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Comparison · 2 models · Updated Nov 2, 2026

Pixtral Large (25.02) vs Qwen3 VL 235B A22B Thinking

Qwen3 VL 235B A22B Thinking comes out ahead, 44 to 33 on our weighted score, and it is the cheaper option too.

  1. Mistral AI

    Pixtral Large (25.02)

    Released Apr 8, 2025

    33/100
    • ECI—
    • Price$2.00 / $6.00
    • Context128K
    Full specs Remove Pixtral Large (25.02)
  2. Our pick

    Alibaba (Qwen)

    Qwen3 VL 235B A22B Thinking

    Released Sep 23, 2025

    44/100
    • ECI—
    • Price$0.50 / $3.95
    • Context131K
    Full specs Remove Qwen3 VL 235B A22B Thinking

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Qwen3 VL 235B A22B Thinking is our pick

Qwen3 VL 235B A22B Thinking is the better all-round choice, scoring 44/100 against Pixtral Large (25.02) (33). It leads on price and inputs & features. 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 ThinkingQwen3 VL 235B A22B Thinking $1.36 · Pixtral Large (25.02) $3.00 per 1M tokens (3:1 blend)
  • Longest contextQwen3 VL 235B A22B ThinkingQwen3 VL 235B A22B Thinking 131,072 · Pixtral Large (25.02) 128,000 tokens
  • Widest inputsSame inputsPixtral Large (25.02): Text, Images · Qwen3 VL 235B A22B Thinking: Text, Images
  • Self-hostingQwen3 VL 235B A22B ThinkingPublishes downloadable weights
How the score is built
MeasureWeightPixtral Large (25.02)Qwen3 VL 235B A22B Thinking
Price50%2642
Inputs & features30%5060
Context window20%2425
Overall100%33/10044/100

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.

Pixtral Large (25.02) vs Qwen3 VL 235B A22B Thinking specifications side by side
SpecificationPixtral Large (25.02)Mistral AIQwen3 VL 235B A22B ThinkingAlibaba (Qwen)
Capability
Capabilities Index (ECI)——
ECI rank——
Price per million tokens
Input$2.00$0.50 (best)
Output$6.00$3.95 (best)
Cached input——
Blended (3:1)$3.00$1.36 (best)
Long-context rateSame rateSame rate
Price sourceMedian of 3 providersMedian of 5 providers
Limits
Context window128,000 tokens131,072 tokens (best)
Max output8,192 tokens32,768 tokens (best)
Inputs and features
TextYesYes
ImagesYesYes
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoYes
Tool callingYesYes
Structured outputNoNo
Availability
WeightsProprietaryOpen
API model ID——
API providers35 (best)
ReleasedApr 8, 2025Sep 23, 2025
Knowledge cutoff—Mar 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.

  • Pixtral Large (25.02)$32.00
  • Qwen3 VL 235B A22B Thinking$12.90
04 — Questions

Which should you choose?

Which is better: Pixtral Large (25.02) or Qwen3 VL 235B A22B Thinking?

Qwen3 VL 235B A22B Thinking is the better all-round choice, scoring 44/100 against Pixtral Large (25.02) (33). It leads on price and inputs & features. 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, Pixtral Large (25.02) or Qwen3 VL 235B A22B Thinking?

Qwen3 VL 235B A22B Thinking is cheaper at $0.50 input / $3.95 output per million tokens (median across 5 API providers). Pixtral Large (25.02) costs $2.00 input / $6.00 output per million tokens (median across 3 API providers). At a typical mix of three input tokens to one output token, that is $1.36 per million tokens for Qwen3 VL 235B A22B Thinking versus $3.00 for Pixtral Large (25.02) (2.2× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. Pixtral Large (25.02) 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 Pixtral Large (25.02) 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?

Qwen3 VL 235B A22B Thinking has the largest context window at 131,072 tokens, against 128,000 for Pixtral Large (25.02). Maximum output per response: Pixtral Large (25.02) up to 8,192, Qwen3 VL 235B A22B Thinking up to 32,768 tokens.

Which can read images, PDFs, audio or video?

Pixtral Large (25.02) 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; Pixtral Large (25.02) is proprietary.

Which is newer?

Qwen3 VL 235B A22B Thinking is the newest, released Sep 23, 2025. Pixtral Large (25.02) came out Apr 8, 2025. Knowledge cutoff: 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 Nov 2, 2026.

05 — Keep comparing

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