's developers with their own harness.
Qwen3.8-27B	M5 Max	128 GB	8-bit	MLX	short prompt, 400 tokens	community17.9	~16	+12%	github.commlx-dspark 0.14 --mode baseline (no drafter) on MLX 0.32, greedy; lmstudio-community/Qwen3.8-27B-MLX-8bit.
Qwen3.8-27B	M5 Ultra	256 GB	Q4_K_M	LM Studio	not stated	sourced55	~56	-2%	bgr.com
Qwen3.8-27B	M5 Ultra	256 GB	4-bit	MLX	512-token prompt, 128 generated	community54.7	~56	-2%	github.comMac Studio, 80-core GPU, 256 GB, macOS 27.0. mlx_lm.benchmark -p 512 -g 128 -n 5 (mlx-lm 0.31.3, MLX 0.32.2): plain decode with no HTTP server or chat template, median of the five trial lines in the repo's engine.json; mlx-community/Qwen3.8-27B-4bit. The repo's headline test streams the same cell through mlx_lm.server (thinking and prompt cache off): 49.2 tok/s.
Qwen3.8-27B	M5 Ultra	256 GB	oQ4e	MLX	6,091-token prompt	sourced48	~53	-9%	macstories.netMacStories review: oMLX 0.7.0.dev2, MTP off, thinking off, single run; Qwen3.8-27B-oQ4e-mtp checkpoint.
Qwen3.8-27B	M5 Ultra	256 GB	Q4_K_M	llama.cpp	ISL 2048 / OSL 512, depth 0	sourced46.27	~56	-17%	tomshardware.com80-core GPU. Tom's Hardware review; llama.cpp, no MTP.
Qwen3.8-27B	M5 Ultra	512 GB	BF16	MLX	8,192-token context, 128 generated	sourced19.69	~17	+16%	machinelearning.apple.comApple ML Research: mlx_lm.benchmark -p 8192 -g 128 -b 1 on one Mac Studio.
Qwen3.8-27Bnot used to scale	M6	24 GB	4-bit	MLX	525-token prompt	community9.8	~8	+23%	llamaperf.comMac mini M6. mlx-vlm 0.7.3, MTP/speculative off; mlx-community 4-bit; single run, anonymous llamaperf report.
Qwen3.8-27B	M6	24 GB	QAT	LM Studio	short prompt	community9.42	~8	+18%	nyaa.shMac mini M6. 4-bit QAT MLX in LM Studio; single run, medium reasoning.
Qwen3.8-Flash-Nextnot used to scale	M3 Ultra	512 GB	4-bit	MLX	not stated	community26.5	~62	-57%	huggingface.coRockTalk mlx_qwen4exp custom port, plain greedy, 26.4–26.6 (llama.cpp Metal on the same machine: 26.4); 4-bit affine g64.
Qwen3.8-Flash-Nextnot used to scale	M3 Ultra	512 GB	4-bit	MLX	short prompt	community25.1	~62	-59%	huggingface.cooMLX 0.6.3, mlx-community 4-bit g32; wall-clock including a short prefill, so a floor (mean of 2).
Qwen3.8-Flash-Nextnot used to scale	M5 Max	128 GB	oQ4e	MLX	512-token coding answers, median of 5 at T 0.6	community69.7	~50	+39%	github.com40-core GPU. oMLX 0.7.1rc1, MTP off; decode-phase GPU contention of 14–16% was flagged, so it does not anchor; greedy 66.8. Run by the Kapitsa engine's developers with their own harness.
Qwen3.8-Flash-Next	M5 Max	128 GB	oQ4e	MLX	4k	community58.7	~47	+25%	omlx.ai40-core GPU. oMLX v0.7.2, MTP/DFlash off; Qwen3.8-Flash-Next-oQ4e-mtp; 69.7 GB peak. 66.4 tok/s at 16k (non-monotonic).
Qwen3.8-Flash-Next	M5 Max	128 GB	Q4_K_M	Ollama	512-token coding answers, median of 5 at T 0.6	community50.1	~49	+2%	github.com40-core GPU. Ollama 0.40.6 GGUF runner, Q4_K_M tag, MTP off; greedy 48.3. Its n-gram table is memory-mapped from SSD (an auxiliary table, not the weights). Run by the Kapitsa engine's developers with their own harness.
Qwen3.8-Flash-Next	M5 Max	128 GB	4-bit	MLX	coding task (prompt length not stated)	community47	~49	-4%	mtplx.comMTPLX 2.10.0 mtplx serve, plain autoregressive (MTP off); flat 4-bit g64 'Bare Speed' pack. Published by the runtime's author.
Qwen3.8-Flash-Next	M5 Max	128 GB	IQ4_NL	llama.cpp	512-token coding answers, median of 5 at T 0.6	community46.4	~50	-7%	github.com40-core GPU. llama.cpp 0.7.0 (b11669), ggml-org IQ4_NL, MTP off; greedy 45.1. Run by the Kapitsa engine's developers with their own harness.
Qwen3.8-Flash-Next	M5 Max	128 GB	4-bit	MLX	not stated	community43.8	~49	-11%	huggingface.coMTPLX 2.10.0, plain autoregressive (MTP off); 'Optimized Speed' pack: 4-bit g64 with 8-bit sparse-attention projections.
Qwen3.8-Flash-Next	M5 Max	128 GB	oQ4e	MLX	1k	community28.5	~47	-39%	omlx.ai40-core GPU. oMLX v0.6.3, MTP off (-mtp checkpoint), thinking on.
Qwen3.8-Flash-Next	M5 Ultra	256 GB	IQ4_NL	llama.cpp	not stated	community57	~85	-33%	llamaperf.comllama.cpp b11538, no speculation, f16 KV, 262K allocated; one user's r/llamacpp post via llamaperf.
Recursive Flint	M3 Pro	36 GB	Q4_1	llama.cpp	512-token coding answers at T 1.0, -c 32768	community50.87	~53	-4%	github.com18-core GPU, macOS 14. llama.cpp b11804, Recursive's Q4_1 GGUF; mean of two clean passes, each a median of 5 (greedy 51.00); run at a 32K context (out of memory at 140K). Run by the Kapitsa engine's developers with their own harness.
Recursive Flintnot used to scale	M3 Ultra	—	INT4	MLX	19-token prompt, 512 generated, median of 5	community104.5	~142	-26%	x.comMac Studio, RAM not stated. mlx-lm from the then-unmerged PR #1998 branch (merged 24 Oct, not yet released) with a load-time workaround for the uint8-stored weights, so it does not anchor; RecursiveSI/flint-int4. The same thread's 107 tok/s on Ollama's MLX engine had reasoning on and an unstated quant. 4.54 bpw = the 22.6 GB RecursiveSI/flint-int4 checkpoint over 39.8B parameters.
Recursive Flint	M3 Ultra	—	4-bit	MLX	1K tokens per request, batch 1	community90.6	~139	-35%	x.commlx-vlm 0.7.10, 4-bit, no MTP or draft model (confirmed in reply 2113009118990496083); peak memory under 25 GB. RAM not restated on this chart (the BF16 chart in the same thread says 512 GB). The batch-8 aggregate is not plain decode.
Recursive Flint	M3 Ultra	512 GB	BF16	MLX	1K, single request	community51.3	~78	-34%	x.commlx-vlm 0.7.10, BF16, no MTP or draft model; posted by mlx-vlm's author. 32.7 tok/s at 128K is a long-context figure, not this row.
Recursive Flintnot used to scale	M4 Pro	48 GB	INT4	rec	1K prompt, 1,024 generated, 5 runs	sourced131.2	~89	+47%	github.comRecursive's own Metal engine, rec 0.1.0 (a vendor runtime, so it does not anchor), on RecursiveSI/flint-int4 (MLX group-64 INT4, INT8 embeddings); prefill excluded. Read from the throughput chart's description in the rec README; the source of Recursive's '>125 tok/s on an M4 Pro' claim. 4.54 bpw = the 22.6 GB RecursiveSI/flint-int4 checkpoint over 39.8B parameters.
Recursive Flintnot used to scale	M4 Pro	48 GB	4-bit	llama.cpp	1K prompt, 1,024 generated, 5 runs	sourced88	~86	+2%	github.comRecursive's llama.cpp baseline on the same chart; build not stated and the chart was committed before PR #30928 merged, so it does not anchor; GGUF type not stated.
Recursive Flint	M4 Pro	48 GB	Q4_1	llama.cpp	512-token coding answers, median of 5 at T 1.0	community79.57	~80	0%	github.comMacBook Pro, 20-core GPU. llama.cpp b11804 (its first build with Flint), Recursive's Q4_1 GGUF (RecursiveSI/flint-int4-gguf), -b/-ub 2048; greedy 79.93. Light foreign-GPU contention flagged (3.85% mean). Run by the Kapitsa engine's developers with their own harness.
Recursive Flint	M5 Pro	64 GB	4-bit	Ollama	18-token prompt, 1,075 generated	community115	~92	+25%	x.comMac mini. Ollama --verbose eval rate 115.33; the post says a 4-bit build but not which tag. Its 87 tok/s after a 20K-token prompt is a long-context figure, not this row.
Recursive Flint	M5 Pro	48 GB	Q4_1	llama.cpp	512-token coding answers, median of 5 at T 1.0	community92.36	~85	+8%	github.comMacBook Pro, 20-core GPU. llama.cpp b11804, Recursive's Q4_1 GGUF; greedy 92.84; no GPU contention; a single harness run. Run by the Kapitsa engine's developers with their own harness.
Recursive Flint	M5 Pro	48 GB	oQ4e	MLX	1k	community80.7	~89	-10%	omlx.ai20-core GPU. oMLX v0.7.2, MTP/DFlash off; Flint-oQ4e; 22.2 GB peak.
Recursive Flintbinned GPU	M5 Max	36 GB	INT4	MLX	~1K context, greedy, 256 generated	community131	— binned GPU	—	github.comThe 36 GB M5 Max is the binned 32-core-GPU, 460 GB/s part, so this run never anchors or sets the reference. Rapid-MLX 0.16.8 on MLX 0.32.4, RecursiveSI/flint-int4; speculative decoding and MTP off per the release notes; ~24 GB peak. 118.5 tok/s at ~8K. Published by the runtime's developers. 4.54 bpw = the 22.6 GB RecursiveSI/flint-int4 checkpoint over 39.8B parameters.
Recursive Flintnot used to scale	M5 Max	128 GB	oQ6e	MLX	1k	community110.2	— quant not costable	—	omlx.ai40-core GPU. oMLX v0.7.2+omni (an unexplained build), MTP/DFlash off; Flint-oQ6e, a format the index cannot cost, so it does not anchor; 30.8 GB peak. 102.5 tok/s at 4k.
Spark-X2.6-4Bnot used to scale	M5 Pro	—	INT4	MLX	decode at 4K context depth	sourced86.58	— quant not costable	—	huggingface.coSparkLLM's card chart 'Mac M5 Pro · 16-core': MLX INT4 through SparkLLM's own Spark-MLX-LLM loader, so it does not anchor. 72.05 tok/s at 32K.
Spark-X2.6-4B	M5 Pro	—	Q4_K_M	llama.cpp	decode at 4K context depth	sourced76.14	~89	-14%	huggingface.coSparkLLM's card chart 'Mac M5 Pro · 16-core' (the 16-core-GPU M5 Pro has the same 307 GB/s); llama.cpp build not stated. 62.04 tok/s at 32K.
Ternary Bonsai 2 27Bnot used to scale	M4 Pro	64 GB	PQ2_0	llama.cpp	tg128, 3 reps	community20.53	— compute-bound format	—	github.comMac mini. PrismML llama.cpp fork prism-b10709-9a9394a (Metal), llama-bench, PQ2_0 (6.70 GiB), so it does not anchor; Spotlight indexing used 1.5–2 CPU cores throughout, so likely a floor.
Ternary Bonsai 2 27Bnot used to scale	M4 Max	128 GB	PQ2_0	llama.cpp	~2.2K-token prompts, 320 generated, temperature 0, mean of 3	community34.5	— compute-bound format	—	github.comMac Studio, 40-core GPU. PrismML llama.cpp fork prism-b10683-d8f26ee (llama-server), PQ2_0 (7.2 GB), thinking off, so it does not anchor.
Ternary Bonsai 2 27Bnot used to scale	M5	32 GB	Ternary	MLX	1k	community12	— compute-bound format	—	omlx.ai10-core GPU. oMLX v0.7.0 with a TurboQuant 4-bit KV cache; prism-ml Ternary-Bonsai-2-27B-mlx-2bit, so it does not anchor; 11.3 GB peak. 11.0 tok/s at 4k.
Ternary Bonsai 2 27B	M5 Pro	—	PQ2_0	llama.cpp	tg128, depth 0, batch 1	sourced28.1	— compute-bound format	—	huggingface.coVendor model card (current stack): PrismML llama.cpp fork (Metal), llama-bench; 7.21 GB. The whitepaper's Table 6 lists 27.7.
Ternary Bonsai 2 27Bnot used to scale	M5 Pro	48 GB	Ternary	MLX	1k	community23.6	— compute-bound format	—	omlx.ai20-core GPU. oMLX v0.7.1.dev1; prism-ml Ternary-Bonsai-2-27B-mlx-2bit, so it does not anchor; 11.8 GB peak. 21.9 tok/s at 4k. Another session on the same machine (4oet2i02) read 23.5.
Ternary Bonsai 2 27B	M5 Max	—	PQ2_0	llama.cpp	tg128, depth 0, batch 1	sourced46.8	— compute-bound format	—	github.comVendor whitepaper Table 6: PrismML llama.cpp fork (Metal), release build, mean of 3 after warm-up; 7.21 GB. Replaces the model card's 47.0, which was labelled pre-rotation.
Ternary Bonsai 2 27Bnot used to scale	M5 Max	48 GB	Ternary	MLX	4k	community43.4	— compute-bound format	—	omlx.ai40-core GPU. oMLX v0.7.1rc1, MTP/DFlash off; prism-ml Ternary-Bonsai-2-27B-mlx-2bit (ternary weights in MLX's 2-bit container, 2.25 bpw stored); the pack needs its bundled loader and the page does not show it was used, so it does not anchor; 14.3 GB peak. 40.3 tok/s at 8k.
Ternary Bonsai 2 27Bnot used to scale	M6	32 GB	Ternary	MLX	4k	community13.3	— compute-bound format	—	omlx.ai12-core GPU. oMLX v0.7.1rc1, MTP/DFlash off; prism-ml Ternary-Bonsai-2-27B-mlx-2bit, so it does not anchor; 13.9 GB peak. 10.5 tok/s at 16k.
Ternary Bonsai 2 9B	M5 Pro	—	PQ2_0	llama.cpp	tg128, batch 1	sourced76.5	— compute-bound format	—	github.comVendor whitepaper Table 3: MacBook Pro M5 Pro, PrismML llama.cpp fork (Metal), llama-bench, flash attention on, mean of 5; 2.4 GB.
Ternary Bonsai 2 9Bbinned GPU	M6	16 GB	Ternary	MLX	4k	community40.2	— compute-bound format	—	omlx.aiThe 16 GB Mac mini M6 is the binned 153 GB/s part. oMLX v0.7.0rc1, MTP/DFlash off; prism-ml Ternary-Bonsai-2-9B-mlx-2bit; 6.3 GB peak. 31.7 tok/s at 16k.

Apple Silicon LLM Benchmarks

Measured figures, and how far the estimate was off

Methodology

Frequently Asked Questions