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Comparison · 3 models · Updated Oct 4, 2026

Nova Pro vs Mistral Small 3.1 24B vs Qwen2.5 32B Instruct

Mistral Small 3.1 24B comes out ahead, 55 to 48 and 43 on our weighted score, and it is the cheaper option too.

  1. Amazon

    Nova Pro

    Released Dec 3, 2024

    48/100
    • ECI123.8
    • Price$0.80 / $3.20
    • Context300K
  2. Our pick

    Mistral AI

    Mistral Small 3.1 24B

    Released Mar 17, 2025

    55/100
    • ECI127.5
    • Price$0.229 / $0.436
    • Context128K
  3. Alibaba (Qwen)

    Qwen2.5 32B Instruct

    Released Sep 17, 2024

    43/100
    • ECI128.5
    • Price$0.70 / $2.80
    • Context131K
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 Nova Pro (48) and Qwen2.5 32B Instruct (43). It leads on price. Nova Pro wins on inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityQwen2.5 32B InstructCapabilities Index (ECI): Qwen2.5 32B Instruct 128.5 · Mistral Small 3.1 24B 127.5 · Nova Pro 123.8
  • Lowest priceMistral Small 3.1 24BMistral Small 3.1 24B $0.281 · Qwen2.5 32B Instruct $1.23 · Nova Pro $1.40 per 1M tokens (3:1 blend)
  • Longest contextNova ProNova Pro 300,000 · Qwen2.5 32B Instruct 131,072 · Mistral Small 3.1 24B 128,000 tokens
  • Widest inputsNova ProNova Pro: Text, Images, PDFs, Video · Mistral Small 3.1 24B: Text, Images · Qwen2.5 32B Instruct: Text
  • Self-hostingMistral Small 3.1 24B and Qwen2.5 32B InstructPublishes downloadable weights
How the score is built
MeasureWeightNova ProMistral Small 3.1 24BQwen2.5 32B Instruct
CapabilityCapabilities Index (ECI)50%455051
Price25%437646
Inputs & features15%706025
Context window10%392424
Overall100%48/10055/10043/100
02 — Side by side

Every spec in one table

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

Nova Pro vs Mistral Small 3.1 24B vs Qwen2.5 32B Instruct specifications side by side
SpecificationNova ProAmazonMistral Small 3.1 24BMistral AIQwen2.5 32B InstructAlibaba (Qwen)
Capability
Capabilities Index (ECI)123.8127.5128.5 (best)
ECI rank#137 of 148#132 of 148#131 of 148 (best)
GPQA DiamondGraduate-level science questions—47.5% (best)46.1%
OTIS Mock AIME 2024–2025Competition mathematics—5.8%7.4% (best)
Price per million tokens
Input$0.80$0.229 (best)$0.70
Output$3.20$0.436 (best)$2.80
Cached input$0.20——
Blended (3:1)$1.40$0.281 (best)$1.23
Long-context rateSame rateSame rateSame rate
Price sourceOfficial Amazon Bedrock APIMedian of 2 providersOfficial Alibaba API
Limits
Context window300,000 tokens (best)128,000 tokens131,072 tokens
Max output10,000 tokens16,384 tokens (best)8,192 tokens
Inputs and features
TextYesYesYes
ImagesYesYesNo
PDFsYesNoNo
AudioNoNoNo
VideoYesNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputNoYesNo
Availability
WeightsProprietaryOpenOpen
API model IDamazon.nova-pro-v1:0—qwen2-5-32b-instruct
API providers3 (best)21
ReleasedDec 3, 2024Mar 17, 2025Sep 17, 2024
Knowledge cutoffOct 2024Jun 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.

  • Nova Pro$14.40
  • Mistral Small 3.1 24B$3.16
  • Qwen2.5 32B Instruct$12.60
04 — Questions

Which should you choose?

Which is better: Nova Pro, Mistral Small 3.1 24B or Qwen2.5 32B Instruct?

Mistral Small 3.1 24B is the better all-round choice, scoring 55/100 against Nova Pro (48) and Qwen2.5 32B Instruct (43). It leads on price. Nova Pro wins on inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Nova Pro, Mistral Small 3.1 24B or Qwen2.5 32B 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 32B Instruct costs $0.70 input / $2.80 output per million tokens (official Alibaba API price); Nova Pro costs $0.80 input / $3.20 output per million tokens (official Amazon Bedrock 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 $1.23 for Qwen2.5 32B Instruct (4.4× as much) and $1.40 for Nova Pro (5× 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), Mistral Small 3.1 24B 127.5 (#132 of 148) and Nova Pro 123.8 (#137 of 148). The confidence ranges of the top two overlap (123.5–130.0 vs 122.6–129.4), so treat the gap as small.

Which is better for coding?

There are no published SWE-bench Verified results for Nova Pro, Mistral Small 3.1 24B and Qwen2.5 32B Instruct 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. All three support tool calling for agent workflows.

Which has the bigger context window?

Nova Pro has the largest context window at 300,000 tokens, against 131,072 for Qwen2.5 32B Instruct and 128,000 for Mistral Small 3.1 24B. Maximum output per response: Nova Pro up to 10,000, Mistral Small 3.1 24B up to 16,384, Qwen2.5 32B Instruct up to 8,192 tokens.

Which can read images, PDFs, audio or video?

Nova Pro accepts text, images, PDFs and video; Mistral Small 3.1 24B accepts text and images; Qwen2.5 32B Instruct accepts text. Nova Pro handles the widest range of inputs.

Are any of these open source?

Mistral Small 3.1 24B and Qwen2.5 32B Instruct publishes its weights and can be self-hosted; Nova Pro is proprietary.

Which is newer?

Mistral Small 3.1 24B is the newest, released Mar 17, 2025. Nova Pro came out Dec 3, 2024; Qwen2.5 32B Instruct came out Sep 17, 2024. Knowledge cutoff: Nova Pro Oct 2024, Mistral Small 3.1 24B Jun 2024, Qwen2.5 32B 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.