The LLMCheck index estimates Nemotron 3.5 Bolt E4B at ~39 tok/s on an M4 at Q4_K_M, a figure from its published bandwidth model, not a measured run. It needs about 6 GB of unified memory. It is NVIDIA's 4B dense model, released under the OpenMDW licence.
Want to run Nemotron 3.5 Bolt E4B faster — or step up to bigger models? Find your Mac →This is an LLMCheck index estimate from its published two-term bandwidth model, not a measured run; the index labels it so everywhere it appears. Own this Mac? Submit a real run →
| Metric | Value |
|---|---|
| Tokens per second | estimated~39 tok/s |
| Provenance | estimate · how estimates are made |
| Quantization | Q4_K_M |
| Minimum RAM | 6 GB |
| Parameters | 4B |
| Chip bandwidth | 120 GB/s |
Each row as the index holds it, with its source. “Mac RAM” is the memory of the Mac a run used, not the model’s requirement (6 GB). The headline figure follows the reference rule: the lower-median measured plain-decode run at 5 bits or fewer (a run whose quant was not stated counts only when no stated-quant run qualifies), else the estimate; a run marked “not used to anchor estimates” is listed here but never becomes the headline.
| Speed | Quant | Engine | Mac RAM | Context | Source | Note |
|---|---|---|---|---|---|---|
| community26.6 tok/s | OptiQ mixed 4/8-bit | MLX | 24 GB | code prompt, batch 1, greedy, thinking off, best of 3 | huggingface.co | mlx-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. |
| community26.6 tok/s | Q4_K_M | llama.cpp | 16 GB | short Japanese prompt, ~400 characters generated, -c 8192 | note.com | Mac 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.; not used to anchor estimates |
Ollama — install it (brew install ollama or the app from ollama.com), then pull the model by its tag, checked on ollama.com on 2026-10-24:
MLX — pick a build from Hugging Face’s MLX listings, then run it with its repo id:
Downloads: Ollama page → · model card →
Prefer a GUI? LM Studio downloads GGUF and MLX builds in one click. Step by step: install Ollama on a Mac.
NVIDIA's OpenMDW-licensed edge model (23 Oct 2026), RL post-trained from Gemma 4 E4B for multi-turn tool use and instruction following: 8B weights, 4B effective, 64K context per NVIDIA. '4GB' is NVIDIA's VRAM target; the official Q4_K_M file is 6.18 GB, and 3–4-bit builds of ~4.2 GB fit an 8 GB Mac. Ollama runs it on Apple Silicon as nemotron-3.5-bolt:e4b (the untagged name is the 74B model). A community MLX run measured 55 tok/s at 6-bit on a 36 GB M3 Max (the 4-bit build reached 73, but its quantizer reports only 71.7% top-1 agreement with BF16), and a community oMLX run measured 46 at 8-bit on an M5 Pro.
OpenMDW licence · 4B · 64K context · LLMCheck capability 17/50 · see its leaderboard rank →
Nemotron 3.5 Bolt E4B needs about 6 GB of unified memory. These current Apple Silicon Macs have the headroom to run it comfortably:
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