--- title: gpt-oss-20b — Open Reasoning LLM | ModelsLab description: Run gpt-oss-20b model via API for agentic reasoning and tool use on 16GB GPUs. Generate structured outputs with low latency now. url: https://modelslab.com/gpt-oss-20b canonical: https://modelslab.com/gpt-oss-20b type: website component: Seo/ModelPage generated_at: 2026-04-24T23:30:59.575855Z --- Available now on ModelsLab · Language Model Gpt-oss-20b gpt-oss-20b Open Reasoning --- [Try Gpt-oss-20b](/models/openai/gpt-oss-20b) [API Documentation](https://docs.modelslab.com) ![Gpt-oss-20b](https://assets.modelslab.ai/generations/8b2f0440-52cc-4f41-93eb-d31006ad71e2.webp) Deploy gpt oss 20b model --- MoE Efficiency ### 21B Total 3.6B Active Activates 3.6B parameters per token from 21B total via top-4 routing from 32 experts. Agentic Workflows ### Native Tool Calling Supports function calling and external tools for multi-step reasoning tasks. Configurable Depth ### Low Mid High Reasoning Adjust reasoning effort in prompts for speed-accuracy tradeoffs. Examples See what Gpt-oss-20b can create --- Copy any prompt below and try it yourself in the [playground](/models/openai/gpt-oss-20b). Code Analysis “Analyze this Python function for bugs and suggest optimizations: def fibonacci(n): if n <= 1: return n else: return fibonacci(n-1) + fibonacci(n-2). Reasoning: high.” Scientific Summary “Summarize quantum entanglement basics and implications for computing. Use structured output with key facts, equations, and applications. Reasoning: medium.” Tool Chain “Plan steps to fetch weather data via API, analyze trends, and plot results. Call tools as needed. Reasoning: high.” Math Proof “Prove Pythagorean theorem using similar triangles. Output chain-of-thought steps and diagram description. Reasoning: high.” For Developers A few lines of code. gpt-oss-20b. One API call. --- ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed. - **Serverless:** scales to zero, scales to millions - **Pay per token,** no minimums - **Python and JavaScript SDKs,** plus REST API [API Documentation ](https://docs.modelslab.com) PythonJavaScriptcURL Copy ```

import requests

response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
  "key": "YOUR_API_KEY",
  "prompt": "",
  "model_id": ""
}
)
print(response.json())

``` FAQ Common questions about Gpt-oss-20b --- [Read the docs ](https://docs.modelslab.com) ### What is gpt-oss-20b LLM? gpt-oss-20b is OpenAI's 21B parameter MoE model with 3.6B active per token. Runs on 16GB VRAM for low-latency reasoning. Matches o3-mini benchmarks. ### How does gpt oss 20b model work? Uses Mixture-of-Experts with 32 experts and top-4 routing. Supports 128K context window. Optimized for agentic tasks and structured outputs. ### What is gpt-oss-20b API for? Ideal for local inference, edge devices, and specialized use cases. Includes native tool use and configurable reasoning levels. ### Is gpt-oss-20b alternative to closed models? Yes, open-weight under Apache 2.0. Outperforms similar open models on reasoning while using less compute. ### What VRAM for gpt oss 20b api? Requires ~16GB GPU VRAM. Delivers high throughput on single H100 or consumer hardware. ### Does gpt-oss-20b llm support tools? Supports built-in and user tools for agentic workflows. Handles multi-turn interactions reliably. Ready to create? --- Start generating with Gpt-oss-20b on ModelsLab. [Try Gpt-oss-20b](/models/openai/gpt-oss-20b) [API Documentation](https://docs.modelslab.com) --- *This markdown version is optimized for AI agents and LLMs.* **Links:** - [Website](https://modelslab.com) - [API Documentation](https://docs.modelslab.com) - [Blog](https://modelslab.com/blog) --- *Generated by ModelsLab - 2026-04-25*