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Comparison · 2 models · Updated Nov 2, 2026

Llama-3.1-8B-Instruct vs Voxtral Small 24B 2507

Llama-3.1-8B-Instruct comes out ahead, 62 to 55 on our weighted score, and it is the cheaper option too.

  1. Our pick

    Meta

    Llama-3.1-8B-Instruct

    Released Jul 23, 2024

    62/100
    • ECI116.4
    • Price$0.06 / $0.08
    • Context128K
    Full specs Remove Llama-3.1-8B-Instruct

  2. Mistral AI

    Voxtral Small 24B 2507

    Released Jul 15, 2025

    55/100
    • ECI—
    • Price$0.10 / $0.40
    • Context33K
    Full specs Remove Voxtral Small 24B 2507

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Llama-3.1-8B-Instruct is our pick

Llama-3.1-8B-Instruct is the better all-round choice, scoring 62/100 against Voxtral Small 24B 2507 (55). It leads on price and context window. Voxtral Small 24B 2507 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 priceLlama-3.1-8B-InstructLlama-3.1-8B-Instruct $0.065 · Voxtral Small 24B 2507 $0.175 per 1M tokens (3:1 blend)
  • Longest contextLlama-3.1-8B-InstructLlama-3.1-8B-Instruct 128,000 · Voxtral Small 24B 2507 32,768 tokens
  • Widest inputsVoxtral Small 24B 2507Llama-3.1-8B-Instruct: Text · Voxtral Small 24B 2507: Text, Audio
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightLlama-3.1-8B-InstructVoxtral Small 24B 2507
Price50%10082
Inputs & features30%2545
Context window20%240
Overall100%62/10055/100

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-3.1-8B-Instruct vs Voxtral Small 24B 2507 specifications side by side
SpecificationLlama-3.1-8B-InstructMetaVoxtral Small 24B 2507Mistral AI
Capability
Capabilities Index (ECI)116.4—
ECI rank#162 of 165—
GPQA DiamondGraduate-level science questions27.0%—
OTIS Mock AIME 2024–2025Competition mathematics1.7%—
Price per million tokens
Input$0.06 (best)$0.10
Output$0.08 (best)$0.40
Cached input——
Blended (3:1)$0.065 (best)$0.175
Long-context rateSame rateSame rate
Price sourceMedian of 17 providersOfficial Mistral API
Limits
Context window128,000 tokens (best)32,768 tokens
Max output4,096 tokens32,768 tokens (best)
Inputs and features
TextYesYes
ImagesNoNo
PDFsNoNo
AudioNoYes
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputNoYes
Availability
WeightsOpenOpenApache 2.0
API model ID—voxtral-small-latest
API providers18 (best)10
ReleasedJul 23, 2024Jul 15, 2025
Knowledge cutoffDec 2023—
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-3.1-8B-Instruct$0.76
  • Voxtral Small 24B 2507$1.80
04 — Questions

Which should you choose?

Which is better: Llama-3.1-8B-Instruct or Voxtral Small 24B 2507?

Llama-3.1-8B-Instruct is the better all-round choice, scoring 62/100 against Voxtral Small 24B 2507 (55). It leads on price and context window. Voxtral Small 24B 2507 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-3.1-8B-Instruct or Voxtral Small 24B 2507?

Llama-3.1-8B-Instruct is cheaper at $0.06 input / $0.08 output per million tokens (median across 17 API providers). Voxtral Small 24B 2507 costs $0.10 input / $0.40 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.065 per million tokens for Llama-3.1-8B-Instruct versus $0.175 for Voxtral Small 24B 2507 (2.7× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. Llama-3.1-8B-Instruct has an ECI of 116.4 and Voxtral Small 24B 2507 has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Llama-3.1-8B-Instruct and Voxtral Small 24B 2507 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.

Which has the bigger context window?

Llama-3.1-8B-Instruct has the largest context window at 128,000 tokens, against 32,768 for Voxtral Small 24B 2507. Maximum output per response: Llama-3.1-8B-Instruct up to 4,096, Voxtral Small 24B 2507 up to 32,768 tokens.

Which can read images, PDFs, audio or video?

Llama-3.1-8B-Instruct accepts text; Voxtral Small 24B 2507 accepts text and audio. Voxtral Small 24B 2507 handles the widest range of inputs.

Are any of these open source?

Yes, both publish their weights (Apache 2.0), so you can self-host them.

Which is newer?

Voxtral Small 24B 2507 is the newest, released Jul 15, 2025. Llama-3.1-8B-Instruct came out Jul 23, 2024. Knowledge cutoff: Llama-3.1-8B-Instruct Dec 2023.

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 Nov 2, 2026.

05 — Keep comparing

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