OpenAI open-weight reasoning model (MoE, 117B/5.1B active) under Apache 2.0; fits on a single 80GB GPU. Configurable reasoning effort.
Context window
128K
tokens
Parameters
117B (5,1B aktywnych)
parameters
Max output
131,072
tokens
Release date
5 August 2025
Access:APIDownloadHostedDeployment:💻 Local☁ Cloud
Overview
Access & deployment
APIDownloadHosted
LocalCloud
Weights: Open weights
Key parameters
📏 Context: 128K
🧩 Parameters: 117B (5,1B aktywnych)
✓ Tools · ✓ Fine-tuning
📥 Input: text
Technical specification
Context window
128K
tokens
Parameters
117B (5,1B aktywnych)
parameters
Max output tokens
131,072
tokens per response
Knowledge cutoff
1 Jun 2024
Knowledge boundary
License
Apache 2.0
Hardware requirements
Fits on a single 80GB GPU (e.g. NVIDIA H100 or AMD MI300X) thanks to MXFP4 quantization of the MoE weights.
Features:✓ Tool use✓ Fine-tuning
Modalities
⬇ Input
text
⬆ Output
textcode
Capabilities and applications
Native model capabilities
Advanced reasoning
The ability to perform multi-step, structured reasoning: analysing problems, planning steps, and drawing conclusions from hypotheses. Reasoning-first models (e.g. GPT-5.1 Thinking) dedicate a portion of inference to chains of thought before responding.
Category: reasoning
Mathematical reasoning
The model's ability to solve mathematical tasks requiring multi-step reasoning — equations, proofs, combinatorics, geometry, calculus and competition-level problems.
Category: reasoning
Coding
Generating, analysing and modifying code in many programming languages. Covers writing functions, debugging, refactoring, code review, and creating tests. Measured by benchmarks such as HumanEval and SWE-bench.
Category: coding
Agentic capability
The model's ability to autonomously plan and execute multi-step tasks by sequentially using tools, maintaining context, and adapting to intermediate results.
Category: planning
Tool use
The model's ability to call external functions, APIs and tools during a conversation: calculator, search engine, code editor, database. The model decides when and how to use a tool and interprets its result.
Category: planning
Structured output
Producing data in structured formats such as JSON.
Category: structured_generation
Long context
Support for large context windows — tens to hundreds of thousands (or millions) of input tokens. Enables analysis of entire codebases, long documents, and many parallel conversations without losing earlier information. GPT-5.1 supports 400,000 tokens.
Category: language
Adaptive reasoning effort
The model decides how much 'thinking' to allocate to a given query: simple questions are answered quickly, complex problems receive more inference cycles. A GPT-5.1 feature (both Instant and Thinking) that shortens time on easy tasks and extends it for hard ones.
Category: reasoning
Application domains
Benchmark results
7 benchmarks
AIME 2024
accuracy · high reasoning, with tools
96.6%
📄 OpenAI gpt-oss model card (arXiv:2508.10925)
AIME 2025
accuracy · high reasoning, with tools
97.9%
📄 OpenAI gpt-oss model card (arXiv:2508.10925)
GPQA
accuracy · GPQA Diamond, high reasoning
80.9%
📄 OpenAI gpt-oss model card (arXiv:2508.10925)
MMLU
accuracy
90.0%
📄 OpenAI gpt-oss model card (arXiv:2508.10925)
Codeforces
Elo · with tools
2622 Elo
📄 OpenAI gpt-oss model card (arXiv:2508.10925)
HealthBench
score
57.6%
📄 OpenAI gpt-oss model card (arXiv:2508.10925)
Artificial Analysis Intelligence Index
index · high reasoning mode
24
📄 Artificial Analysis
Technical architecture
Core Architecture
Model Form
Deployment and security
☁ Available on platforms
🔒 Security / Enterprise
✓ Verified enterprise information
Updated: 23 Jul 2026↗ Security documentation
