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Comparison · 2 models · Updated Oct 4, 2026

Qwen3 235B-A22B Instruct 2507 vs Mistral Small 3.2

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.

  1. Alibaba (Qwen)

    Qwen3 235B-A22B Instruct 2507

    Released Jul 21, 2025

    58/100
    • ECI138.9
    • Price$0.15 / $0.75
    • Context262K
    Full specs Remove Qwen3 235B-A22B Instruct 2507

  2. Mistral AI

    Mistral Small 3.2

    Released Jun 20, 2025

    60/100
    • ECI131.7
    • Price$0.10 / $0.30
    • Context128K
    Full specs Remove Mistral Small 3.2

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01 — Verdict

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 3.2Qwen3 235B-A22B Instruct 2507: Text · Mistral Small 3.2: Text, Images
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightQwen3 235B-A22B Instruct 2507Mistral Small 3.2
CapabilityCapabilities Index (ECI)50%6455
Price25%7589
Inputs & features15%2550
Context window10%3724
Overall100%58/10060/100
02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Qwen3 235B-A22B Instruct 2507 vs Mistral Small 3.2 specifications side by side
SpecificationQwen3 235B-A22B Instruct 2507Alibaba (Qwen)Mistral Small 3.2Mistral AI
Capability
Capabilities Index (ECI)138.9 (best)131.7
ECI rank#105 of 148 (best)#123 of 148
GPQA DiamondGraduate-level science questions—49.1%
OTIS Mock AIME 2024–2025Competition mathematics—30.3%
Price per million tokens
Input$0.15$0.10 (best)
Output$0.75$0.30 (best)
Cached input——
Blended (3:1)$0.30$0.15 (best)
Long-context rateSame rateSame rate
Price sourceMedian of 11 providersOfficial Mistral API
Limits
Context window262,144 tokens (best)128,000 tokens
Max output16,384 tokens16,384 tokens
Inputs and features
TextYesYes
ImagesNoYes
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenApache 2.0Open
API model ID—mistral-small-2506
API providers11 (best)6
ReleasedJul 21, 2025Jun 20, 2025
Knowledge cutoff—Mar 2025
03 — Cost

What would a month cost?

Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.

  • Qwen3 235B-A22B Instruct 2507$3.00
  • Mistral Small 3.2$1.60
04 — Questions

Which should you choose?

Which is better: Qwen3 235B-A22B Instruct 2507 or Mistral Small 3.2?

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, Qwen3 235B-A22B Instruct 2507 or Mistral Small 3.2?

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 Qwen3 235B-A22B Instruct 2507 and Mistral Small 3.2 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: Qwen3 235B-A22B Instruct 2507 up to 16,384, Mistral Small 3.2 up to 16,384 tokens.

Which can read images, PDFs, audio or video?

Qwen3 235B-A22B Instruct 2507 accepts text; Mistral Small 3.2 accepts text and images. 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.

05 — Keep comparing

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