ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Llama-3.1-8B-Instruct vs Mistral Nemo vs Mistral Small 3.1 24B

Mistral Small 3.1 24B comes out ahead, 55 to 48 and 46 on our weighted score, though Mistral Nemo is 47% cheaper per token.

  1. Meta

    Llama-3.1-8B-Instruct

    Released Jul 23, 2024

    46/100
    • ECI116.6
    • Price$0.152 / $0.167
    • Context128K
    Full specs Remove Llama-3.1-8B-Instruct

  2. Mistral AI

    Mistral Nemo

    Released Jul 1, 2024

    48/100
    • ECI118.7
    • Price$0.15 / $0.15
    • Context128K
    Full specs Remove Mistral Nemo
  3. 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
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 Mistral Nemo (48) and Llama-3.1-8B-Instruct (46). It leads on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityMistral Small 3.1 24BCapabilities Index (ECI): Mistral Small 3.1 24B 127.5 · Mistral Nemo 118.7 · Llama-3.1-8B-Instruct 116.6
  • Lowest priceMistral NemoMistral Nemo $0.15 · Llama-3.1-8B-Instruct $0.156 · Mistral Small 3.1 24B $0.281 per 1M tokens (3:1 blend)
  • Longest contextAbout the sameLlama-3.1-8B-Instruct 128,000 · Mistral Nemo 128,000 · Mistral Small 3.1 24B 128,000 tokens
  • Widest inputsMistral Small 3.1 24BLlama-3.1-8B-Instruct: Text · Mistral Nemo: 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-3.1-8B-InstructMistral NemoMistral Small 3.1 24B
CapabilityCapabilities Index (ECI)50%363950
Price25%888976
Inputs & features15%252560
Context window10%242424
Overall100%46/10048/10055/100
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 Mistral Nemo vs Mistral Small 3.1 24B specifications side by side
SpecificationLlama-3.1-8B-InstructMetaMistral NemoMistral AIMistral Small 3.1 24BMistral AI
Capability
Capabilities Index (ECI)116.6118.7127.5 (best)
ECI rank#145 of 148#140 of 148#132 of 148 (best)
GPQA DiamondGraduate-level science questions27.0%29.9%47.5% (best)
OTIS Mock AIME 2024–2025Competition mathematics1.7%—5.8% (best)
Price per million tokens
Input$0.152$0.15 (best)$0.229
Output$0.167$0.15 (best)$0.436
Cached input———
Blended (3:1)$0.156$0.15 (best)$0.281
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 9 providersOfficial Mistral APIMedian of 2 providers
Limits
Context window128,000 tokens128,000 tokens128,000 tokens
Max output4,096 tokens128,000 tokens (best)16,384 tokens
Inputs and features
TextYesYesYes
ImagesNoNoYes
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputNoNoYes
Availability
WeightsOpenOpenOpen
API model ID—mistral-nemo—
API providers9 (best)52
ReleasedJul 23, 2024Jul 1, 2024Mar 17, 2025
Knowledge cutoffDec 2023Jul 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-3.1-8B-Instruct$1.85
  • Mistral Nemo$1.80
  • Mistral Small 3.1 24B$3.16
04 — Questions

Which should you choose?

Which is better: Llama-3.1-8B-Instruct, Mistral Nemo or Mistral Small 3.1 24B?

Mistral Small 3.1 24B is the better all-round choice, scoring 55/100 against Mistral Nemo (48) and Llama-3.1-8B-Instruct (46). It leads on capability and inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Llama-3.1-8B-Instruct, Mistral Nemo or Mistral Small 3.1 24B?

Mistral Nemo is cheaper at $0.15 input / $0.15 output per million tokens (official Mistral API price). Llama-3.1-8B-Instruct costs $0.152 input / $0.167 output per million tokens (median across 9 API providers); Mistral Small 3.1 24B costs $0.229 input / $0.436 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $0.15 per million tokens for Mistral Nemo versus $0.156 for Llama-3.1-8B-Instruct (1× as much) and $0.281 for Mistral Small 3.1 24B (1.9× as much).

Which scores higher on benchmarks?

Mistral Small 3.1 24B scores higher on the Capabilities Index (ECI): Mistral Small 3.1 24B 127.5 (#132 of 148), Mistral Nemo 118.7 (#140 of 148) and Llama-3.1-8B-Instruct 116.6 (#145 of 148). Their confidence ranges do not overlap (122.6–129.4 vs 111.3–121.5), so the gap is a real one. On individual benchmarks: GPQA Diamond — Mistral Small 3.1 24B 47.5%, Mistral Nemo 29.9%, Llama-3.1-8B-Instruct 27.0%.

Which is better for coding?

There are no published SWE-bench Verified results for Llama-3.1-8B-Instruct, Mistral Nemo and Mistral Small 3.1 24B yet, so there is no like-for-like coding score. On overall capability, Mistral Small 3.1 24B 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?

Llama-3.1-8B-Instruct, Mistral Nemo and Mistral Small 3.1 24B share the same 128,000-token context window. Maximum output per response: Llama-3.1-8B-Instruct up to 4,096, Mistral Nemo up to 128,000, Mistral Small 3.1 24B up to 16,384 tokens.

Which can read images, PDFs, audio or video?

Llama-3.1-8B-Instruct accepts text; Mistral Nemo 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, all three publish their weights, so you can self-host them.

Which is newer?

Mistral Small 3.1 24B is the newest, released Mar 17, 2025. Llama-3.1-8B-Instruct came out Jul 23, 2024; Mistral Nemo came out Jul 1, 2024. Knowledge cutoff: Llama-3.1-8B-Instruct Dec 2023, Mistral Nemo Jul 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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