NICKCKCKCKCKCKCKCKCK/gpt-oss-20b

TEXT GENERATIONPricing:Input $0.3 / Output $1.2Concurrent Unit Cost:1Model Size:20BQuant:FP8Context Size:32kPublished:Oct 6, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

The gpt-oss-20b is a 21 billion parameter open-weight model from OpenAI, designed for powerful reasoning, agentic tasks, and versatile developer use cases. It features configurable reasoning effort, full chain-of-thought access, and agentic capabilities including function calling, web browsing, Python code execution, and structured outputs. Optimized with MXFP4 quantization, it can run within 16GB of memory, making it suitable for lower latency, local, or specialized applications.

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Overview

The gpt-oss-20b is a 21 billion parameter open-weight model from OpenAI, part of the gpt-oss series designed for robust reasoning and agentic tasks. It is released under a permissive Apache 2.0 license, allowing for broad experimentation, customization, and commercial deployment. This model is specifically optimized for lower latency and specialized use cases, capable of running within 16GB of memory thanks to MXFP4 quantization of its Mixture-of-Experts (MoE) weights.

Key Capabilities

  • Configurable Reasoning Effort: Users can adjust the model's reasoning depth (low, medium, high) to balance speed and analytical detail for different tasks.
  • Full Chain-of-Thought Access: Provides complete visibility into the model's reasoning process, aiding in debugging and increasing trust in outputs.
  • Agentic Functionality: Natively supports function calling, web browsing, Python code execution, and structured outputs, making it suitable for complex agentic workflows.
  • Fine-tunability: The model is designed for fine-tuning, enabling customization for specific use cases, even on consumer hardware.
  • Harmony Response Format: Trained on OpenAI's harmony response format, which is essential for correct operation.

Good For

  • Local and Specialized Applications: Its efficient memory footprint (16GB) makes it ideal for deployment on consumer hardware or for applications requiring low latency.
  • Developer Use Cases: Excellent for tasks requiring deep reasoning, agentic capabilities, and structured outputs.
  • Commercial and Experimental Projects: The Apache 2.0 license provides flexibility for various development and deployment scenarios.
  • Debugging and Trust: Full chain-of-thought access is beneficial for understanding and validating model decisions.

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