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Comparison · 2 models · Updated Oct 4, 2026

Qwen2.5 32B Instruct vs Mistral Large 2.1

Qwen2.5 32B Instruct comes out ahead, 43 to 38 on our weighted score, and it is the cheaper option too.

  1. Our pick

    Alibaba (Qwen)

    Qwen2.5 32B Instruct

    Released Sep 17, 2024

    43/100
    • ECI128.5
    • Price$0.70 / $2.80
    • Context131K
    Full specs Remove Qwen2.5 32B Instruct

  2. Mistral AI

    Mistral Large 2.1

    Released Nov 18, 2024

    38/100
    • ECI128.5
    • Price$2.00 / $6.00
    • Context131K
    Full specs Remove Mistral Large 2.1

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Qwen2.5 32B Instruct is our pick

Qwen2.5 32B Instruct is the better all-round choice, scoring 43/100 against Mistral Large 2.1 (38). It leads on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityTieCapabilities Index (ECI): Qwen2.5 32B Instruct 128.5 · Mistral Large 2.1 128.5
  • Lowest priceQwen2.5 32B InstructQwen2.5 32B Instruct $1.23 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend)
  • Longest contextAbout the sameQwen2.5 32B Instruct 131,072 · Mistral Large 2.1 131,072 tokens
  • Widest inputsSame inputsQwen2.5 32B Instruct: Text · Mistral Large 2.1: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightQwen2.5 32B InstructMistral Large 2.1
CapabilityCapabilities Index (ECI)50%5151
Price25%4627
Inputs & features15%2525
Context window10%2424
Overall100%43/10038/100
02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Qwen2.5 32B Instruct vs Mistral Large 2.1 specifications side by side
SpecificationQwen2.5 32B InstructAlibaba (Qwen)Mistral Large 2.1Mistral AI
Capability
Capabilities Index (ECI)128.5128.5
ECI rank#131 of 148#130 of 148 (best)
GPQA DiamondGraduate-level science questions46.1%51.3% (best)
OTIS Mock AIME 2024–2025Competition mathematics7.4%7.8% (best)
Price per million tokens
Input$0.70 (best)$2.00
Output$2.80 (best)$6.00
Cached input——
Blended (3:1)$1.23 (best)$3.00
Long-context rateSame rateSame rate
Price sourceOfficial Alibaba APIOfficial Mistral API
Limits
Context window131,072 tokens131,072 tokens
Max output8,192 tokens16,384 tokens (best)
Inputs and features
TextYesYes
ImagesNoNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenOpen
API model IDqwen2-5-32b-instructmistral-large-2411
API providers12 (best)
ReleasedSep 17, 2024Nov 18, 2024
Knowledge cutoffApr 2024Nov 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.

  • Qwen2.5 32B Instruct$12.60
  • Mistral Large 2.1$32.00
04 — Questions

Which should you choose?

Which is better: Qwen2.5 32B Instruct or Mistral Large 2.1?

Qwen2.5 32B Instruct is the better all-round choice, scoring 43/100 against Mistral Large 2.1 (38). It leads on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Qwen2.5 32B Instruct or Mistral Large 2.1?

Qwen2.5 32B Instruct is cheaper at $0.70 input / $2.80 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 $1.23 per million tokens for Qwen2.5 32B Instruct versus $3.00 for Mistral Large 2.1 (2.4× as much).

Which scores higher on benchmarks?

Qwen2.5 32B Instruct scores higher on the Capabilities Index (ECI): Qwen2.5 32B Instruct 128.5 (#131 of 148) and Mistral Large 2.1 128.5 (#130 of 148). The confidence ranges of the top two overlap (123.5–130.0 vs 123.8–130.8), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 2.1 51.3%, Qwen2.5 32B Instruct 46.1%; OTIS Mock AIME 2024–2025 — Mistral Large 2.1 7.8%, Qwen2.5 32B Instruct 7.4%.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen2.5 32B Instruct and Mistral Large 2.1 yet, so there is no like-for-like coding score. On overall capability, Qwen2.5 32B Instruct leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

Which has the bigger context window?

Qwen2.5 32B Instruct and Mistral Large 2.1 share the same 131,072-token context window. Maximum output per response: Qwen2.5 32B Instruct up to 8,192, Mistral Large 2.1 up to 16,384 tokens.

Which can read images, PDFs, audio or video?

Qwen2.5 32B Instruct accepts text; Mistral Large 2.1 accepts text. They handle the same number of input types.

Are any of these open source?

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

Which is newer?

Mistral Large 2.1 is the newest, released Nov 18, 2024. Qwen2.5 32B Instruct came out Sep 17, 2024. Knowledge cutoff: Qwen2.5 32B Instruct Apr 2024, Mistral Large 2.1 Nov 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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