ZMIME
Comparison · 2 models · Updated Nov 2, 2026

Mistral Small 3.2 vs Qwen3 30B-A3B Instruct 2507

Qwen3 30B-A3B Instruct 2507 comes out ahead, 58 to 51 on our weighted score.

  1. Mistral AI

    Mistral Small 3.2

    Released Jun 20, 2025Deprecated

    51/100
    • ECI—
    • Price$0.10 / $0.30
    • Context128K
    Full specs Remove Mistral Small 3.2
  2. Our pick

    Alibaba (Qwen)

    Qwen3 30B-A3B Instruct 2507

    Released Jul 28, 2025

    58/100
    • ECI137.3
    • Price$0.10 / $0.30
    • Context262K
    Full specs Remove Qwen3 30B-A3B Instruct 2507

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Qwen3 30B-A3B Instruct 2507 is our pick

Qwen3 30B-A3B Instruct 2507 is the better all-round choice, scoring 58/100 against Mistral Small 3.2 (51). It leads on capability and context window. Mistral Small 3.2 wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025), because Mistral Small 3.2 has no Capabilities Index score yet.

  • CapabilityQwen3 30B-A3B Instruct 2507Shared benchmarks: Qwen3 30B-A3B Instruct 2507 58.9% · Mistral Small 3.2 39.7%
  • Lowest priceSame priceMistral Small 3.2 $0.15 · Qwen3 30B-A3B Instruct 2507 $0.15 per 1M tokens (3:1 blend)
  • Longest contextQwen3 30B-A3B Instruct 2507Qwen3 30B-A3B Instruct 2507 262,144 · Mistral Small 3.2 128,000 tokens
  • Widest inputsMistral Small 3.2Mistral Small 3.2: Text, Images · Qwen3 30B-A3B Instruct 2507: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightMistral Small 3.2Qwen3 30B-A3B Instruct 2507
CapabilityShared benchmarks50%4059
Price25%8585
Inputs & features15%5025
Context window10%2437
Overall100%51/10058/100
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 30B-A3B Instruct 2507 specifications side by side
SpecificationMistral Small 3.2Mistral AIQwen3 30B-A3B Instruct 2507Alibaba (Qwen)
Capability
Capabilities Index (ECI)—137.3
ECI rank—#124 of 165
GPQA DiamondGraduate-level science questions49.1%55.6% (best)
OTIS Mock AIME 2024–2025Competition mathematics30.3%62.2% (best)
Price per million tokens
Input$0.10$0.10
Output$0.30$0.30
Cached input——
Blended (3:1)$0.15$0.15
Long-context rateSame rateSame rate
Price sourceOfficial Mistral APIMedian of 12 providers
Limits
Context window128,000 tokens262,144 tokens (best)
Max output16,384 tokens16,384 tokens
Inputs and features
TextYesYes
ImagesYesNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenOpenApache 2.0
API model IDmistral-small-2506—
API providers714 (best)
ReleasedJun 20, 2025Jul 28, 2025
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 30B-A3B Instruct 2507$1.60
04 — Questions

Which should you choose?

Which is better: Mistral Small 3.2 or Qwen3 30B-A3B Instruct 2507?

Qwen3 30B-A3B Instruct 2507 is the better all-round choice, scoring 58/100 against Mistral Small 3.2 (51). It leads on capability and context window. Mistral Small 3.2 wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%. Capability uses the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025), because Mistral Small 3.2 has no Capabilities Index score yet.

Which is cheaper, Mistral Small 3.2 or Qwen3 30B-A3B Instruct 2507?

Mistral Small 3.2 and Qwen3 30B-A3B Instruct 2507 cost the same: $0.10 input / $0.30 output per million tokens.

Which scores higher on benchmarks?

Not every model here has a Capabilities Index score, so we compare the average of shared benchmarks (GPQA Diamond and OTIS Mock AIME 2024–2025): Qwen3 30B-A3B Instruct 2507 58.9% and Mistral Small 3.2 39.7%. On individual benchmarks: GPQA Diamond — Qwen3 30B-A3B Instruct 2507 55.6%, Mistral Small 3.2 49.1%; OTIS Mock AIME 2024–2025 — Qwen3 30B-A3B Instruct 2507 62.2%, 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 30B-A3B Instruct 2507 yet, so there is no like-for-like coding score. On overall capability, Qwen3 30B-A3B 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 30B-A3B 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 30B-A3B Instruct 2507 up to 16,384 tokens.

Which can read images, PDFs, audio or video?

Mistral Small 3.2 accepts text and images; Qwen3 30B-A3B 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 30B-A3B Instruct 2507 is the newest, released Jul 28, 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 Nov 2, 2026.

05 — Keep comparing

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