GPT-OSS Model Comparison
Choose the right GPT-OSS model for your use case. Both models feature identical capabilities with different computational requirements and performance characteristics.
GPT-OSS-120B
117B parameters (5.1B active)
Recommended for
Production
Designed for production and general-purpose high reasoning use cases
Technical Specifications
Total Parameters:117B
Active Parameters:5.1B
Hardware Requirement:Single H100 GPU
Quantization:Native MXFP4
Key Features
- Configurable reasoning levels
- Full chain-of-thought reasoning access
- Native MXFP4 quantization
- Runs on a single H100 GPU
Capabilities
- Function calling
- Web browsing
- Python code execution
- Structured outputs
GPT-OSS-20B
21B parameters (3.6B active)
Recommended for
Consumer Hardware
Can run within 16GB of memory for consumer hardware
Technical Specifications
Total Parameters:21B
Active Parameters:3.6B
Memory Requirement:16GB RAM
Quantization:Native MXFP4
Key Features
- Configurable reasoning levels
- Full chain-of-thought reasoning
- Native MXFP4 quantization
- Fine-tunable on consumer hardware
Capabilities
- Function calling
- Web browsing
- Python code execution
- Structured outputs
Quick Comparison
| Feature | GPT-OSS-120B | GPT-OSS-20B |
|---|---|---|
| Total Parameters | 117B | 21B |
| Memory Requirement | H100 GPU | 16GB RAM |
| Reasoning Levels | ✅ Low/Medium/High | ✅ Low/Medium/High |
| Function Calling | ✅ | ✅ |
| Fine-tuning | ✅ | ✅ |
| Apache 2.0 License | ✅ | ✅ |