Nemotron 3.5 Super VL 120B-A12B runs at 74 tok/s (74.3 as recorded) on a 96 GB M5 Ultra, 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.
Want to run Nemotron 3.5 Super VL 120B-A12B faster — or step up to bigger models? Find your Mac →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.
| Metric | Value |
|---|---|
| Tokens per second | community74 tok/s |
| Provenance | community run · omlx.ai |
| Quantization | 4-bit |
| Engine | MLX |
| Context | 1k |
| Figure dated | 2026-10-19 |
| Minimum RAM | 72 GB |
| Parameters | 120B MoE (12B active) |
| Chip bandwidth | 1228 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 (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.
| Speed | Quant | Engine | Mac RAM | Context | Source | Note |
|---|---|---|---|---|---|---|
| community74.3 tok/s | 4-bit | MLX | 96 GB | 1k | omlx.ai | 64-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. |
| estimated74 tok/s | Q4_K_M | llama.cpp | 256 GB | — | LLMCheck estimator | — |
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 →
The 74 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.
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 →
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:
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