ZMIME
Comparison · 2 models · Updated Oct 4, 2026

Qwen Turbo vs Mistral Small 3.1 24B

Qwen Turbo comes out ahead, 48 to 44 on our weighted score, and it is the cheaper option too.

  1. Our pick

    Alibaba (Qwen)

    Qwen Turbo

    Released Nov 1, 2024

    48/100
    • ECI—
    • Price$0.05 / $0.20
    • Context1M
    Full specs Remove Qwen Turbo

  2. Mistral AI

    Mistral Small 3.1 24B

    Released Mar 17, 2025

    44/100
    • ECI127.5
    • Price$0.229 / $0.436
    • Context128K
    Full specs Remove Mistral Small 3.1 24B

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Qwen Turbo is our pick

Qwen Turbo is the better all-round choice, scoring 48/100 against Mistral Small 3.1 24B (44). It leads on price and context window. Mistral Small 3.1 24B wins on capability and 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 Qwen Turbo has no Capabilities Index score yet.

  • CapabilityMistral Small 3.1 24BShared benchmarks: Mistral Small 3.1 24B 26.7% · Qwen Turbo 24.0%
  • Lowest priceQwen TurboQwen Turbo $0.087 · Mistral Small 3.1 24B $0.281 per 1M tokens (3:1 blend)
  • Longest contextQwen TurboQwen Turbo 1,000,000 · Mistral Small 3.1 24B 128,000 tokens
  • Widest inputsMistral Small 3.1 24BQwen Turbo: Text · Mistral Small 3.1 24B: Text, Images
  • Self-hostingMistral Small 3.1 24BPublishes downloadable weights
How the score is built
MeasureWeightQwen TurboMistral Small 3.1 24B
CapabilityShared benchmarks50%2427
Price25%10076
Inputs & features15%3560
Context window10%6024
Overall100%48/10044/100
02 — Side by side

Every spec in one table

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

Qwen Turbo vs Mistral Small 3.1 24B specifications side by side
SpecificationQwen TurboAlibaba (Qwen)Mistral Small 3.1 24BMistral AI
Capability
Capabilities Index (ECI)—127.5
ECI rank—#132 of 148
GPQA DiamondGraduate-level science questions41.8%47.5% (best)
OTIS Mock AIME 2024–2025Competition mathematics6.1% (best)5.8%
Price per million tokens
Input$0.05 (best)$0.229
Output$0.20 (best)$0.436
Cached input——
Blended (3:1)$0.087 (best)$0.281
Long-context rateSame rateSame rate
Price sourceOfficial Alibaba APIMedian of 2 providers
Limits
Context window1,000,000 tokens (best)128,000 tokens
Max output16,384 tokens16,384 tokens
Inputs and features
TextYesYes
ImagesNoYes
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningYesNo
Tool callingYesYes
Structured outputNoYes
Availability
WeightsProprietaryOpen
API model IDqwen-turbo—
API providers3 (best)2
ReleasedNov 1, 2024Mar 17, 2025
Knowledge cutoffApr 2024Jun 2024
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.

  • Qwen Turbo$0.90
  • Mistral Small 3.1 24B$3.16
04 — Questions

Which should you choose?

Which is better: Qwen Turbo or Mistral Small 3.1 24B?

Qwen Turbo is the better all-round choice, scoring 48/100 against Mistral Small 3.1 24B (44). It leads on price and context window. Mistral Small 3.1 24B wins on capability and 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 Qwen Turbo has no Capabilities Index score yet.

Which is cheaper, Qwen Turbo or Mistral Small 3.1 24B?

Qwen Turbo is cheaper at $0.05 input / $0.20 output per million tokens (official Alibaba API price). Mistral Small 3.1 24B costs $0.229 input / $0.436 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $0.087 per million tokens for Qwen Turbo versus $0.281 for Mistral Small 3.1 24B (3.2× as much).

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): Mistral Small 3.1 24B 26.7% and Qwen Turbo 24.0%. On individual benchmarks: GPQA Diamond — Mistral Small 3.1 24B 47.5%, Qwen Turbo 41.8%; OTIS Mock AIME 2024–2025 — Qwen Turbo 6.1%, Mistral Small 3.1 24B 5.8%.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen Turbo and Mistral Small 3.1 24B yet, so there is no like-for-like coding score. On overall capability, Mistral Small 3.1 24B 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?

Qwen Turbo has the largest context window at 1,000,000 tokens, against 128,000 for Mistral Small 3.1 24B. Maximum output per response: Qwen Turbo up to 16,384, Mistral Small 3.1 24B up to 16,384 tokens.

Which can read images, PDFs, audio or video?

Qwen Turbo accepts text; Mistral Small 3.1 24B accepts text and images. Mistral Small 3.1 24B handles the widest range of inputs.

Are any of these open source?

Mistral Small 3.1 24B publishes its weights and can be self-hosted; Qwen Turbo is proprietary.

Which is newer?

Mistral Small 3.1 24B is the newest, released Mar 17, 2025. Qwen Turbo came out Nov 1, 2024. Knowledge cutoff: Qwen Turbo Apr 2024, Mistral Small 3.1 24B Jun 2024.

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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