Model record

gpt-oss-120b

OpenAI · Apache 2.0 · verified

Architecture Mixture of experts
Parameters 117B total / 5.1B active
Context 131,072 tokens
Deployment tier Workstation
Starting memory 66 GB
Recommended 80 GB

What this model is

OpenAI reports 117B total parameters and 5.1B active parameters per token.

The architecture is mixture of experts. Memory must hold the full weight set, while active parameters affect the speed heuristic. Experts can be offloaded to system memory, but that trades speed for capacity.

Memory and quantization

Decimal GB. The MXFP4 GGUF file is 63.39 GB; the checked GGUF repository does not publish a separate Q8 build.

Quantization Published files 8K estimate
MXFP4 63.39 GB 65.19 GB

Estimate formula: published weight files + 0.3067 GB per 8K tokens × context / 8K + 1.5 GB runtime overhead. Sizes are decimal GB, not GiB. At 8K context, the smallest listed build is about 65.2 GB before OS and application reserve.

Conservative FP16 estimate from the public config. Alternating full-attention layers use 8 KV heads; local layers are capped by a 128-token sliding window.

KV method source: https://huggingface.co/openai/gpt-oss-120b/raw/main/config.json

Speed heuristic

Not benchmarked here. The calculator uses 5.1B active parameters only as a relative speed heuristic.

Active path: 5.1B parameters. This is a relative speed signal only; it is not a tokens/sec benchmark.

If the full weights do not fit in accelerator memory but do fit in system memory, the calculator marks the result as a tight CPU-offload fit. Expect substantially slower generation and verify the runtime's MoE offload support.

Runtimes

  • Ollama
  • llama.cpp
  • vLLM
ollama run gpt-oss:120b

License restrictions

Apache 2.0 permits commercial use and modification; retain notices and comply with the patent and termination terms.

This is a plain-language summary, not legal advice. Read the linked license before commercial deployment or redistribution.

Known issues

  • OpenAI positions this model for a single 80 GB accelerator; 64 GB systems are below the MXFP4 weight requirement before KV cache.
  • The Harmony response format is required.

Sources

This page is an independent compatibility guide, not official documentation. Verify the primary source before downloading or deploying a model.

Check a specific machine