ZMIME
Comparison · 3 models · Updated Oct 4, 2026

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

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. 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

  2. Alibaba (Qwen)

    Qwen Turbo

    Released Nov 1, 2024

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

  3. 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
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-LiteGemini 2.5 Flash-Lite: Text, Images, PDFs, Audio, Video · Qwen Turbo: Text · Mistral Small 3.2: Text, Images
  • Self-hostingMistral Small 3.2Publishes downloadable weights
How the score is built
MeasureWeightGemini 2.5 Flash-LiteQwen TurboMistral Small 3.2
Price50%8610089
Inputs & features30%1003550
Context window20%616024
Overall100%85/10072/10064/100

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.

Gemini 2.5 Flash-Lite vs Qwen Turbo vs Mistral Small 3.2 specifications side by side
SpecificationGemini 2.5 Flash-LiteGoogleQwen TurboAlibaba (Qwen)Mistral Small 3.2Mistral AI
Capability
Capabilities Index (ECI)133.9 (best)—131.7
ECI rank#118 of 148 (best)—#123 of 148
GPQA DiamondGraduate-level science questions—41.8%49.1% (best)
OTIS Mock AIME 2024–2025Competition mathematics—6.1%30.3% (best)
Price per million tokens
Input$0.10$0.05 (best)$0.10
Output$0.40$0.20 (best)$0.30
Cached input$0.01——
Blended (3:1)$0.175$0.087 (best)$0.15
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Google APIOfficial Alibaba APIOfficial Mistral API
Limits
Context window1,048,576 tokens (best)1,000,000 tokens128,000 tokens
Max output65,536 tokens (best)16,384 tokens16,384 tokens
Inputs and features
TextYesYesYes
ImagesYesNoYes
PDFsYesNoNo
AudioYesNoNo
VideoYesNoNo
ReasoningYesYesNo
Tool callingYesYesYes
Structured outputYesNoNo
Availability
WeightsProprietaryProprietaryOpen
API model IDgemini-2.5-flash-liteqwen-turbomistral-small-2506
API providers20 (best)36
ReleasedJun 17, 2025Nov 1, 2024Jun 20, 2025
Knowledge cutoffJan 2025Apr 2024Mar 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.

  • Gemini 2.5 Flash-Lite$1.80
  • Qwen Turbo$0.90
  • Mistral Small 3.2$1.60
04 — Questions

Which should you choose?

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

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

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. Gemini 2.5 Flash-Lite has an ECI of 133.9, Qwen Turbo has not been scored yet and Mistral Small 3.2 has an ECI of 131.7.

Which is better for coding?

There are no published SWE-bench Verified results for Gemini 2.5 Flash-Lite, Qwen Turbo and Mistral Small 3.2 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: Gemini 2.5 Flash-Lite up to 65,536, Qwen Turbo up to 16,384, Mistral Small 3.2 up to 16,384 tokens.

Which can read images, PDFs, audio or video?

Gemini 2.5 Flash-Lite accepts text, images, PDFs, audio and video; Qwen Turbo accepts text; Mistral Small 3.2 accepts text and images. 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; Gemini 2.5 Flash-Lite and Qwen Turbo 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: Gemini 2.5 Flash-Lite Jan 2025, Qwen Turbo Apr 2024, 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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