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Comparison · 2 models · Updated Oct 4, 2026

Mistral Medium 3.1 vs Qwen3 VL 235B A22B Thinking

Too close to call on our weighted score (Mistral Medium 3.1 50, Qwen3 VL 235B A22B Thinking 48). The right pick depends on what you value most.

  1. Mistral AI

    Mistral Medium 3.1

    Released Aug 12, 2025

    50/100
    • ECI—
    • Price$0.40 / $2.00
    • Context262K
    Full specs Remove Mistral Medium 3.1

  2. Alibaba (Qwen)

    Qwen3 VL 235B A22B Thinking

    Released Sep 23, 2025

    48/100
    • ECI—
    • Price$0.40 / $4.00
    • Context131K
    Full specs Remove Qwen3 VL 235B A22B Thinking

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Too close to call

It is close. Our weighted score puts them within 1 points (Mistral Medium 3.1 50/100, Qwen3 VL 235B A22B Thinking 48/100), so choose by what matters most for your work: Mistral Medium 3.1 on price and Mistral Medium 3.1 for long inputs. 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 priceMistral Medium 3.1Mistral Medium 3.1 $0.80 · Qwen3 VL 235B A22B Thinking $1.30 per 1M tokens (3:1 blend)
  • Longest contextMistral Medium 3.1Mistral Medium 3.1 262,144 · Qwen3 VL 235B A22B Thinking 131,072 tokens
  • Widest inputsSame inputsMistral Medium 3.1: Text, Images · Qwen3 VL 235B A22B Thinking: Text, Images
  • Self-hostingQwen3 VL 235B A22B ThinkingPublishes downloadable weights
How the score is built
MeasureWeightMistral Medium 3.1Qwen3 VL 235B A22B Thinking
Price50%5444
Inputs & features30%5070
Context window20%3724
Overall100%50/10048/100

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 Medium 3.1 vs Qwen3 VL 235B A22B Thinking specifications side by side
SpecificationMistral Medium 3.1Mistral AIQwen3 VL 235B A22B ThinkingAlibaba (Qwen)
Capability
Capabilities Index (ECI)——
ECI rank——
Price per million tokens
Input$0.40$0.40
Output$2.00 (best)$4.00
Cached input——
Blended (3:1)$0.80 (best)$1.30
Long-context rateSame rateSame rate
Price sourceOfficial Mistral APIMedian of 9 providers
Limits
Context window262,144 tokens (best)131,072 tokens
Max output262,144 tokens (best)32,768 tokens
Inputs and features
TextYesYes
ImagesYesYes
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoYes
Tool callingYesYes
Structured outputNoYes
Availability
WeightsProprietaryOpen
API model IDmistral-medium-2508—
API providers19 (best)
ReleasedAug 12, 2025Sep 23, 2025
Knowledge cutoffMay 2025Mar 31, 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 Medium 3.1$8.00
  • Qwen3 VL 235B A22B Thinking$12.00
04 — Questions

Which should you choose?

Which is better: Mistral Medium 3.1 or Qwen3 VL 235B A22B Thinking?

It is close. Our weighted score puts them within 1 points (Mistral Medium 3.1 50/100, Qwen3 VL 235B A22B Thinking 48/100), so choose by what matters most for your work: Mistral Medium 3.1 on price and Mistral Medium 3.1 for long inputs. 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 Medium 3.1 or Qwen3 VL 235B A22B Thinking?

Mistral Medium 3.1 is cheaper at $0.40 input / $2.00 output per million tokens (official Mistral API price). Qwen3 VL 235B A22B Thinking costs $0.40 input / $4.00 output per million tokens (median across 9 API providers). At a typical mix of three input tokens to one output token, that is $0.80 per million tokens for Mistral Medium 3.1 versus $1.30 for Qwen3 VL 235B A22B Thinking (1.6× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. Mistral Medium 3.1 has not been scored yet and Qwen3 VL 235B A22B Thinking has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Mistral Medium 3.1 and Qwen3 VL 235B A22B Thinking yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.

Which has the bigger context window?

Mistral Medium 3.1 has the largest context window at 262,144 tokens, against 131,072 for Qwen3 VL 235B A22B Thinking. Maximum output per response: Mistral Medium 3.1 up to 262,144, Qwen3 VL 235B A22B Thinking up to 32,768 tokens.

Which can read images, PDFs, audio or video?

Mistral Medium 3.1 accepts text and images; Qwen3 VL 235B A22B Thinking accepts text and images. They handle the same number of input types.

Are any of these open source?

Qwen3 VL 235B A22B Thinking publishes its weights and can be self-hosted; Mistral Medium 3.1 is proprietary.

Which is newer?

Qwen3 VL 235B A22B Thinking is the newest, released Sep 23, 2025. Mistral Medium 3.1 came out Aug 12, 2025. Knowledge cutoff: Mistral Medium 3.1 May 2025, Qwen3 VL 235B A22B Thinking Mar 31, 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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