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| Detail | Value |
|---|---|
| Architecture | Hybrid Mamba-2 + Transformer Attention + Latent MoE |
| Total Parameters | 120B |
| Active Parameters | 12B per token |
| Context Length | 1M tokens (262,144 default) |
| Experts | 512 routed, 22 active per token, 1 shared |
| Quantization | 6-bit affine (6.507 BPW), group size 64 |
| Disk Size | ~92 GB |
| Peak Memory | ~98.4 GB |
mlx-lm >= 0.31.2 (install from git main for Latent MoE support)pip install git+https://github.com/ml-explore/mlx-lm.git1mlx_lm.generate \
2 --model FF-01/Nemotron-3-Super-120B-A12B-MLX-6bit \
3 --prompt "Hello!" \
4 --max-tokens 2561from mlx_lm import load, generate
2
3model, tokenizer = load("FF-01/Nemotron-3-Super-120B-A12B-MLX-6bit")
4response = generate(model, tokenizer, prompt="Hello!", max_tokens=256)
5print(response)FF-01/Nemotron-3-Super-120B-A12B-MLX-6bit in the model browser and download directly.| Metric | Value |
|---|---|
| Generation Speed | ~43.6 tok/s |
| Peak Memory | 98.4 GB |
<think> and </think> tags to delineate reasoning.