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Codestral-22B vs Mistral Small 3.1 24B Base

Codestral-22B and Mistral Small 3.1 24B Base are closely matched at 0.0 and 0.3 on the LLM Stats Score.

Mistral AI · Mistral AI · Updated for 2026

Which is better?

Codestral-22B and Mistral Small 3.1 24B Base are closely matched on the overall LLM Stats Score at 0.0 and 0.3.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Codestral-22B

  • you are already invested in the Mistral AI ecosystem

Choose Mistral Small 3.1 24B Base

  • you want the most recent training data — it shipped Mar 2025

At a glance

The differences that matter most.

Codestral-22B
Mistral AI
Mistral Small 3.1 24B Base
Mistral AI
Core performance indexes
LLM Stats Score
0.0
#332
0.3
#331
Reasoning
-0.1
#324
0.5
#322
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$0.10 / M
Output price
— / M
$0.30 / M
Context window
—
128,000

Individual benchmarks

7 reported for Codestral-22B · 5 for Mistral Small 3.1 24B Base

No common benchmarks found

Codestral-22B and Mistral Small 3.1 24B Basedon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

1.8B diff

Mistral Small 3.1 24B Base has 1.8B more parameters than Codestral-22B, making it 8.1% larger.

Mistral AI
Codestral-22B
22.2Bparameters
Mistral AI
Mistral Small 3.1 24B Base
24.0Bparameters
22.2B
Codestral-22B
24.0B
Mistral Small 3.1 24B Base

Context Window

Maximum input and output token capacity

Only Mistral Small 3.1 24B Base specifies input context (128,000 tokens). Only Mistral Small 3.1 24B Base specifies output context (128,000 tokens).

Mistral AI
Codestral-22B
Input- tokens
Output- tokens
Mistral AI
Mistral Small 3.1 24B Base
Input128,000 tokens
Output128,000 tokens
Sun Sep 27 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Mistral Small 3.1 24B Base supports multimodal inputs, whereas Codestral-22B does not.

Mistral Small 3.1 24B Base can handle both text and other forms of data like images, making it suitable for multimodal applications.

Codestral-22B

Text
Images
Audio
Video

Mistral Small 3.1 24B Base

Text
Images
Audio
Video

License

Usage and distribution terms

Codestral-22B is licensed under MNPL-0.1, while Mistral Small 3.1 24B Base uses Apache 2.0.

License differences may affect how you can use these models in commercial or open-source projects.

Codestral-22B

MNPL-0.1

Open weights

Mistral Small 3.1 24B Base

Apache 2.0

Open weights

Release Timeline

When each model was launched

Codestral-22B was released on 2024-05-29, while Mistral Small 3.1 24B Base was released on 2025-03-17.

Mistral Small 3.1 24B Base is 10 months newer than Codestral-22B.

Codestral-22B

May 29, 2024

2.3 years ago

Mistral Small 3.1 24B Base

Mar 17, 2025

1.5 years ago

9mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Codestral-22B and Mistral Small 3.1 24B Base side-by-side, then vote on the output you prefer.

Codestral-22B
✓ Preferred
Mistral Small 3.1 24B Base
Open in Playground

FAQ

Common questions about Codestral-22B vs Mistral Small 3.1 24B Base.

Which is better, Codestral-22B or Mistral Small 3.1 24B Base?

Codestral-22B and Mistral Small 3.1 24B Base are closely matched on the LLM Stats Score at 0.0 and 0.3. Codestral-22B is made by Mistral AI and Mistral Small 3.1 24B Base is made by Mistral AI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Codestral-22B compare to Mistral Small 3.1 24B Base in benchmarks?

Codestral-22B scores HumanEvalFIM-Average: 91.6%, HumanEval: 81.1%, MBPP: 78.2%, Spider: 63.5%, HumanEval-Average: 61.5%. Mistral Small 3.1 24B Base scores MMLU: 81.0%, TriviaQA: 80.5%, MMMU: 59.3%, MMLU-Pro: 56.0%, GPQA: 37.5%.

What are the context window sizes for Codestral-22B and Mistral Small 3.1 24B Base?

Codestral-22B supports an unknown number of tokens and Mistral Small 3.1 24B Base supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Codestral-22B and Mistral Small 3.1 24B Base?

Key differences include LLM Stats Score (0.0 vs 0.3), multimodal support (no vs yes), licensing (MNPL-0.1 vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

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