Mistral Nemo vs R1
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 Nemo and R1.
Mistral Nemo
A 12B parameter model with a 128k token context length built by Mistral in collaboration with NVIDIA. The model is multilingual, supporting English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese,...
R1
DeepSeek R1 is here: Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inference pass....
Technical Specifications
| Specification | Mistral Nemo | R1 |
|---|---|---|
| Provider | Mistral | DeepSeek |
| Context Window | 131,072 tokens | 163,840 tokens |
| Agent Suitability | N/A | N/A |
| Time to First Token (TTFT) | N/A | N/A |
| Deployment Model | self hostable | self hostable |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2024-07-19 | 2025-01-20 |
API Pricing Comparison
Input Price per Million Tokens
Mistral Nemo
$0.02
R1
$0.70
Output Price per Million Tokens
Mistral Nemo
$0.03
R1
$2.50
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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.
Mistral Nemo Quirks & Gotchas
No developer gotchas reported.
R1 Quirks & Gotchas
No developer gotchas reported.