NVIDIA Nemotron-3-super-120B-A12B on Apple M2 (16GB Unified)
M2 (16GB Unified) cannot run NVIDIA Nemotron-3-super-120B-A12B. 16 GB VRAM is insufficient at any quantization level.
Model Size
120B
Device VRAM
16 GB
Bandwidth
100 GB/s
Quantization
Q2_K
Performance by Quantization
OwnRig currently has one published compatibility entry for NVIDIA Nemotron-3-super-120B-A12B on Apple M2 (16GB Unified) at Q2_K. This pairing has limitations — check the rating and notes below.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q2_K | – | – | ✗ Offload | Not viable | estimated |
Notes
Q2_K
Model exceeds m2-16gb effective VRAM capacity.
About NVIDIA Nemotron-3-super-120B-A12B
NVIDIA Nemotron-3-super-120B-A12B (120B) is a chat, coding, reasoning, multi-purpose model. MoE architecture with 120B total parameters and roughly 12B active per token. Requires VRAM for the full expert pool but decodes more like a smaller model once loaded. Native 131K context with 1M-token extension support.
View all NVIDIA Nemotron-3-super-120B-A12B hardware options →About Apple M2 (16GB Unified)
Apple M2 (16GB Unified) has 16 GB at 100 GB/s. Available in MacBook Air 13" (2022), MacBook Air 15" (2023), MacBook Pro 13" (2022).
See all models Apple M2 (16GB Unified) can run →Estimate method: Estimated: model exceeds m2-16gb VRAM capacity. Reference hardware source: github.com (2026-04-18)
Performance varies by driver version, inference engine, quantization method, context length, and system configuration. Figures shown are estimates based on community benchmarks and may not reflect your exact setup. Product names are trademarks of their respective owners. OwnRig is independent and not affiliated with any hardware or AI model provider.