OpenAI: Gpt-oss-20b
OpenAI gpt-oss-20b MoE
Deploy Efficient Reasoning Models
MoE Architecture
21B Total 3.6B Active
Activates 3.6B parameters per token from 21B total for low-latency inference on single GPU.
Reasoning Levels
Low Medium High Effort
Set reasoning effort in system prompt to balance speed and performance on complex tasks.
Agentic Tools
Function Calling Support
Handles tool use, structured outputs, and chain-of-thought for STEM and coding.
Examples
See what OpenAI: Gpt-oss-20b can create
Copy any prompt below and try it yourself in the playground.
Math Proof
“Prove Fermat's Last Theorem step-by-step using high reasoning effort. Explain each mathematical concept clearly for advanced audience.”
Code Debugger
“Debug this Python function for sorting algorithms: def quicksort(arr): ... Identify errors and provide fixed version with medium reasoning.”
Physics Simulation
“Simulate quantum entanglement experiment. Describe setup, equations, and outcomes using low reasoning effort for quick overview.”
Algorithm Design
“Design efficient graph traversal algorithm for social network analysis. Include pseudocode and time complexity analysis with high effort.”
For Developers
A few lines of code.
Reasoning. 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
import requestsresponse = requests.post("https://modelslab.com/api/v7/llm/chat/completions",json={"key": "YOUR_API_KEY","prompt": "","model_id": ""})print(response.json())
Ready to create?
Start generating with OpenAI: Gpt-oss-20b on ModelsLab.