ZMIME
Comparison · 2 models · Updated Oct 4, 2026

Mistral Small 3.1 24B vs Llama-3.3-70B-Instruct

Mistral Small 3.1 24B comes out ahead, 55 to 46 on our weighted score, and it is the cheaper option too.

  1. 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

  2. Meta

    Llama-3.3-70B-Instruct

    Released Dec 6, 2024

    46/100
    • ECI127.3
    • Price$0.59 / $0.724
    • Context128K
    Full specs Remove Llama-3.3-70B-Instruct

  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-3.3-70B-Instruct (46). It leads on price 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 · Llama-3.3-70B-Instruct 127.3
  • Lowest priceMistral Small 3.1 24BMistral Small 3.1 24B $0.281 · Llama-3.3-70B-Instruct $0.624 per 1M tokens (3:1 blend)
  • Longest contextAbout the sameMistral Small 3.1 24B 128,000 · Llama-3.3-70B-Instruct 128,000 tokens
  • Widest inputsMistral Small 3.1 24BMistral Small 3.1 24B: Text, Images · Llama-3.3-70B-Instruct: Text
  • 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-3.3-70B-Instruct
CapabilityCapabilities Index (ECI)50%5049
Price25%7660
Inputs & features15%6025
Context window10%2424
Overall100%55/10046/100
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-3.3-70B-Instruct specifications side by side
SpecificationMistral Small 3.1 24BMistral AILlama-3.3-70B-InstructMeta
Capability
Capabilities Index (ECI)127.5 (best)127.3
ECI rank#132 of 148 (best)#133 of 148
GPQA DiamondGraduate-level science questions47.5% (best)47.4%
OTIS Mock AIME 2024–2025Competition mathematics5.8% (best)5.1%
Price per million tokens
Input$0.229 (best)$0.59
Output$0.436 (best)$0.724
Cached input——
Blended (3:1)$0.281 (best)$0.624
Long-context rateSame rateSame rate
Price sourceMedian of 2 providersMedian of 21 providers
Limits
Context window128,000 tokens128,000 tokens
Max output16,384 tokens (best)4,096 tokens
Inputs and features
TextYesYes
ImagesYesNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputYesNo
Availability
WeightsOpenOpen
API model ID—llama-3.3-70b-instruct
API providers224 (best)
ReleasedMar 17, 2025Dec 6, 2024
Knowledge cutoffJun 2024Dec 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.

  • Mistral Small 3.1 24B$3.16
  • Llama-3.3-70B-Instruct$7.35
04 — Questions

Which should you choose?

Which is better: Mistral Small 3.1 24B or Llama-3.3-70B-Instruct?

Mistral Small 3.1 24B is the better all-round choice, scoring 55/100 against Llama-3.3-70B-Instruct (46). It leads 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-3.3-70B-Instruct?

Mistral Small 3.1 24B is cheaper at $0.229 input / $0.436 output per million tokens (median across 2 API providers). Llama-3.3-70B-Instruct costs $0.59 input / $0.724 output per million tokens (median across 21 API providers; free on Llama). 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 $0.624 for Llama-3.3-70B-Instruct (2.2× 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-3.3-70B-Instruct 127.3 (#133 of 148). The confidence ranges of the top two overlap (122.6–129.4 vs 122.5–129.5), so treat the gap as small. On individual benchmarks: GPQA Diamond — Mistral Small 3.1 24B 47.5%, Llama-3.3-70B-Instruct 47.4%; OTIS Mock AIME 2024–2025 — Mistral Small 3.1 24B 5.8%, Llama-3.3-70B-Instruct 5.1%.

Which is better for coding?

There are no published SWE-bench Verified results for Mistral Small 3.1 24B and Llama-3.3-70B-Instruct 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. Both support tool calling for agent workflows.

Which has the bigger context window?

Mistral Small 3.1 24B and Llama-3.3-70B-Instruct share the same 128,000-token context window. Maximum output per response: Mistral Small 3.1 24B up to 16,384, Llama-3.3-70B-Instruct up to 4,096 tokens.

Which can read images, PDFs, audio or video?

Mistral Small 3.1 24B accepts text and images; Llama-3.3-70B-Instruct accepts text. Mistral Small 3.1 24B handles the widest range of inputs.

Are any of these open source?

Yes, both 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-3.3-70B-Instruct came out Dec 6, 2024. Knowledge cutoff: Mistral Small 3.1 24B Jun 2024, Llama-3.3-70B-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 Oct 4, 2026.

05 — Keep comparing

Related comparisons