Mistral Nemo vs Qwen3 30B A3B Instruct 2507
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 30B A3B Instruct 2507.
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 30B A3B Instruct 2507
Qwen3-30B-A3B-Instruct-2507 is a 30.5B-parameter mixture-of-experts language model from Qwen, with 3.3B active parameters per inference. It operates in non-thinking mode and is designed for high-quality instruction following, multilingual understanding, and...
Technical Specifications
| Specification | Mistral Nemo | Qwen3 30B A3B Instruct 2507 |
|---|---|---|
| Provider | Mistral | Alibaba |
| Context Window | 131,072 tokens | 131,072 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 | 2025-07-29 |
API Pricing Comparison
Input Price per Million Tokens
Mistral Nemo
$0.02
Qwen3 30B A3B Instruct 2507
$0.05
Output Price per Million Tokens
Mistral Nemo
$0.03
Qwen3 30B A3B Instruct 2507
$0.19
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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 30B A3B Instruct 2507 Quirks & Gotchas
No developer gotchas reported.