ZMIME
Comparison · 2 models · Updated Oct 4, 2026

Qwen2.5 72B Instruct vs Mistral Large 2.1

Too close to call on our weighted score (Qwen2.5 72B Instruct 40, Mistral Large 2.1 38). The right pick depends on what you value most.

  1. Alibaba (Qwen)

    Qwen2.5 72B Instruct

    Released Sep 19, 2024

    40/100
    • ECI129.0
    • Price$1.40 / $5.60
    • Context131K
  2. Mistral AI

    Mistral Large 2.1

    Released Nov 18, 2024

    38/100
    • ECI128.5
    • Price$2.00 / $6.00
    • Context131K
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01 — Verdict

Too close to call

It is close. Our weighted score puts them within 1 points (Qwen2.5 72B Instruct 40/100, Mistral Large 2.1 38/100), so choose by what matters most for your work: Qwen2.5 72B Instruct for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityQwen2.5 72B InstructCapabilities Index (ECI): Qwen2.5 72B Instruct 129.0 · Mistral Large 2.1 128.5
  • Lowest priceQwen2.5 72B InstructQwen2.5 72B Instruct $2.45 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend)
  • Longest contextAbout the sameQwen2.5 72B Instruct 131,072 · Mistral Large 2.1 131,072 tokens
  • Widest inputsSame inputsQwen2.5 72B 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 72B InstructMistral Large 2.1
CapabilityCapabilities Index (ECI)50%5251
Price25%3127
Inputs & features15%2525
Context window10%2424
Overall100%40/10038/100
02 — Side by side

Every spec in one table

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

Qwen2.5 72B Instruct vs Mistral Large 2.1 specifications side by side
SpecificationQwen2.5 72B InstructAlibaba (Qwen)Mistral Large 2.1Mistral AI
Capability
Capabilities Index (ECI)129.0 (best)128.5
ECI rank#128 of 148 (best)#130 of 148
GPQA DiamondGraduate-level science questions49.2%51.3% (best)
OTIS Mock AIME 2024–2025Competition mathematics8.1% (best)7.8%
Price per million tokens
Input$1.40 (best)$2.00
Output$5.60 (best)$6.00
Cached input——
Blended (3:1)$2.45 (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 IDqwen2-5-72b-instructmistral-large-2411
API providers12 (best)
ReleasedSep 19, 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 72B Instruct$25.20
  • Mistral Large 2.1$32.00
04 — Questions

Which should you choose?

Which is better: Qwen2.5 72B Instruct or Mistral Large 2.1?

It is close. Our weighted score puts them within 1 points (Qwen2.5 72B Instruct 40/100, Mistral Large 2.1 38/100), so choose by what matters most for your work: Qwen2.5 72B Instruct for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Qwen2.5 72B Instruct or Mistral Large 2.1?

Qwen2.5 72B Instruct is cheaper at $1.40 input / $5.60 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 $2.45 per million tokens for Qwen2.5 72B Instruct versus $3.00 for Mistral Large 2.1 (1.2× as much).

Which scores higher on benchmarks?

Qwen2.5 72B Instruct scores higher on the Capabilities Index (ECI): Qwen2.5 72B Instruct 129.0 (#128 of 148) and Mistral Large 2.1 128.5 (#130 of 148). The confidence ranges of the top two overlap (123.8–130.7 vs 123.8–130.8), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Large 2.1 51.3%, Qwen2.5 72B Instruct 49.2%; OTIS Mock AIME 2024–2025 — Qwen2.5 72B Instruct 8.1%, Mistral Large 2.1 7.8%.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen2.5 72B Instruct and Mistral Large 2.1 yet, so there is no like-for-like coding score. On overall capability, Qwen2.5 72B 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 72B Instruct and Mistral Large 2.1 share the same 131,072-token context window. Maximum output per response: Qwen2.5 72B Instruct up to 8,192, Mistral Large 2.1 up to 16,384 tokens.

Which can read images, PDFs, audio or video?

Qwen2.5 72B 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 72B Instruct came out Sep 19, 2024. Knowledge cutoff: Qwen2.5 72B 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.