Mistral Large vs Qwen 3
Pricing, benchmarks, and use case comparison
Quick take
- •Mistral Large is meaningfully stronger at multimodal (65 vs 30 on our capability index).
- •Qwen 3 is meaningfully stronger at cost efficiency (90 vs 66).
- •Qwen 3 is open-weights (free to self-host); Mistral Large is paid API only.
Specs comparison
| Mistral Large | Qwen 3 | |
|---|---|---|
| Provider | Mistral AI | Alibaba (Qwen Team) |
| Type | Closed source | Open source |
| Context window | 128000 | 128K tokens (32K for 0.6B/1.7B/4B dense variants) |
| Input / 1M tokens | 2.00 | ✓Free (self-host) |
| Output / 1M tokens | 6.00 | Free (self-host) |
| Release date | 2024-02 | 2025-04 |
Benchmarks
| Benchmark | Mistral Large | Qwen 3 |
|---|---|---|
| MMLU | 84.0% | - |
| HumanEval | 92.0% | - |
| Qwen3-235B-A22B | - | 235B total / 22B active |
| Qwen3-30B-A3B | - | 30B total / 3B active |
Scores sourced from official provider release posts and independent benchmark aggregators.
Which should you choose?
Choose Mistral Large if...
- →You need a strong European-built flagship with open weights
- →Your work is multilingual or requires nuanced reasoning
- →You want structured/JSON output and solid coding ability
- →You need the option to self-host for data sovereignty
Choose Qwen 3 if...
- →You need an open, self-hostable model with a permissive license
- →You want to toggle deep reasoning on or off per request
- →Multilingual applications
- →Efficient inference via MoE with few active parameters