gpt-oss-20b
gpt-oss-20b
Version: 11
OpenAILast updated December 2025
Push the open model frontier with GPT-OSS models, released under the permissive Apache 2.0 license, allowing anyone to use, modify, and deploy them freely.
Reasoning
Multilingual
Coding

Key capabilities

About this model

OpenAI's open-weight models designed for powerful reasoning, agentic tasks, and versatile developer use cases.

Key model capabilities

  • Permissive Apache 2.0 license: Build freely without copyleft restrictions or patent risk—ideal for experimentation, customization, and commercial deployment.
  • Configurable reasoning effort: Easily adjust the reasoning effort (low, medium, high) based on your specific use case and latency needs.
  • Full chain-of-thought: Gain complete access to the model's reasoning process, facilitating easier debugging and increased trust in outputs. It's not intended to be shown to end users.
  • Fine-tunable: Fully customize models to your specific use case through parameter fine-tuning.
  • Agentic capabilities: Use the models' native capabilities for function calling, web browsing , Python code execution , and Structured Outputs.
  • Native MXFP4 quantization: The models are trained with native MXFP4 precision for the MoE layer, making gpt-oss-120b run on a single H100 GPU and the gpt-oss-20b model run within 16GB of memory.

Use cases

See Responsible AI for additional considerations for responsible use.

Key use cases

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Out of scope use cases

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Pricing

Pricing is based on a number of factors, including deployment type and tokens used. See pricing details here.

Technical specs

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Training cut-off date

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Training time

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Input formats

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Output formats

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Supported languages

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Sample JSON response

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Model architecture

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Long context

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Optimizing model performance

Configurable reasoning effort: Easily adjust the reasoning effort (low, medium, high) based on your specific use case and latency needs.

Additional assets

Please see OpenAI's gpt-oss-120b model card here.

Training disclosure

Training, testing and validation

The provider has not supplied this information.

Distribution

Distribution channels

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More information

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Responsible AI considerations

Safety techniques

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Safety evaluations

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Known limitations

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Acceptable use

Acceptable use policy

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Quality and performance evaluations

Source: OpenAI The provider has not supplied this information.

Benchmarking methodology

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Public data summary

Source: OpenAI The provider has not supplied this information.
Model Specifications
Context Length131072
LicenseCustom
Last UpdatedDecember 2025
Input TypeText
Output TypeText
ProviderOpenAI
Languages1 Language