OpenAI · AI model
gpt-oss-120b
OpenAI's larger open-weight reasoning model (117B total, 5.1B active parameters) under the Apache 2.0 license; fits on a single H100 GPU. Text input and output, 131,072-token context window.
Last verified Available 7 sources
Key specs
- Provider
- OpenAI
- Family
- gpt-oss
- API identifier
- gpt-oss-120b
- Availability
- Available
- Release date
- 2025-08-05
- License
- Open source (Apache 2.0)
- Context window
- 131,072 tokens
- Max output
- 131,072 tokens
- Knowledge cutoff
- June 2024
- API access
- Unknown
- Consumer app
- Unknown
Capabilities
Inputs
- Text input Yes
- Image input No Model page marks image as not supported; text is the only modality
- Audio input No Model page marks audio as not supported
- Video input No Model page marks video as not supported
- File input Unknown
Outputs
- Text output Yes
- Image output No Model page marks image as not supported; text is the only modality
- Audio output No Model page marks audio as not supported
Features
- Reasoning Native Configurable reasoning effort (low, medium, high) with full chain-of-thought access; no option to disable reasoning is documented
- Tool calling Yes Function calling listed as a supported feature and Responses API tool; key features name native function calling, web browsing, Python code execution and structured outputs
- Web search Yes Model page lists web_search among the tools supported with the Responses API (with function_calling, code_interpreter and mcp); key features also name native web browsing
"Unknown" means we have not verified this capability yet; it does not mean the model lacks it.
Pricing
No current prices listed.
Benchmarks
| Benchmark | Setting | Score | Reported by | Measured | Verified | Source |
|---|---|---|---|---|---|---|
| AutomationBench % tasks completed correctly, higher is better | v1.0.6; high effort | 0.15 % | Third party | — | 2026-10-25 | AutomationBench AI benchmark leaderboard (Zapier) |
| GDPval-AA v2.1 Elo, higher is better | high effort | 608 Elo | Third party | 2026-10-25 | 2026-10-25 | GDPval-AA v2.1 Leaderboard (Artificial Analysis) |
| low effort | 171 Elo | Third party | 2026-10-25 | 2026-10-25 | GDPval-AA v2.1 Leaderboard (Artificial Analysis) | |
| Humanity's Last Exam accuracy %, higher is better | no tools; high effort | 14.9 % | Self-reported | — | 2026-10-25 | gpt-oss-120b & gpt-oss-20b Model Card (OpenAI, arXiv 2508.10925) |
| no tools; low effort | 5.2 % | Self-reported | — | 2026-10-25 | gpt-oss-120b & gpt-oss-20b Model Card (OpenAI, arXiv 2508.10925) | |
| no tools; medium effort | 8.6 % | Self-reported | — | 2026-10-25 | gpt-oss-120b & gpt-oss-20b Model Card (OpenAI, arXiv 2508.10925) | |
| text-only subset; Scale Labs harness, o3-mini judge | 15.48 % | Third party | — | 2026-10-25 | Humanity's Last Exam (Text Only) leaderboard (Scale Labs) | |
| with tools; high effort | 19 % | Self-reported | — | 2026-10-25 | gpt-oss-120b & gpt-oss-20b Model Card (OpenAI, arXiv 2508.10925) | |
| with tools; low effort | 9.1 % | Self-reported | — | 2026-10-25 | gpt-oss-120b & gpt-oss-20b Model Card (OpenAI, arXiv 2508.10925) | |
| with tools; medium effort | 11.3 % | Self-reported | — | 2026-10-25 | gpt-oss-120b & gpt-oss-20b Model Card (OpenAI, arXiv 2508.10925) | |
| Text Arena Arena score, higher is better | Overall, style control on | 1,352 | Third party | 2026-10-23 | 2026-10-25 | Text Arena leaderboard (Arena) |
Leaderboard versions (for example 1.0.5 and 1.0.6) are not comparable. Some results use fallback routing for refused steps: for "Claude Fable 5.1 (with Opus 5 Fallback)", Opus 5 handled 260 of 657 tasks. Artificial Analysis runs a separate leaderboard, AutomationBench-AA, which uses a guardrail-adjusted metric; its scores are not comparable with Zapier's. The partial_credit metric is for diagnostics only. The leaderboard shows no per-row evaluation dates.
Elo is a relative rating: values change as models are added and the scale is re-anchored, so always store the date a rating was read. For example, Anthropic's launch page gives 1846 for Claude Opus 5.5, while the leaderboard on 2026-10-12 shows 1866 (Max, Default Fallback). Earlier versions (Google cites "GDPVal-AA v2") are not comparable. Judging is done by an LLM, not by human experts. Anthropic models are listed with "Default Fallback", meaning refused steps are routed to a fallback model. AA-Briefcase and GDP.pdf are separate evaluations.
Results differ a lot by setting: with tools versus without tools (Anthropic reports 45.9% without tools and 57.4% with tools for Claude Haiku 5.5), and the full set versus the text-only subset. Providers use different judge models and harnesses (Scale uses o3-mini; Alibaba states GPT-4o). Derived sets such as HLE-Verified (a third-party revision with 1,811 scored items), HLE-Rolling and HLE-Diamond are different item sets and are not comparable. The questions are public, so contamination is possible, and community reviews have reported flawed items.
Scores measure voter preference, which can be influenced by answer style and length. The leaderboard offers a style-control adjustment, so record which view was used. Scores shift with every update, so a value is only meaningful together with its leaderboard date. Entries marked "Preliminary" or with few votes have wide confidence intervals. The same model can appear several times with different reasoning-effort suffixes (for example -high or -max). Category views (Coding, Math, Creative Writing and others) are different rankings from Overall.
One row per result, without rank numbers: each result was measured under its own setting (effort level, harness, tools, test version), as stated by the source, and scores compare only within the same setting. Self-reported results come from the provider and have not been reproduced independently.
Rankings
- #13 of 14 in Best AI for research as of 2026-10-26
- #38 of 42 in Best AI API as of 2026-10-26
- #39 of 39 in Best AI for business as of 2026-10-26
Derived from our published ranking snapshots; each ranking explains its criteria and weights.
Compare gpt-oss-120b
Guides
About gpt-oss-120b
gpt-oss-120b is the larger of OpenAI's two open-weight gpt-oss language models, with 117B total parameters and 5.1B active parameters, and fits on a single H100 GPU. It is released under the Apache 2.0 license with weights available on Hugging Face. It supports configurable reasoning effort (low, medium, high), full chain-of-thought access, function calling and structured outputs, and OpenAI describes it as fine-tunable.
Strengths and weaknesses
Strengths
- Open weights under the Apache 2.0 license; can be self-hosted and fine-tuned
- Configurable reasoning effort (low, medium, high) with full chain-of-thought access
- Native function calling, web browsing, Python code execution and structured outputs
- Runs on a single 80 GB GPU (H100)
Weaknesses
- Text-only input and output (no image input)
- 131,072-token context window and June 2024 knowledge cutoff, smaller and earlier than the GPT-6 models
- No OpenAI API price is listed on the pricing page, and the model page shows rate limits of 0 for all API usage tiers
Sources
- gpt-oss-120b Model | OpenAI API
- Introducing gpt-oss | OpenAI
- gpt-oss-120b & gpt-oss-20b Model Card (OpenAI, arXiv 2508.10925)
- Humanity's Last Exam (Text Only) leaderboard (Scale Labs)
- GDPval-AA v2.1 Leaderboard (Artificial Analysis)
- AutomationBench AI benchmark leaderboard (Zapier)
- Text Arena leaderboard (Arena)
Last verified Page updated 2026-10-26