DeepSeek R1 vs Mistral Small 3.2 24B
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 DeepSeek R1 and Mistral Small 3.2 24B.
DeepSeek R1
A premier reasoning model employing large-scale reinforcement learning. Displays specialized math, coding, and logical validation capabilities comparable to OpenAI's 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...
Technical Specifications
| Specification | DeepSeek R1 | Mistral Small 3.2 24B |
|---|---|---|
| Provider | DeepSeek | Mistral |
| Context Window | 163,840 tokens | 128,000 tokens |
| Agent Suitability | 78/100 | N/A |
| Time to First Token (TTFT) | 1800 ms | N/A |
| Deployment Model | managed api | self hostable |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2025-01-20 | 2025-06-20 |
API Pricing Comparison
Input Price per Million Tokens
DeepSeek R1
$0.70
Mistral Small 3.2 24B
$0.07
Output Price per Million Tokens
DeepSeek R1
$2.50
Mistral Small 3.2 24B
$0.20
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Benchmark Performance Metrics
Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.
DeepSeek R1 Quirks & Gotchas
- ▸Reasoning model — not designed for high-frequency tool calling
- ▸Pair with a smaller model (V4 Flash) for routing and use R1 for complex reasoning only
Mistral Small 3.2 24B Quirks & Gotchas
No developer gotchas reported.