ZMIME
Comparison · 2 models · Updated Oct 4, 2026

Mistral Small 3.2 vs Qwen3.5 9B

Qwen3.5 9B comes out ahead, 72 to 60 on our weighted score, and it is the cheaper option too.

  1. 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
  2. Our pick

    Alibaba (Qwen)

    Qwen3.5 9B

    Released Feb 23, 2026

    72/100
    • ECI139.5
    • Price$0.10 / $0.15
    • Context262K
    Full specs Remove Qwen3.5 9B

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Qwen3.5 9B is our pick

Qwen3.5 9B is the better all-round choice, scoring 72/100 against Mistral Small 3.2 (60). It leads on capability, price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityQwen3.5 9BCapabilities Index (ECI): Qwen3.5 9B 139.5 · Mistral Small 3.2 131.7
  • Lowest priceQwen3.5 9BQwen3.5 9B $0.113 · Mistral Small 3.2 $0.15 per 1M tokens (3:1 blend)
  • Longest contextQwen3.5 9BQwen3.5 9B 262,144 · Mistral Small 3.2 128,000 tokens
  • Widest inputsQwen3.5 9BMistral Small 3.2: Text, Images · Qwen3.5 9B: Text, Images, Video
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightMistral Small 3.2Qwen3.5 9B
CapabilityCapabilities Index (ECI)50%5565
Price25%8995
Inputs & features15%5080
Context window10%2437
Overall100%60/10072/100
02 — Side by side

Every spec in one table

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

Mistral Small 3.2 vs Qwen3.5 9B specifications side by side
SpecificationMistral Small 3.2Mistral AIQwen3.5 9BAlibaba (Qwen)
Capability
Capabilities Index (ECI)131.7139.5 (best)
ECI rank#123 of 148#101 of 148 (best)
GPQA DiamondGraduate-level science questions49.1%79.0% (best)
OTIS Mock AIME 2024–2025Competition mathematics30.3%61.7% (best)
Price per million tokens
Input$0.10$0.10
Output$0.30$0.15 (best)
Cached input——
Blended (3:1)$0.15$0.113 (best)
Long-context rateSame rateSame rate
Price sourceOfficial Mistral APIMedian of 14 providers
Limits
Context window128,000 tokens262,144 tokens (best)
Max output16,384 tokens65,536 tokens (best)
Inputs and features
TextYesYes
ImagesYesYes
PDFsNoNo
AudioNoNo
VideoNoYes
ReasoningNoYes
Tool callingYesYes
Structured outputNoYes
Availability
WeightsOpenOpen
API model IDmistral-small-2506—
API providers615 (best)
ReleasedJun 20, 2025Feb 23, 2026
Knowledge cutoffMar 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.

  • Mistral Small 3.2$1.60
  • Qwen3.5 9B$1.30
04 — Questions

Which should you choose?

Which is better: Mistral Small 3.2 or Qwen3.5 9B?

Qwen3.5 9B is the better all-round choice, scoring 72/100 against Mistral Small 3.2 (60). It leads on capability, price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Mistral Small 3.2 or Qwen3.5 9B?

Qwen3.5 9B is cheaper at $0.10 input / $0.15 output per million tokens (median across 14 API providers). Mistral Small 3.2 costs $0.10 input / $0.30 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.113 per million tokens for Qwen3.5 9B versus $0.15 for Mistral Small 3.2 (1.3× as much).

Which scores higher on benchmarks?

Qwen3.5 9B scores higher on the Capabilities Index (ECI): Qwen3.5 9B 139.5 (#101 of 148) and Mistral Small 3.2 131.7 (#123 of 148). Their confidence ranges do not overlap (136.5–141.3 vs 126.6–133.9), so the gap is a real one. On individual benchmarks: GPQA Diamond — Qwen3.5 9B 79.0%, Mistral Small 3.2 49.1%; OTIS Mock AIME 2024–2025 — Qwen3.5 9B 61.7%, Mistral Small 3.2 30.3%.

Which is better for coding?

There are no published SWE-bench Verified results for Mistral Small 3.2 and Qwen3.5 9B yet, so there is no like-for-like coding score. On overall capability, Qwen3.5 9B 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?

Qwen3.5 9B 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, Qwen3.5 9B up to 65,536 tokens.

Which can read images, PDFs, audio or video?

Mistral Small 3.2 accepts text and images; Qwen3.5 9B accepts text, images and video. Qwen3.5 9B handles the widest range of inputs.

Are any of these open source?

Yes, both publish their weights, so you can self-host them.

Which is newer?

Qwen3.5 9B is the newest, released Feb 23, 2026. 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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