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gpt-oss-20b

gpt-oss-20b is a verified current AI model with official specifications, pricing or access details, capabilities, practical use cases, strengths and limitations.

Open-Weight Reasoning ModelText Free
In plain English

What is this model and why does it matter?

gpt-oss-20b is OpenAI's 21B-total, 3.6B-active Mixture-of-Experts reasoning model for low-latency, local and specialized deployments with full chain-of-thought access and agentic capabilities.

Local AIPrivate reasoningFine-tuningAgentic workflowsLow-latency open-weight deployments
Model overview

gpt-oss-20b: features, use cases and important details

gpt-oss-20b is a current AI model verified from first-party OpenAI sources.

gpt-oss-20b verified specifications

gpt-oss-20b is OpenAI’s 21B-total, 3.6B-active Mixture-of-Experts reasoning model for low-latency, local and specialized deployments with full chain-of-thought access and agentic capabilities. Its verified context or usage limit is 131072 tokens, with 131072 tokens maximum output.

gpt-oss-20b pricing and access

OpenAI releases gpt-oss-20b as Apache-2.0 open weights rather than a metered OpenAI API model. There is no OpenAI per-token fee; users pay for their own local or cloud inference infrastructure.

gpt-oss-20b best uses

Local AI, Private reasoning, Fine-tuning, Agentic workflows, Low-latency open-weight deployments.

gpt-oss-20b limitations

No hosted OpenAI API endpoint, June 2024 knowledge cutoff, Local quality and speed depend on the inference stack.

Get started

How to use this model

  1. Download the official gpt-oss-20b weights.
  2. Review the Apache 2.0 license and usage policy.
  3. Run a compatible inference stack.
  4. Choose low, medium or high reasoning effort.
  5. Add tools or structured outputs where needed.
  6. Benchmark latency and memory on your hardware.
Copy and try

Example prompts

  • Analyze this codebase locally and propose a fix.
  • Use Python and tools to solve this structured reasoning task.
  • Fine-tune this open model for a private domain assistant.
Capabilities

What it can do

  • 21B total / 3.6B active
  • 131K context
  • Apache 2.0
  • Reasoning controls
  • Function calling
  • Structured outputs
  • Fine-tuning
Best for

Practical use cases

  • Private assistants
  • Coding
  • Research
  • Local agents
  • Fine-tuned enterprise models
Pricing

What does it cost?

OpenAI releases gpt-oss-20b as Apache-2.0 open weights rather than a metered OpenAI API model. There is no OpenAI per-token fee; users pay for their own local or cloud inference infrastructure.

InputSelf-hosted infrastructure cost
OutputSelf-hosted infrastructure cost
Simple summaryNo OpenAI API token charge; cost depends on the hardware or inference provider used to serve the weights.

What stands out

  • Apache 2.0
  • Open weights
  • Lower hardware footprint than gpt-oss-120b
  • Full reasoning visibility

Things to consider

  • Text only
  • Requires serving infrastructure
  • Older knowledge cutoff
Limitations

Important restrictions and trade-offs

  • No hosted OpenAI API endpoint
  • June 2024 knowledge cutoff
  • Local quality and speed depend on the inference stack
SimplifyAITools verdict

Our editorial take

A major high-demand open-weight OpenAI model for developers who want local reasoning without the 120B model’s hardware requirements.

References

Primary sources

  1. Open source 1 ↗
  2. Open source 2 ↗
  3. Open source 3 ↗
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