ZMIME
Comparison · 2 models · Updated Oct 4, 2026

Mistral Small 3.1 24B vs Qwen2.5 72B Instruct

Mistral Small 3.1 24B comes out ahead, 55 to 40 on our weighted score, and it is the cheaper option too.

  1. Our pick

    Mistral AI

    Mistral Small 3.1 24B

    Released Mar 17, 2025

    55/100
    • ECI127.5
    • Price$0.229 / $0.436
    • Context128K
    Full specs Remove Mistral Small 3.1 24B

  2. Alibaba (Qwen)

    Qwen2.5 72B Instruct

    Released Sep 19, 2024

    40/100
    • ECI129.0
    • Price$1.40 / $5.60
    • Context131K
    Full specs Remove Qwen2.5 72B Instruct

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Mistral Small 3.1 24B is our pick

Mistral Small 3.1 24B is the better all-round choice, scoring 55/100 against Qwen2.5 72B Instruct (40). It leads on price and inputs & features. Qwen2.5 72B Instruct wins on 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 Small 3.1 24B 127.5
  • Lowest priceMistral Small 3.1 24BMistral Small 3.1 24B $0.281 · Qwen2.5 72B Instruct $2.45 per 1M tokens (3:1 blend)
  • Longest contextQwen2.5 72B InstructQwen2.5 72B Instruct 131,072 · Mistral Small 3.1 24B 128,000 tokens
  • Widest inputsMistral Small 3.1 24BMistral Small 3.1 24B: Text, Images · Qwen2.5 72B Instruct: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightMistral Small 3.1 24BQwen2.5 72B Instruct
CapabilityCapabilities Index (ECI)50%5052
Price25%7631
Inputs & features15%6025
Context window10%2424
Overall100%55/10040/100
02 — Side by side

Every spec in one table

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

Mistral Small 3.1 24B vs Qwen2.5 72B Instruct specifications side by side
SpecificationMistral Small 3.1 24BMistral AIQwen2.5 72B InstructAlibaba (Qwen)
Capability
Capabilities Index (ECI)127.5129.0 (best)
ECI rank#132 of 148#128 of 148 (best)
GPQA DiamondGraduate-level science questions47.5%49.2% (best)
OTIS Mock AIME 2024–2025Competition mathematics5.8%8.1% (best)
Price per million tokens
Input$0.229 (best)$1.40
Output$0.436 (best)$5.60
Cached input——
Blended (3:1)$0.281 (best)$2.45
Long-context rateSame rateSame rate
Price sourceMedian of 2 providersOfficial Alibaba API
Limits
Context window128,000 tokens131,072 tokens (best)
Max output16,384 tokens (best)8,192 tokens
Inputs and features
TextYesYes
ImagesYesNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputYesNo
Availability
WeightsOpenOpen
API model ID—qwen2-5-72b-instruct
API providers2 (best)1
ReleasedMar 17, 2025Sep 19, 2024
Knowledge cutoffJun 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 Small 3.1 24B$3.16
  • Qwen2.5 72B Instruct$25.20
04 — Questions

Which should you choose?

Which is better: Mistral Small 3.1 24B or Qwen2.5 72B Instruct?

Mistral Small 3.1 24B is the better all-round choice, scoring 55/100 against Qwen2.5 72B Instruct (40). It leads on price and inputs & features. Qwen2.5 72B Instruct wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Mistral Small 3.1 24B or Qwen2.5 72B Instruct?

Mistral Small 3.1 24B is cheaper at $0.229 input / $0.436 output per million tokens (median across 2 API providers). Qwen2.5 72B Instruct costs $1.40 input / $5.60 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.281 per million tokens for Mistral Small 3.1 24B versus $2.45 for Qwen2.5 72B Instruct (8.7× 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 Small 3.1 24B 127.5 (#132 of 148). The confidence ranges of the top two overlap (123.8–130.7 vs 122.6–129.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — Qwen2.5 72B Instruct 49.2%, Mistral Small 3.1 24B 47.5%; OTIS Mock AIME 2024–2025 — Qwen2.5 72B Instruct 8.1%, Mistral Small 3.1 24B 5.8%.

Which is better for coding?

There are no published SWE-bench Verified results for Mistral Small 3.1 24B and Qwen2.5 72B Instruct 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 has the largest context window at 131,072 tokens, against 128,000 for Mistral Small 3.1 24B. Maximum output per response: Mistral Small 3.1 24B up to 16,384, Qwen2.5 72B Instruct up to 8,192 tokens.

Which can read images, PDFs, audio or video?

Mistral Small 3.1 24B accepts text and images; Qwen2.5 72B Instruct accepts text. Mistral Small 3.1 24B 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?

Mistral Small 3.1 24B is the newest, released Mar 17, 2025. Qwen2.5 72B Instruct came out Sep 19, 2024. Knowledge cutoff: Mistral Small 3.1 24B Jun 2024, Qwen2.5 72B Instruct 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

Related comparisons