ZMIME
Comparison · 2 models · Updated Oct 4, 2026

Codestral vs Mistral Large 2.1

Codestral comes out ahead, 48 to 26 on our weighted score, and it is the cheaper option too.

  1. Our pick

    Mistral AI

    Codestral

    Released May 29, 2024

    48/100
    • ECI—
    • Price$0.30 / $0.90
    • Context256K
    Full specs Remove Codestral

  2. Mistral AI

    Mistral Large 2.1

    Released Nov 18, 2024

    26/100
    • ECI128.5
    • Price$2.00 / $6.00
    • Context131K
    Full specs Remove Mistral Large 2.1

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

Codestral is our pick

Codestral is the better all-round choice, scoring 48/100 against Mistral Large 2.1 (26). It leads on price and context window. 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 priceCodestralCodestral $0.45 · Mistral Large 2.1 $3.00 per 1M tokens (3:1 blend)
  • Longest contextCodestralCodestral 256,000 · Mistral Large 2.1 131,072 tokens
  • Widest inputsSame inputsCodestral: Text · Mistral Large 2.1: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightCodestralMistral Large 2.1
Price50%6627
Inputs & features30%2525
Context window20%3624
Overall100%48/10026/100

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.

Codestral vs Mistral Large 2.1 specifications side by side
SpecificationCodestralMistral AIMistral Large 2.1Mistral AI
Capability
Capabilities Index (ECI)—128.5
ECI rank—#130 of 148
GPQA DiamondGraduate-level science questions—51.3%
OTIS Mock AIME 2024–2025Competition mathematics—7.8%
Price per million tokens
Input$0.30 (best)$2.00
Output$0.90 (best)$6.00
Cached input$0.03—
Blended (3:1)$0.45 (best)$3.00
Long-context rateSame rateSame rate
Price sourceOfficial Mistral APIOfficial Mistral API
Limits
Context window256,000 tokens (best)131,072 tokens
Max output4,096 tokens16,384 tokens (best)
Inputs and features
TextYesYes
ImagesNoNo
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningNoNo
Tool callingYesYes
Structured outputNoNo
Availability
WeightsOpenOpen
API model IDcodestral-latestmistral-large-2411
API providers3 (best)2
ReleasedMay 29, 2024Nov 18, 2024
Knowledge cutoffOct 2024Nov 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.

  • Codestral$4.80
  • Mistral Large 2.1$32.00
04 — Questions

Which should you choose?

Which is better: Codestral or Mistral Large 2.1?

Codestral is the better all-round choice, scoring 48/100 against Mistral Large 2.1 (26). It leads on price and context window. 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, Codestral or Mistral Large 2.1?

Codestral is cheaper at $0.30 input / $0.90 output per million tokens (official Mistral API price). Mistral Large 2.1 costs $2.00 input / $6.00 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.45 per million tokens for Codestral versus $3.00 for Mistral Large 2.1 (6.7× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers both models yet. Codestral has not been scored yet and Mistral Large 2.1 has an ECI of 128.5.

Which is better for coding?

There are no published SWE-bench Verified results for Codestral and Mistral Large 2.1 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?

Codestral has the largest context window at 256,000 tokens, against 131,072 for Mistral Large 2.1. Maximum output per response: Codestral up to 4,096, Mistral Large 2.1 up to 16,384 tokens.

Which can read images, PDFs, audio or video?

Codestral accepts text; Mistral Large 2.1 accepts text. They handle the same number of input types.

Are any of these open source?

Yes, both publish their weights, so you can self-host them.

Which is newer?

Mistral Large 2.1 is the newest, released Nov 18, 2024. Codestral came out May 29, 2024. Knowledge cutoff: Codestral Oct 2024, Mistral Large 2.1 Nov 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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