Model Comparison

Codestral-22B vs QwQ-32B-Preview

Comparing Codestral-22B and QwQ-32B-Preview across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Codestral-22B and QwQ-32B-Preview don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Model Size

Parameter count comparison

10.3B diff

QwQ-32B-Preview has 10.3B more parameters than Codestral-22B, making it 46.4% larger.

Codestral-22B

22.2Bparameters

QwQ-32B-Preview

32.5Bparameters

22.2B

Codestral-22B

32.5B

QwQ-32B-Preview

Context Window

Maximum input and output token capacity

Only QwQ-32B-Preview specifies input context (32,768 tokens). Only QwQ-32B-Preview specifies output context (32,768 tokens).

Codestral-22B

Input- tokens

Output- tokens

QwQ-32B-Preview

Input32,768 tokens

Output32,768 tokens

Sun May 31 2026 • llm-stats.com

License

Usage and distribution terms

Codestral-22B is licensed under MNPL-0.1, while QwQ-32B-Preview 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

QwQ-32B-Preview

Apache 2.0

Open weights

Release Timeline

When each model was launched

Codestral-22B was released on 2024-05-29, while QwQ-32B-Preview was released on 2024-11-28.

QwQ-32B-Preview is 6 months newer than Codestral-22B.

Codestral-22B

May 29, 2024

2.0 years ago

QwQ-32B-Preview

Nov 28, 2024

1.5 years ago

6mo newer

Knowledge Cutoff

When training data ends

QwQ-32B-Preview has a documented knowledge cutoff of 2024-11-28, while Codestral-22B's cutoff date is not specified.

We can confirm QwQ-32B-Preview's training data extends to 2024-11-28, but cannot make a direct comparison without Codestral-22B's cutoff date.

Codestral-22B

—

QwQ-32B-Preview

Nov 2024

Outputs Comparison

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Key Takeaways

Codestral-22B

View details

Mistral AI

No standout differentiators in the data we have for this pair.

QwQ-32B-Preview

View details

Alibaba Cloud / Qwen Team

Larger context window (32,768 tokens)

Detailed Comparison

AI Model Comparison Table
Feature	Codestral-22B	QwQ-32B-Preview

FAQ

Common questions about Codestral-22B vs QwQ-32B-Preview.

Which is better, Codestral-22B or QwQ-32B-Preview?

Codestral-22B (Mistral AI) and QwQ-32B-Preview (Alibaba Cloud / Qwen Team) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does Codestral-22B compare to QwQ-32B-Preview in benchmarks?

Codestral-22B scores HumanEvalFIM-Average: 91.6%, HumanEval: 81.1%, MBPP: 78.2%, Spider: 63.5%, HumanEval-Average: 61.5%. QwQ-32B-Preview scores MATH-500: 90.6%, GPQA: 65.2%, AIME 2024: 50.0%, LiveCodeBench: 50.0%.

What are the context window sizes for Codestral-22B and QwQ-32B-Preview?

Codestral-22B supports an unknown number of tokens and QwQ-32B-Preview supports 33K 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 QwQ-32B-Preview?

Key differences include licensing (MNPL-0.1 vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Codestral-22B and QwQ-32B-Preview?

Codestral-22B is developed by Mistral AI and QwQ-32B-Preview is developed by Alibaba Cloud / Qwen Team.