Mistral Small 3.2 24B 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 Mistral Small 3.2 24B and o1.
Mistral Small 3.2 24B
Mistral-Small-3.2-24B-Instruct-2506 is an updated 24B parameter model from Mistral optimized for instruction following, repetition reduction, and improved function calling. Compared to the 3.1 release, version 3.2 significantly improves accuracy on...
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 | Mistral Small 3.2 24B | o1 |
|---|---|---|
| Provider | Mistral | OpenAI |
| Context Window | 128,000 tokens | 200,000 tokens |
| Agent Suitability | N/A | 88/100 |
| Time to First Token (TTFT) | N/A | 2500 ms |
| Deployment Model | self hostable | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2025-06-20 | 2024-12-17 |
API Pricing Comparison
Input Price per Million Tokens
Mistral Small 3.2 24B
$0.07
o1
$15.00
Output Price per Million Tokens
Mistral Small 3.2 24B
$0.20
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.
Mistral Small 3.2 24B 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