Mistral Small 3.2 vs Qwen3 235B-A22B Instruct 2507
Too close to call on our weighted score (Mistral Small 3.2 60, Qwen3 235B-A22B Instruct 2507 58). The right pick depends on what you value most.
Mistral AIMistral Small 3.2
60/100- ECI131.7
- Price$0.10 / $0.30
- Context128K
Alibaba (Qwen)Qwen3 235B-A22B Instruct 2507
58/100- ECI138.9
- Price$0.15 / $0.75
- Context262K
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Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within 2 points (Mistral Small 3.2 60/100, Qwen3 235B-A22B Instruct 2507 58/100), so choose by what matters most for your work: Qwen3 235B-A22B Instruct 2507 for raw capability and Mistral Small 3.2 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen3 235B-A22B Instruct 2507Capabilities Index (ECI): Qwen3 235B-A22B Instruct 2507 138.9 · Mistral Small 3.2 131.7
- Lowest priceMistral Small 3.2Mistral Small 3.2 $0.15 · Qwen3 235B-A22B Instruct 2507 $0.30 per 1M tokens (3:1 blend)
- Longest contextQwen3 235B-A22B Instruct 2507Qwen3 235B-A22B Instruct 2507 262,144 · Mistral Small 3.2 128,000 tokens
- Widest inputsMistral Small 3.2Mistral Small 3.2: Text, Images · Qwen3 235B-A22B Instruct 2507: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Mistral Small 3.2 | Qwen3 235B-A22B Instruct 2507 |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 55 | 64 |
| Price | 25% | 89 | 75 |
| Inputs & features | 15% | 50 | 25 |
| Context window | 10% | 24 | 37 |
| Overall | 100% | 60/100 | 58/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Mistral Small 3.2Mistral AI | Qwen3 235B-A22B Instruct 2507Alibaba (Qwen) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 131.7 | 138.9 (best) |
| ECI rank | #123 of 148 | #105 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 49.1% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 30.3% | — |
| Price per million tokens | ||
| Input | $0.10 (best) | $0.15 |
| Output | $0.30 (best) | $0.75 |
| Cached input | — | — |
| Blended (3:1) | $0.15 (best) | $0.30 |
| Long-context rate | Same rate | Same rate |
| Price source | Official Mistral API | Median of 11 providers |
| Limits | ||
| Context window | 128,000 tokens | 262,144 tokens (best) |
| Max output | 16,384 tokens | 16,384 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Open | OpenApache 2.0 |
| API model ID | mistral-small-2506 | — |
| API providers | 6 | 11 (best) |
| Released | Jun 20, 2025 | Jul 21, 2025 |
| Knowledge cutoff | Mar 2025 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Mistral Small 3.2$1.60
- Qwen3 235B-A22B Instruct 2507$3.00
Which should you choose?
Which is better: Mistral Small 3.2 or Qwen3 235B-A22B Instruct 2507?
It is close. Our weighted score puts them within 2 points (Mistral Small 3.2 60/100, Qwen3 235B-A22B Instruct 2507 58/100), so choose by what matters most for your work: Qwen3 235B-A22B Instruct 2507 for raw capability and Mistral Small 3.2 on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Mistral Small 3.2 or Qwen3 235B-A22B Instruct 2507?
Mistral Small 3.2 is cheaper at $0.10 input / $0.30 output per million tokens (official Mistral API price). Qwen3 235B-A22B Instruct 2507 costs $0.15 input / $0.75 output per million tokens (median across 11 API providers). At a typical mix of three input tokens to one output token, that is $0.15 per million tokens for Mistral Small 3.2 versus $0.30 for Qwen3 235B-A22B Instruct 2507 (2× as much).
Which scores higher on benchmarks?
Qwen3 235B-A22B Instruct 2507 scores higher on the Capabilities Index (ECI): Qwen3 235B-A22B Instruct 2507 138.9 (#105 of 148) and Mistral Small 3.2 131.7 (#123 of 148). Their confidence ranges do not overlap (135.8–140.6 vs 126.6–133.9), so the gap is a real one.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Small 3.2 and Qwen3 235B-A22B Instruct 2507 yet, so there is no like-for-like coding score. On overall capability, Qwen3 235B-A22B Instruct 2507 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
Qwen3 235B-A22B Instruct 2507 has the largest context window at 262,144 tokens, against 128,000 for Mistral Small 3.2. Maximum output per response: Mistral Small 3.2 up to 16,384, Qwen3 235B-A22B Instruct 2507 up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Mistral Small 3.2 accepts text and images; Qwen3 235B-A22B Instruct 2507 accepts text. Mistral Small 3.2 handles the widest range of inputs.
Are any of these open source?
Yes, both publish their weights (Apache 2.0), so you can self-host them.
Which is newer?
Qwen3 235B-A22B Instruct 2507 is the newest, released Jul 21, 2025. Mistral Small 3.2 came out Jun 20, 2025. Knowledge cutoff: Mistral Small 3.2 Mar 2025.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
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