ZMIME
Comparison · 3 models · Updated Oct 4, 2026

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

Llama 4 Scout 17B Instruct comes out ahead, 71 to 61 and 51 on our weighted score, though Command R is 23% cheaper per token.

  1. Our pick

    Meta

    Llama 4 Scout 17B Instruct

    Released Apr 5, 2025

    71/100
    • ECI129.7
    • Price$0.225 / $0.69
    • Context10M
    Full specs Remove Llama 4 Scout 17B Instruct

  2. Cohere

    Command R

    Released Aug 30, 2024

    51/100
    • ECI—
    • Price$0.15 / $0.60
    • Context128K
    Full specs Remove Command R

  3. Mistral AI

    Mistral Small 3.1 24B

    Released Mar 17, 2025

    61/100
    • ECI127.5
    • Price$0.229 / $0.436
    • Context128K
    Full specs Remove Mistral Small 3.1 24B
01 — Verdict

Llama 4 Scout 17B Instruct is our pick

Llama 4 Scout 17B Instruct is the better all-round choice, scoring 71/100 against Mistral Small 3.1 24B (61) and Command R (51). It leads on context window. Mistral Small 3.1 24B wins on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

  • CapabilityNot enough dataNo independent benchmark covers every model here yet
  • Lowest priceCommand RCommand R $0.263 · Mistral 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 · Command R 128,000 · Mistral Small 3.1 24B 128,000 tokens
  • Widest inputsLlama 4 Scout 17B Instruct and Mistral Small 3.1 24BLlama 4 Scout 17B Instruct: Text, Images · Command R: 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
MeasureWeightLlama 4 Scout 17B InstructCommand RMistral Small 3.1 24B
Price50%727776
Inputs & features30%502560
Context window20%1002424
Overall100%71/10051/10061/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

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

Llama 4 Scout 17B Instruct vs Command R vs Mistral Small 3.1 24B specifications side by side
SpecificationLlama 4 Scout 17B InstructMetaCommand RCohereMistral Small 3.1 24BMistral AI
Capability
Capabilities Index (ECI)129.7 (best)—127.5
ECI rank#126 of 148 (best)—#132 of 148
GPQA DiamondGraduate-level science questions51.8% (best)—47.5%
OTIS Mock AIME 2024–2025Competition mathematics7.8% (best)—5.8%
Price per million tokens
Input$0.225$0.15 (best)$0.229
Output$0.69$0.60$0.436 (best)
Cached input———
Blended (3:1)$0.341$0.263 (best)$0.281
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 4 providersOfficial Cohere APIMedian of 2 providers
Limits
Context window10,000,000 tokens (best)128,000 tokens128,000 tokens
Max output16,384 tokens (best)4,000 tokens16,384 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesNoYes
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputNoNoYes
Availability
WeightsOpenOpenOpen
API model ID—command-r-08-2024—
API providers45 (best)2
ReleasedApr 5, 2025Aug 30, 2024Mar 17, 2025
Knowledge cutoffAug 2024Jun 1, 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.

  • Llama 4 Scout 17B Instruct$3.63
  • Command R$2.70
  • Mistral Small 3.1 24B$3.16
04 — Questions

Which should you choose?

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

Llama 4 Scout 17B Instruct is the better all-round choice, scoring 71/100 against Mistral Small 3.1 24B (61) and Command R (51). It leads on context window. Mistral Small 3.1 24B wins on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

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

Command R is cheaper at $0.15 input / $0.60 output per million tokens (official Cohere API price). Mistral Small 3.1 24B costs $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 $0.263 per million tokens for Command R versus $0.281 for Mistral Small 3.1 24B (1.1× as much) and $0.341 for Llama 4 Scout 17B Instruct (1.3× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Llama 4 Scout 17B Instruct has an ECI of 129.7, Command R has not been scored yet and Mistral Small 3.1 24B has an ECI of 127.5.

Which is better for coding?

There are no published SWE-bench Verified results for Llama 4 Scout 17B Instruct, Command R and Mistral Small 3.1 24B yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three 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 Command R and 128,000 for Mistral Small 3.1 24B. Maximum output per response: Llama 4 Scout 17B Instruct up to 16,384, Command R up to 4,000, Mistral Small 3.1 24B up to 16,384 tokens.

Which can read images, PDFs, audio or video?

Llama 4 Scout 17B Instruct accepts text and images; Command R accepts text; Mistral Small 3.1 24B accepts text and images. Llama 4 Scout 17B Instruct handles the widest range of inputs.

Are any of these open source?

Yes, all three 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; Command R came out Aug 30, 2024. Knowledge cutoff: Llama 4 Scout 17B Instruct Aug 2024, Command R Jun 1, 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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