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Comparison · 2 models · Updated Oct 4, 2026

Qwen3 VL 235B A22B Instruct vs Mistral Medium 3.1

Qwen3 VL 235B A22B Instruct comes out ahead, 53 to 50 on our weighted score, and it is the cheaper option too.

  1. Our pick

    Alibaba (Qwen)

    Qwen3 VL 235B A22B Instruct

    Released Sep 23, 2025

    53/100
    • ECI—
    • Price$0.30 / $1.55
    • Context131K
    Full specs Remove Qwen3 VL 235B A22B Instruct

  2. 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

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Qwen3 VL 235B A22B Instruct is our pick

Qwen3 VL 235B A22B Instruct is the better all-round choice, scoring 53/100 against Mistral Medium 3.1 (50). It leads on price and inputs & features. Mistral Medium 3.1 wins on context window. 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 priceQwen3 VL 235B A22B InstructQwen3 VL 235B A22B Instruct $0.613 · Mistral Medium 3.1 $0.80 per 1M tokens (3:1 blend)
  • Longest contextMistral Medium 3.1Mistral Medium 3.1 262,144 · Qwen3 VL 235B A22B Instruct 131,072 tokens
  • Widest inputsSame inputsQwen3 VL 235B A22B Instruct: Text, Images · Mistral Medium 3.1: Text, Images
  • Self-hostingQwen3 VL 235B A22B InstructPublishes downloadable weights
How the score is built
MeasureWeightQwen3 VL 235B A22B InstructMistral Medium 3.1
Price50%6054
Inputs & features30%6050
Context window20%2437
Overall100%53/10050/100

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.

Qwen3 VL 235B A22B Instruct vs Mistral Medium 3.1 specifications side by side
SpecificationQwen3 VL 235B A22B InstructAlibaba (Qwen)Mistral Medium 3.1Mistral AI
Capability
Capabilities Index (ECI)——
ECI rank——
Price per million tokens
Input$0.30 (best)$0.40
Output$1.55 (best)$2.00
Cached input——
Blended (3:1)$0.613 (best)$0.80
Long-context rateSame rateSame rate
Price sourceMedian of 12 providersOfficial Mistral API
Limits
Context window131,072 tokens262,144 tokens (best)
Max output32,768 tokens262,144 tokens (best)
Inputs and features
TextYesYes
ImagesYesYes
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputYesNo
Availability
WeightsOpenProprietary
API model ID—mistral-medium-2508
API providers12 (best)1
ReleasedSep 23, 2025Aug 12, 2025
Knowledge cutoffMar 31, 2025May 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.

  • Qwen3 VL 235B A22B Instruct$6.10
  • Mistral Medium 3.1$8.00
04 — Questions

Which should you choose?

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

Qwen3 VL 235B A22B Instruct is the better all-round choice, scoring 53/100 against Mistral Medium 3.1 (50). It leads on price and inputs & features. Mistral Medium 3.1 wins on context window. 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, Qwen3 VL 235B A22B Instruct or Mistral Medium 3.1?

Qwen3 VL 235B A22B Instruct is cheaper at $0.30 input / $1.55 output per million tokens (median across 12 API providers). Mistral Medium 3.1 costs $0.40 input / $2.00 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.613 per million tokens for Qwen3 VL 235B A22B Instruct versus $0.80 for Mistral Medium 3.1 (1.3× as much).

Which scores higher on benchmarks?

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

Which is better for coding?

There are no published SWE-bench Verified results for Qwen3 VL 235B A22B Instruct and Mistral Medium 3.1 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 Instruct. Maximum output per response: Qwen3 VL 235B A22B Instruct up to 32,768, Mistral Medium 3.1 up to 262,144 tokens.

Which can read images, PDFs, audio or video?

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

Are any of these open source?

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

Which is newer?

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