ZMIME
Comparison · 2 models · Updated Oct 4, 2026

Mistral Small 3.1 24B vs Llama 4 Scout 17B Instruct

Llama 4 Scout 17B Instruct comes out ahead, 62 to 55 on our weighted score, though Mistral Small 3.1 24B is 18% cheaper per token.

  1. 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. Our pick

    Meta

    Llama 4 Scout 17B Instruct

    Released Apr 5, 2025

    62/100
    • ECI129.7
    • Price$0.225 / $0.69
    • Context10M
    Full specs Remove Llama 4 Scout 17B Instruct

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Llama 4 Scout 17B Instruct is our pick

Llama 4 Scout 17B Instruct is the better all-round choice, scoring 62/100 against Mistral Small 3.1 24B (55). It leads on capability and context window. Mistral Small 3.1 24B wins on price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityLlama 4 Scout 17B InstructCapabilities Index (ECI): Llama 4 Scout 17B Instruct 129.7 · Mistral Small 3.1 24B 127.5
  • Lowest priceMistral Small 3.1 24BMistral Small 3.1 24B $0.281 · Llama 4 Scout 17B Instruct $0.341 per 1M tokens (3:1 blend)
  • Longest contextLlama 4 Scout 17B InstructLlama 4 Scout 17B Instruct 10,000,000 · Mistral Small 3.1 24B 128,000 tokens
  • Widest inputsSame inputsMistral Small 3.1 24B: Text, Images · Llama 4 Scout 17B Instruct: Text, Images
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightMistral Small 3.1 24BLlama 4 Scout 17B Instruct
CapabilityCapabilities Index (ECI)50%5052
Price25%7672
Inputs & features15%6050
Context window10%24100
Overall100%55/10062/100
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 Llama 4 Scout 17B Instruct specifications side by side
SpecificationMistral Small 3.1 24BMistral AILlama 4 Scout 17B InstructMeta
Capability
Capabilities Index (ECI)127.5129.7 (best)
ECI rank#132 of 148#126 of 148 (best)
GPQA DiamondGraduate-level science questions47.5%51.8% (best)
OTIS Mock AIME 2024–2025Competition mathematics5.8%7.8% (best)
Price per million tokens
Input$0.229$0.225 (best)
Output$0.436 (best)$0.69
Cached input——
Blended (3:1)$0.281 (best)$0.341
Long-context rateSame rateSame rate
Price sourceMedian of 2 providersMedian of 4 providers
Limits
Context window128,000 tokens10,000,000 tokens (best)
Max output16,384 tokens16,384 tokens
Inputs and features
TextYesYes
ImagesYesYes
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputYesNo
Availability
WeightsOpenOpen
API model ID——
API providers24 (best)
ReleasedMar 17, 2025Apr 5, 2025
Knowledge cutoffJun 2024Aug 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
  • Llama 4 Scout 17B Instruct$3.63
04 — Questions

Which should you choose?

Which is better: Mistral Small 3.1 24B or Llama 4 Scout 17B Instruct?

Llama 4 Scout 17B Instruct is the better all-round choice, scoring 62/100 against Mistral Small 3.1 24B (55). It leads on capability and context window. Mistral Small 3.1 24B wins on price and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Mistral Small 3.1 24B or Llama 4 Scout 17B Instruct?

Mistral Small 3.1 24B is cheaper at $0.229 input / $0.436 output per million tokens (median across 2 API providers). Llama 4 Scout 17B Instruct costs $0.225 input / $0.69 output per million tokens (median across 4 API providers). 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 $0.341 for Llama 4 Scout 17B Instruct (1.2× as much).

Which scores higher on benchmarks?

Llama 4 Scout 17B Instruct scores higher on the Capabilities Index (ECI): Llama 4 Scout 17B Instruct 129.7 (#126 of 148) and Mistral Small 3.1 24B 127.5 (#132 of 148). The confidence ranges of the top two overlap (124.8–131.4 vs 122.6–129.4), so treat the gap as small. On individual benchmarks: GPQA Diamond — Llama 4 Scout 17B Instruct 51.8%, Mistral Small 3.1 24B 47.5%; OTIS Mock AIME 2024–2025 — Llama 4 Scout 17B Instruct 7.8%, 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 Llama 4 Scout 17B Instruct yet, so there is no like-for-like coding score. On overall capability, Llama 4 Scout 17B 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?

Llama 4 Scout 17B Instruct has the largest context window at 10,000,000 tokens, against 128,000 for Mistral Small 3.1 24B. Maximum output per response: Mistral Small 3.1 24B up to 16,384, Llama 4 Scout 17B Instruct up to 16,384 tokens.

Which can read images, PDFs, audio or video?

Mistral Small 3.1 24B accepts text and images; Llama 4 Scout 17B Instruct accepts text and images. 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?

Llama 4 Scout 17B Instruct is the newest, released Apr 5, 2025. Mistral Small 3.1 24B came out Mar 17, 2025. Knowledge cutoff: Mistral Small 3.1 24B Jun 2024, Llama 4 Scout 17B Instruct Aug 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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