ZMIME
Comparison · 2 models · Updated Oct 4, 2026

Qwen2.5 7B Instruct vs Mistral Large 2.1

Qwen2.5 7B Instruct comes out ahead, 44 to 38 on our weighted score, and it is the cheaper option too.

  1. Our pick

    Alibaba (Qwen)

    Qwen2.5 7B Instruct

    Released Sep 19, 2024

    44/100
    • ECI118.5
    • Price$0.175 / $0.70
    • Context131K
    Full specs Remove Qwen2.5 7B 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 7B Instruct is our pick

Qwen2.5 7B Instruct is the better all-round choice, scoring 44/100 against Mistral Large 2.1 (38). It leads on price. Mistral Large 2.1 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityMistral Large 2.1Capabilities Index (ECI): Mistral Large 2.1 128.5 · Qwen2.5 7B Instruct 118.5
  • Lowest priceQwen2.5 7B InstructQwen2.5 7B Instruct $0.306 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend)
  • Longest contextAbout the sameQwen2.5 7B Instruct 131,072 · Mistral Large 2.1 131,072 tokens
  • Widest inputsSame inputsQwen2.5 7B 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 7B InstructMistral Large 2.1
CapabilityCapabilities Index (ECI)50%3851
Price25%7427
Inputs & features15%2525
Context window10%2424
Overall100%44/10038/100
02 — Side by side

Every spec in one table

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

Qwen2.5 7B Instruct vs Mistral Large 2.1 specifications side by side
SpecificationQwen2.5 7B InstructAlibaba (Qwen)Mistral Large 2.1Mistral AI
Capability
Capabilities Index (ECI)118.5128.5 (best)
ECI rank#141 of 148#130 of 148 (best)
GPQA DiamondGraduate-level science questions35.5%51.3% (best)
OTIS Mock AIME 2024–2025Competition mathematics2.5%7.8% (best)
Price per million tokens
Input$0.175 (best)$2.00
Output$0.70 (best)$6.00
Cached input——
Blended (3:1)$0.306 (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 IDqwen2-5-7b-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 7B Instruct$3.15
  • Mistral Large 2.1$32.00
04 — Questions

Which should you choose?

Which is better: Qwen2.5 7B Instruct or Mistral Large 2.1?

Qwen2.5 7B Instruct is the better all-round choice, scoring 44/100 against Mistral Large 2.1 (38). It leads on price. Mistral Large 2.1 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Qwen2.5 7B Instruct or Mistral Large 2.1?

Qwen2.5 7B Instruct is cheaper at $0.175 input / $0.70 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 $0.306 per million tokens for Qwen2.5 7B Instruct versus $3.00 for Mistral Large 2.1 (9.8× as much).

Which scores higher on benchmarks?

Mistral Large 2.1 scores higher on the Capabilities Index (ECI): Mistral Large 2.1 128.5 (#130 of 148) and Qwen2.5 7B Instruct 118.5 (#141 of 148). Their confidence ranges do not overlap (123.8–130.8 vs 110.7–121.3), so the gap is a real one. On individual benchmarks: GPQA Diamond — Mistral Large 2.1 51.3%, Qwen2.5 7B Instruct 35.5%; OTIS Mock AIME 2024–2025 — Mistral Large 2.1 7.8%, Qwen2.5 7B Instruct 2.5%.

Which is better for coding?

There are no published SWE-bench Verified results for Qwen2.5 7B Instruct and Mistral Large 2.1 yet, so there is no like-for-like coding score. On overall capability, Mistral Large 2.1 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 7B Instruct and Mistral Large 2.1 share the same 131,072-token context window. Maximum output per response: Qwen2.5 7B Instruct up to 8,192, Mistral Large 2.1 up to 16,384 tokens.

Which can read images, PDFs, audio or video?

Qwen2.5 7B 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 7B Instruct came out Sep 19, 2024. Knowledge cutoff: Qwen2.5 7B 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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