ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Mistral Small 3.2 vs Qwen Turbo vs Gemini 2.5 Flash-Lite

Gemini 2.5 Flash-Lite comes out ahead, 85 to 72 and 64 on our weighted score, though Qwen Turbo is 2× cheaper per token.

  1. Mistral AI

    Mistral Small 3.2

    Released Jun 20, 2025

    64/100
    • ECI131.7
    • Price$0.10 / $0.30
    • Context128K
    Full specs Remove Mistral Small 3.2

  2. Alibaba (Qwen)

    Qwen Turbo

    Released Nov 1, 2024

    72/100
    • ECI—
    • Price$0.05 / $0.20
    • Context1M
    Full specs Remove Qwen Turbo
  3. Our pick

    Google

    Gemini 2.5 Flash-Lite

    Released Jun 17, 2025

    85/100
    • ECI133.9
    • Price$0.10 / $0.40
    • Context1.05M
    Full specs Remove Gemini 2.5 Flash-Lite
01 — Verdict

Gemini 2.5 Flash-Lite is our pick

Gemini 2.5 Flash-Lite is the better all-round choice, scoring 85/100 against Qwen Turbo (72) and Mistral Small 3.2 (64). It leads on inputs & features. Qwen Turbo wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

  • CapabilityNot enough dataNo independent benchmark covers every model here yet
  • Lowest priceQwen TurboQwen Turbo $0.087 · Mistral Small 3.2 $0.15 · Gemini 2.5 Flash-Lite $0.175 per 1M tokens (3:1 blend)
  • Longest contextGemini 2.5 Flash-LiteGemini 2.5 Flash-Lite 1,048,576 · Qwen Turbo 1,000,000 · Mistral Small 3.2 128,000 tokens
  • Widest inputsGemini 2.5 Flash-LiteMistral Small 3.2: Text, Images · Qwen Turbo: Text · Gemini 2.5 Flash-Lite: Text, Images, PDFs, Audio, Video
  • Self-hostingMistral Small 3.2Publishes downloadable weights
How the score is built
MeasureWeightMistral Small 3.2Qwen TurboGemini 2.5 Flash-Lite
Price50%8910086
Inputs & features30%5035100
Context window20%246061
Overall100%64/10072/10085/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

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 Qwen Turbo vs Gemini 2.5 Flash-Lite specifications side by side
SpecificationMistral Small 3.2Mistral AIQwen TurboAlibaba (Qwen)Gemini 2.5 Flash-LiteGoogle
Capability
Capabilities Index (ECI)131.7—133.9 (best)
ECI rank#123 of 148—#118 of 148 (best)
GPQA DiamondGraduate-level science questions49.1% (best)41.8%—
OTIS Mock AIME 2024–2025Competition mathematics30.3% (best)6.1%—
Price per million tokens
Input$0.10$0.05 (best)$0.10
Output$0.30$0.20 (best)$0.40
Cached input——$0.01
Blended (3:1)$0.15$0.087 (best)$0.175
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Mistral APIOfficial Alibaba APIOfficial Google API
Limits
Context window128,000 tokens1,000,000 tokens1,048,576 tokens (best)
Max output16,384 tokens16,384 tokens65,536 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesNoYes
PDFsNoNoYes
AudioNoNoYes
VideoNoNoYes
ReasoningNoYesYes
Tool callingYesYesYes
Structured outputNoNoYes
Availability
WeightsOpenProprietaryProprietary
API model IDmistral-small-2506qwen-turbogemini-2.5-flash-lite
API providers6320 (best)
ReleasedJun 20, 2025Nov 1, 2024Jun 17, 2025
Knowledge cutoffMar 2025Apr 2024Jan 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
  • Qwen Turbo$0.90
  • Gemini 2.5 Flash-Lite$1.80
04 — Questions

Which should you choose?

Which is better: Mistral Small 3.2, Qwen Turbo or Gemini 2.5 Flash-Lite?

Gemini 2.5 Flash-Lite is the better all-round choice, scoring 85/100 against Qwen Turbo (72) and Mistral Small 3.2 (64). It leads on inputs & features. Qwen Turbo wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

Which is cheaper, Mistral Small 3.2, Qwen Turbo or Gemini 2.5 Flash-Lite?

Qwen Turbo is cheaper at $0.05 input / $0.20 output per million tokens (official Alibaba API price). Mistral Small 3.2 costs $0.10 input / $0.30 output per million tokens (official Mistral API price); Gemini 2.5 Flash-Lite costs $0.10 input / $0.40 output per million tokens (official Google API price). At a typical mix of three input tokens to one output token, that is $0.087 per million tokens for Qwen Turbo versus $0.15 for Mistral Small 3.2 (1.7× as much) and $0.175 for Gemini 2.5 Flash-Lite (2× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Mistral Small 3.2 has an ECI of 131.7, Qwen Turbo has not been scored yet and Gemini 2.5 Flash-Lite has an ECI of 133.9.

Which is better for coding?

There are no published SWE-bench Verified results for Mistral Small 3.2, Qwen Turbo and Gemini 2.5 Flash-Lite yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.

Which has the bigger context window?

Gemini 2.5 Flash-Lite has the largest context window at 1,048,576 tokens, against 1,000,000 for Qwen Turbo and 128,000 for Mistral Small 3.2. Maximum output per response: Mistral Small 3.2 up to 16,384, Qwen Turbo up to 16,384, Gemini 2.5 Flash-Lite up to 65,536 tokens.

Which can read images, PDFs, audio or video?

Mistral Small 3.2 accepts text and images; Qwen Turbo accepts text; Gemini 2.5 Flash-Lite accepts text, images, PDFs, audio and video. Gemini 2.5 Flash-Lite handles the widest range of inputs.

Are any of these open source?

Mistral Small 3.2 publishes its weights and can be self-hosted; Qwen Turbo and Gemini 2.5 Flash-Lite is proprietary.

Which is newer?

Mistral Small 3.2 is the newest, released Jun 20, 2025. Gemini 2.5 Flash-Lite came out Jun 17, 2025; Qwen Turbo came out Nov 1, 2024. Knowledge cutoff: Mistral Small 3.2 Mar 2025, Qwen Turbo Apr 2024, Gemini 2.5 Flash-Lite Jan 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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