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Codestral-22B vs Pixtral Large

Codestral-22B and Pixtral Large are closely matched at 0.2 and 11.9 on the LLM Stats Score.

Mistral AI · Mistral AI · Updated for 2026

Which is better?

Codestral-22B and Pixtral Large are closely matched on the overall LLM Stats Score at 0.2 and 11.9.

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 Pixtral Large

  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Nov 2024

At a glance

The differences that matter most.

Codestral-22B
Mistral AI
Pixtral Large
Mistral AI
Core performance indexes
LLM Stats Score
0.2
#309
11.9
#240
Reasoning
0.1
#303
13.2
#224
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$2.00 / M
Output price
— / M
$6.00 / M
Context window
—
128,000

Individual benchmarks

7 reported for Codestral-22B · 7 for Pixtral Large

No common benchmarks found

Codestral-22B and Pixtral Largedon'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

101.8B diff

Pixtral Large has 101.8B more parameters than Codestral-22B, making it 458.6% larger.

Mistral AI
Codestral-22B
22.2Bparameters
Mistral AI
Pixtral Large
124.0Bparameters
22.2B
Codestral-22B
124.0B
Pixtral Large

Context Window

Maximum input and output token capacity

Only Pixtral Large specifies input context (128,000 tokens). Only Pixtral Large specifies output context (128,000 tokens).

Mistral AI
Codestral-22B
Input- tokens
Output- tokens
Mistral AI
Pixtral Large
Input128,000 tokens
Output128,000 tokens
Mon Aug 31 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Pixtral Large supports multimodal inputs, whereas Codestral-22B does not.

Pixtral Large can handle both text and other forms of data like images, making it suitable for multimodal applications.

Codestral-22B

Text
Images
Audio
Video

Pixtral Large

Text
Images
Audio
Video

License

Usage and distribution terms

Codestral-22B is licensed under MNPL-0.1, while Pixtral Large uses Mistral Research License (MRL) for research; Mistral Commercial License for commercial use.

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

Codestral-22B

MNPL-0.1

Open weights

Pixtral Large

Mistral Research License (MRL) for research; Mistral Commercial License for commercial use

Open weights

Release Timeline

When each model was launched

Codestral-22B was released on 2024-05-29, while Pixtral Large was released on 2024-11-18.

Pixtral Large is 6 months newer than Codestral-22B.

Codestral-22B

May 29, 2024

2.3 years ago

Pixtral Large

Nov 18, 2024

1.8 years ago

5mo 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 Pixtral Large side-by-side, then vote on the output you prefer.

Codestral-22B
✓ Preferred
Pixtral Large
Open in Playground

FAQ

Common questions about Codestral-22B vs Pixtral Large.

Which is better, Codestral-22B or Pixtral Large?

Codestral-22B and Pixtral Large are closely matched on the LLM Stats Score at 0.2 and 11.9. Codestral-22B is made by Mistral AI and Pixtral Large 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 Pixtral Large in benchmarks?

Codestral-22B scores HumanEvalFIM-Average: 91.6%, HumanEval: 81.1%, MBPP: 78.2%, Spider: 63.5%, HumanEval-Average: 61.5%. Pixtral Large scores AI2D: 93.8%, DocVQA: 93.3%, ChartQA: 88.1%, VQAv2: 80.9%, MM-MT-Bench: 74.0%.

What are the context window sizes for Codestral-22B and Pixtral Large?

Codestral-22B supports an unknown number of tokens and Pixtral Large 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 Pixtral Large?

Key differences include LLM Stats Score (0.2 vs 11.9), multimodal support (no vs yes), licensing (MNPL-0.1 vs Mistral Research License (MRL) for research; Mistral Commercial License for commercial use). See the full comparison above for benchmark-by-benchmark results.

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