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Comparison · 2 models · Updated Oct 4, 2026

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

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

  1. 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
  2. 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

  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 24BQwen2.5 72B Instruct: Text · Mistral Small 3.1 24B: Text, Images
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightQwen2.5 72B InstructMistral Small 3.1 24B
CapabilityCapabilities Index (ECI)50%5250
Price25%3176
Inputs & features15%2560
Context window10%2424
Overall100%40/10055/100
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 Small 3.1 24B specifications side by side
SpecificationQwen2.5 72B InstructAlibaba (Qwen)Mistral Small 3.1 24BMistral AI
Capability
Capabilities Index (ECI)129.0 (best)127.5
ECI rank#128 of 148 (best)#132 of 148
GPQA DiamondGraduate-level science questions49.2% (best)47.5%
OTIS Mock AIME 2024–2025Competition mathematics8.1% (best)5.8%
Price per million tokens
Input$1.40$0.229 (best)
Output$5.60$0.436 (best)
Cached input——
Blended (3:1)$2.45$0.281 (best)
Long-context rateSame rateSame rate
Price sourceOfficial Alibaba APIMedian of 2 providers
Limits
Context window131,072 tokens (best)128,000 tokens
Max output8,192 tokens16,384 tokens (best)
Inputs and features
TextYesYes
ImagesNoYes
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputNoYes
Availability
WeightsOpenOpen
API model IDqwen2-5-72b-instruct—
API providers12 (best)
ReleasedSep 19, 2024Mar 17, 2025
Knowledge cutoffApr 2024Jun 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 Small 3.1 24B$3.16
04 — Questions

Which should you choose?

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

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

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 Qwen2.5 72B Instruct and Mistral Small 3.1 24B 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: Qwen2.5 72B Instruct up to 8,192, Mistral Small 3.1 24B up to 16,384 tokens.

Which can read images, PDFs, audio or video?

Qwen2.5 72B Instruct accepts text; Mistral Small 3.1 24B accepts text and images. 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: Qwen2.5 72B Instruct Apr 2024, Mistral Small 3.1 24B Jun 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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