can it run
Yes, but close to the edge. 96GB against a 82GB working set: it runs, with little room for long context windows or other processes.
weights 65GB + KV cache 0.28GB at 4k context vs ~96GB usable → full. 65.3 GB needed of 96 GB usable — headroom for context
computed roofline: 1792 GB/s × 0.46–0.76 efficiency window / 9.8GB (Q4_K_M) — bands, never points.
MoE: file is 65GB (that decides fit) but only ~18B of experts activate per token (~9.8GB streamed) — band below is the active-expert estimate, optimistic; community MoE rows run several× the naive bandwidth math
| model file | 65GB (GGUF Q4_K_M) |
| minimum memory | 82GB working set |
| this machine | 96GB GDDR7 |
| params | 120B MoE |
| license | apache-2.0 |
| price | $16499 |
easy run: ollama pull gpt-oss:120b
runs with: ollama · llama.cpp · koboldcpp · lm studio
→ NIMO AI Mini PC (128GB) — cheapest machine that runs it ($1999)
→ ASUS ExpertCenter Pro ET900N G3 (GB300) — this model on the biggest machine
→ every model the RTX PRO 6000 Blackwell (96GB) can run — full list
→ tinybox green v2 blackwell (4× RTX PRO 6000) — upgrade path machine