Mistral Nemo vs Qwen3.5 397B A17B
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 Qwen3.5 397B A17B.
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,...
Qwen3.5 397B A17B
The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers...
Technical Specifications
| Specification | Mistral Nemo | Qwen3.5 397B A17B |
|---|---|---|
| Provider | Mistral | Alibaba |
| Context Window | 131,072 tokens | 256,000 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 | 2026-02-16 |
API Pricing Comparison
Input Price per Million Tokens
Mistral Nemo
$0.02
Qwen3.5 397B A17B
$0.39
Output Price per Million Tokens
Mistral Nemo
$0.03
Qwen3.5 397B A17B
$2.45
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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.
Qwen3.5 397B A17B Quirks & Gotchas
No developer gotchas reported.