ZMIME
Comparison · 2 models · Updated Oct 4, 2026

Llama-3.2-1B vs Mistral Small 3.1 24B

Mistral Small 3.1 24B comes out ahead, 55 to 36 on our weighted score, though Llama-3.2-1B is 3.3× cheaper per token.

  1. Meta

    Llama-3.2-1B

    Released Sep 25, 2024

    36/100
    • ECI102.0
    • Price$0.064 / $0.15
    • Context131K
    Full specs Remove Llama-3.2-1B
  2. 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

  3. Add a model

    Make it a three-way comparison.

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 Llama-3.2-1B (36). It leads on capability and inputs & features. Llama-3.2-1B wins on price. 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 · Llama-3.2-1B 102.0
  • Lowest priceLlama-3.2-1BLlama-3.2-1B $0.085 · Mistral Small 3.1 24B $0.281 per 1M tokens (3:1 blend)
  • Longest contextLlama-3.2-1BLlama-3.2-1B 131,072 · Mistral Small 3.1 24B 128,000 tokens
  • Widest inputsMistral Small 3.1 24BLlama-3.2-1B: 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-3.2-1BMistral Small 3.1 24B
CapabilityCapabilities Index (ECI)50%1750
Price25%10076
Inputs & features15%060
Context window10%2424
Overall100%36/10055/100
02 — Side by side

Every spec in one table

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

Llama-3.2-1B vs Mistral Small 3.1 24B specifications side by side
SpecificationLlama-3.2-1BMetaMistral Small 3.1 24BMistral AI
Capability
Capabilities Index (ECI)102.0127.5 (best)
ECI rank#147 of 148#132 of 148 (best)
GPQA DiamondGraduate-level science questions23.9%47.5% (best)
OTIS Mock AIME 2024–2025Competition mathematics0.6%5.8% (best)
Price per million tokens
Input$0.064 (best)$0.229
Output$0.15 (best)$0.436
Cached input——
Blended (3:1)$0.085 (best)$0.281
Long-context rateSame rateSame rate
Price sourceMedian of 2 providersMedian of 2 providers
Limits
Context window131,072 tokens (best)128,000 tokens
Max output8,192 tokens16,384 tokens (best)
Inputs and features
TextYesYes
ImagesNoYes
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingNoYes
Structured outputNoYes
Availability
WeightsOpenLlama 3.2 Community LicenseOpen
API model ID——
API providers22
ReleasedSep 25, 2024Mar 17, 2025
Knowledge cutoffDec 2023Jun 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-3.2-1B$0.936
  • Mistral Small 3.1 24B$3.16
04 — Questions

Which should you choose?

Which is better: Llama-3.2-1B or Mistral Small 3.1 24B?

Mistral Small 3.1 24B is the better all-round choice, scoring 55/100 against Llama-3.2-1B (36). It leads on capability and inputs & features. Llama-3.2-1B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, Llama-3.2-1B or Mistral Small 3.1 24B?

Llama-3.2-1B is cheaper at $0.064 input / $0.15 output per million tokens (median across 2 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 $0.085 per million tokens for Llama-3.2-1B versus $0.281 for Mistral Small 3.1 24B (3.3× 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) and Llama-3.2-1B 102.0 (#147 of 148). Their confidence ranges do not overlap (122.6–129.4 vs 90.7–110.3), so the gap is a real one. On individual benchmarks: GPQA Diamond — Mistral Small 3.1 24B 47.5%, Llama-3.2-1B 23.9%; OTIS Mock AIME 2024–2025 — Mistral Small 3.1 24B 5.8%, Llama-3.2-1B 0.6%.

Which is better for coding?

There are no published SWE-bench Verified results for Llama-3.2-1B 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. Note that Llama-3.2-1B does not support tool calling, which most coding agents need.

Which has the bigger context window?

Llama-3.2-1B has the largest context window at 131,072 tokens, against 128,000 for Mistral Small 3.1 24B. Maximum output per response: Llama-3.2-1B up to 8,192, Mistral Small 3.1 24B up to 16,384 tokens.

Which can read images, PDFs, audio or video?

Llama-3.2-1B 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, both publish their weights (Llama 3.2 Community License), so you can self-host them.

Which is newer?

Mistral Small 3.1 24B is the newest, released Mar 17, 2025. Llama-3.2-1B came out Sep 25, 2024. Knowledge cutoff: Llama-3.2-1B Dec 2023, 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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