ZMIME
Comparison · 2 models · Updated Oct 4, 2026

Mistral Large 2.1 vs Qwen Max

Mistral Large 2.1 comes out ahead, 26 to 22 on our weighted score, though Qwen Max is 7% cheaper per token.

  1. Our pick

    Mistral AI

    Mistral Large 2.1

    Released Nov 18, 2024

    26/100
    • ECI128.5
    • Price$2.00 / $6.00
    • Context131K
    Full specs Remove Mistral Large 2.1

  2. Alibaba (Qwen)

    Qwen Max

    Released Apr 3, 2024

    22/100
    • ECI—
    • Price$1.60 / $6.40
    • Context33K
    Full specs Remove Qwen Max

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Mistral Large 2.1 is our pick

Mistral Large 2.1 is the better all-round choice, scoring 26/100 against Qwen Max (22). It leads 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 priceQwen MaxQwen Max $2.80 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend)
  • Longest contextMistral Large 2.1Mistral Large 2.1 131,072 · Qwen Max 32,768 tokens
  • Widest inputsSame inputsMistral Large 2.1: Text · Qwen Max: Text
  • Self-hostingMistral Large 2.1Publishes downloadable weights
How the score is built
MeasureWeightMistral Large 2.1Qwen Max
Price50%2729
Inputs & features30%2525
Context window20%240
Overall100%26/10022/100

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 Large 2.1 vs Qwen Max specifications side by side
SpecificationMistral Large 2.1Mistral AIQwen MaxAlibaba (Qwen)
Capability
Capabilities Index (ECI)128.5—
ECI rank#130 of 148—
GPQA DiamondGraduate-level science questions51.3%—
OTIS Mock AIME 2024–2025Competition mathematics7.8%—
Price per million tokens
Input$2.00$1.60 (best)
Output$6.00 (best)$6.40
Cached input——
Blended (3:1)$3.00$2.80 (best)
Long-context rateSame rateSame rate
Price sourceOfficial Mistral APIOfficial Alibaba API
Limits
Context window131,072 tokens (best)32,768 tokens
Max output16,384 tokens (best)8,192 tokens
Inputs and features
TextYesYes
ImagesNoNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenProprietary
API model IDmistral-large-2411qwen-max
API providers26 (best)
ReleasedNov 18, 2024Apr 3, 2024
Knowledge cutoffNov 2024Apr 2024
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 Large 2.1$32.00
  • Qwen Max$28.80
04 — Questions

Which should you choose?

Which is better: Mistral Large 2.1 or Qwen Max?

Mistral Large 2.1 is the better all-round choice, scoring 26/100 against Qwen Max (22). It leads 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, Mistral Large 2.1 or Qwen Max?

Qwen Max is cheaper at $1.60 input / $6.40 output per million tokens (official Alibaba API price). Mistral Large 2.1 costs $2.00 input / $6.00 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $2.80 per million tokens for Qwen Max versus $3.00 for Mistral Large 2.1 (1.1× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. Mistral Large 2.1 has an ECI of 128.5 and Qwen Max has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Mistral Large 2.1 and Qwen Max 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 Large 2.1 has the largest context window at 131,072 tokens, against 32,768 for Qwen Max. Maximum output per response: Mistral Large 2.1 up to 16,384, Qwen Max up to 8,192 tokens.

Which can read images, PDFs, audio or video?

Mistral Large 2.1 accepts text; Qwen Max accepts text. They handle the same number of input types.

Are any of these open source?

Mistral Large 2.1 publishes its weights and can be self-hosted; Qwen Max is proprietary.

Which is newer?

Mistral Large 2.1 is the newest, released Nov 18, 2024. Qwen Max came out Apr 3, 2024. Knowledge cutoff: Mistral Large 2.1 Nov 2024, Qwen Max Apr 2024.

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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