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Comparison · 2 models · Updated Oct 4, 2026

Qwen3 VL 235B A22B Thinking vs MiniMax-M2

Too close to call on our weighted score (MiniMax-M2 48, Qwen3 VL 235B A22B Thinking 48). The right pick depends on what you value most.

  1. 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

  2. MiniMax

    MiniMax-M2

    Released Oct 27, 2025

    48/100
    • ECI—
    • Price$0.30 / $1.20
    • Context205K
    Full specs Remove MiniMax-M2

  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 a point (MiniMax-M2 48/100, Qwen3 VL 235B A22B Thinking 48/100), so choose by what matters most for your work: MiniMax-M2 on price and MiniMax-M2 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 priceMiniMax-M2MiniMax-M2 $0.525 · Qwen3 VL 235B A22B Thinking $1.30 per 1M tokens (3:1 blend)
  • Longest contextMiniMax-M2MiniMax-M2 204,800 · Qwen3 VL 235B A22B Thinking 131,072 tokens
  • Widest inputsQwen3 VL 235B A22B ThinkingQwen3 VL 235B A22B Thinking: Text, Images · MiniMax-M2: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightQwen3 VL 235B A22B ThinkingMiniMax-M2
Price50%4463
Inputs & features30%7035
Context window20%2432
Overall100%48/10048/100

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.

Qwen3 VL 235B A22B Thinking vs MiniMax-M2 specifications side by side
SpecificationQwen3 VL 235B A22B ThinkingAlibaba (Qwen)MiniMax-M2MiniMax
Capability
Capabilities Index (ECI)——
ECI rank——
Price per million tokens
Input$0.40$0.30 (best)
Output$4.00$1.20 (best)
Cached input——
Blended (3:1)$1.30$0.525 (best)
Long-context rateSame rateSame rate
Price sourceMedian of 9 providersOfficial MiniMax (minimax.io) API
Limits
Context window131,072 tokens204,800 tokens (best)
Max output32,768 tokens131,072 tokens (best)
Inputs and features
TextYesYes
ImagesYesNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningYesYes
Tool callingYesYes
Structured outputYesNo
Availability
WeightsOpenOpen
API model ID—MiniMax-M2
API providers913 (best)
ReleasedSep 23, 2025Oct 27, 2025
Knowledge cutoffMar 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.

  • Qwen3 VL 235B A22B Thinking$12.00
  • MiniMax-M2$5.40
04 — Questions

Which should you choose?

Which is better: Qwen3 VL 235B A22B Thinking or MiniMax-M2?

It is close. Our weighted score puts them within a point (MiniMax-M2 48/100, Qwen3 VL 235B A22B Thinking 48/100), so choose by what matters most for your work: MiniMax-M2 on price and MiniMax-M2 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, Qwen3 VL 235B A22B Thinking or MiniMax-M2?

MiniMax-M2 is cheaper at $0.30 input / $1.20 output per million tokens (official MiniMax (minimax.io) 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 $0.525 per million tokens for MiniMax-M2 versus $1.30 for Qwen3 VL 235B A22B Thinking (2.5× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. Qwen3 VL 235B A22B Thinking has not been scored yet and MiniMax-M2 has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen3 VL 235B A22B Thinking and MiniMax-M2 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?

MiniMax-M2 has the largest context window at 204,800 tokens, against 131,072 for Qwen3 VL 235B A22B Thinking. Maximum output per response: Qwen3 VL 235B A22B Thinking up to 32,768, MiniMax-M2 up to 131,072 tokens.

Which can read images, PDFs, audio or video?

Qwen3 VL 235B A22B Thinking accepts text and images; MiniMax-M2 accepts text. Qwen3 VL 235B A22B Thinking handles the widest range of inputs.

Are any of these open source?

Yes, both publish their weights, so you can self-host them.

Which is newer?

MiniMax-M2 is the newest, released Oct 27, 2025. Qwen3 VL 235B A22B Thinking came out Sep 23, 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 Oct 4, 2026.

05 — Keep comparing

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