OpenAI
gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. It activates 5.1B parameters per forward pass and is optimized...
Running this yourself: likely needs a high-memory cloud gpu.
This model is still tracked for research and discovery, but it is excluded from default public rankings until it returns to active status.
32.2
Quality Score
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Arena ELO
117B
Parameters
131K
Context
This measures the amount of verifiable public evidence we have, not how capable the model is. A missing field means it has not been verified yet, not that its value is zero.
19 of 22 public signals
Use this section to answer one simple question first: how much outside evidence do we have that this model performs well? Structured benchmark scores appear first, then official provider evidence, then live arena signal.
This model has normalized benchmark rows, so scores here are directly comparable across benchmark sources.
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5.1M
Downloads
5.1K
Likes
Aug 2025
Released
5/5 signals
3/4 signals
4/5 signals
3/4 signals
4/4 signals
Parameters
117B
Training compute
4.9e24 FLOP
Dataset scale
Not reported
Base model
Not reported
Source-reported access: Open weights (unrestricted) · Confident confidence
Gaps we are still tracking
These are recent benchmark or leaderboard claims from official provider sources. They are useful for freshness and context, but they are not treated the same as normalized independent benchmark rows.
gpt-oss-120b - SWE-Bench Verified
SWE-Bench Verified resolved rate 26.0
View sourceIntroducing GPT-5.2
Introducing GPT-5.2 | OpenAI Skip to main content Research Products Business Developers Company Foundation (opens in a new window) Log in Try ChatGPT (opens in a new window) Research Products Business Developers Company Foundation (opens in a new window) Try ChatGPT (opens in a new window) Login OpenAI December 11, 2025 Product Release Introducing GPT‑5.2 The most advanced frontier model for professional work and long-running agents. Loading… Share Model performance Model per
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