Run Nemotron 3.5 Super VL 120B-A12B on M4 Max

Nemotron 3.5 Super VL 120B-A12B runs at 51 tok/s (50.8 as recorded) on a 128 GB M4 Max, a community run reported by omlx.ai (MLX, 4-bit, 1k context). It needs about 72 GB of unified memory. It is NVIDIA's 120B mixture-of-experts model (12B active), released under the OpenMDW licence.

Speed
community51
tok/s
First Token
—
seconds
RAM Needed
72
GB minimum
Engine
MLX
of this figure
Want to run Nemotron 3.5 Super VL 120B-A12B faster — or step up to bigger models? Find your Mac →

The figure

This is a community run: a real run, reported by its source and linked below. The index records it as given and never adjusts it.

MetricValue
Tokens per secondcommunity51 tok/s
Provenancecommunity run · omlx.ai
Quantization4-bit
EngineMLX
Context1k
Figure dated2026-10-18
Minimum RAM72 GB
Parameters120B MoE (12B active)
Chip bandwidth546 GB/s

Every figure for Nemotron 3.5 Super VL 120B-A12B on the M4 Max

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 (72 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.

SpeedQuantEngineMac RAMContextSourceNote
community50.8 tok/s4-bitMLX128 GB1komlx.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.
estimated36 tok/sQ4_K_Mllama.cpp128 GB—LLMCheck estimator—
Provenance key
sourced
Published figure — vendor or press review
estimated
community
Linked individual run — blog, forum or submission

Setup: run Nemotron 3.5 Super VL 120B-A12B on a Mac

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:

ollama run nemotron-3.5-super:120b

MLX — pick a build from Hugging Face’s MLX listings, then run it with its repo id:

pip install -U mlx-lm
mlx_lm.generate --model <repo-id> --prompt "Hello"

Downloads: Ollama page → · model card →

The 51 tok/s figure above came from MLX at 4-bit; other runtimes and quants run at different speeds.

Prefer a GUI? LM Studio downloads GGUF and MLX builds in one click. Step by step: install Ollama on a Mac.

Nemotron 3.5 Super VL 120B-A12B on other Apple Silicon chips

ChipSpeedQuantEngineBandwidth
M5 Ultracommunity74 tok/s4-bitMLX1228 GB/s
M3 Ultraestimated59 tok/sQ4_K_Mllama.cpp819 GB/s
M5 Maxcommunity36 tok/sQ4_0llama.cpp614 GB/s

About Nemotron 3.5 Super VL 120B-A12B

NVIDIA's OpenMDW 120B Mamba-Transformer MoE with 12B active (15 Oct 2026): text, image and video in, 1M context; SWE-bench Verified 71.1 on NVIDIA's own NeMo Gym harness. Q4_K_M is ~70 GB (Ollama's nemotron-3.5-super tag is 80–90 GB), so it needs a 96–128 GB Mac; it runs in llama.cpp b11669+, Ollama and mlx-vlm 0.7.9+. Community plain-decode runs on an M5 Max measured 30.6 tok/s (mlx-vlm, NVFP4), 35.9 (llama.cpp Q4_0) and 51.8 (oMLX 4-bit), and 74.3 on a 96 GB M5 Ultra (oMLX 4-bit). Avoid NVFP4 GGUFs in llama.cpp on a Mac: Metal runs those tensors on the CPU.

OpenMDW licence · 120B MoE · 1000K context · LLMCheck capability 42/50 · see its leaderboard rank →

System requirements

Macs with the M4 Max

🛒 Get a Mac that runs Nemotron 3.5 Super VL 120B-A12B

Nemotron 3.5 Super VL 120B-A12B needs about 72 GB of unified memory. These current Apple Silicon Macs have the headroom to run it comfortably:

As an Amazon Associate, LLMCheck earns from qualifying purchases. These affiliate links cost you nothing extra and help keep the LLMCheck index free.

Compare More Models

See how Nemotron 3.5 Super VL 120B-A12B stacks up against other models on your specific Mac hardware.

Open Compare Tool Full Leaderboard