gpt-oss-120b vs o1
How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for gpt-oss-120b and o1.
gpt-oss-120b
gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. It activates 5.1B parameters per forward pass and is optimized...
o1
The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding. The o1 model series is trained with large-scale reinforcement learning to reason...
Technical Specifications
| Specification | gpt-oss-120b | o1 |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Context Window | 131,072 tokens | 200,000 tokens |
| Agent Suitability | N/A | 88/100 |
| Time to First Token (TTFT) | N/A | 2500 ms |
| Deployment Model | managed api | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2025-08-05 | 2024-12-17 |
API Pricing Comparison
Input Price per Million Tokens
gpt-oss-120b
$0.03
o1
$15.00
Output Price per Million Tokens
gpt-oss-120b
$0.15
o1
$60.00
Want to test both models live?
Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.
Benchmark Performance Metrics
Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.
gpt-oss-120b Quirks & Gotchas
No developer gotchas reported.
o1 Quirks & Gotchas
- ▸Reasoning model — high latency by design, not for real-time use
- ▸Best for complex math/code reasoning where accuracy > speed
- ▸Use o3-mini when you need reasoning with lower latency