Local AI Advisor

Can Mac Studio M2 Ultra 192 GB run gpt-oss-120b?

192 GB unified · 800 GB/s memory bandwidth · gpt-oss-120b has 116.8B parameters (5.1B active per token).

Short answer

Yes, excellent for chat and excellent or better for every workload we test.

Best quantization for chat: MXFP4 (59 GB of weights) on LM Studio. Generation: 85–120 tok/s, leaving about 122 GB free for your other apps.

How it rates for each workload

Same model and machine, different jobs. Agents and long documents send far bigger prompts than chat, so they need much more speed and memory.

WorkloadVerdictQuantGenerationFirst replyContext
Chatwith Open WebUIExcellentMXFP485–120 tok/sunder 1 s8KDetails
Coding questionswith ContinueExcellentMXFP485–110 tok/s≈3 s16KDetails
Coding in a repositorywith AiderExcellentMXFP475–100 tok/s≈9 s32KDetails
Agentic codingwith OpenCodeExcellentMXFP470–95 tok/s≈15 s32KDetails
Long documents (64K)with Open WebUIExcellentMXFP455–70 tok/s≈40 s64KDetails

Speeds are estimates calibrated against measured benchmarks on similar hardware. “First reply” is the time to read the workload’s opening prompt. How we calculate

Get it running

Copy-paste commands for the MXFP4 build with a 64K context. Ollama and llama.cpp download the file straight from Hugging Face.

ollama run hf.co/unsloth/gpt-oss-120b-GGUF:F16

Downloads 65.37 GB (F16). Ollama's default context is small: set OLLAMA_CONTEXT_LENGTH=65536 before `ollama serve` for long prompts.

Different tool, context size or workload?

These pages use typical settings. The full check models your exact setup.