Model Comparison

Codestral-22B vs Qwen2.5-Coder 32B Instruct

Qwen2.5-Coder 32B Instruct significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

Codestral-22B outperforms in 0 benchmarks, while Qwen2.5-Coder 32B Instruct is better at 2 benchmarks (HumanEval, MBPP).

Qwen2.5-Coder 32B Instruct significantly outperforms across most benchmarks.

Tue Mar 31 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Tue Mar 31 2026 • llm-stats.com
Mistral AI
Codestral-22B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Alibaba Cloud / Qwen Team
Qwen2.5-Coder 32B Instruct
Input tokens$0.09
Output tokens$0.09
Best providerLambda
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

9.8B diff

Qwen2.5-Coder 32B Instruct has 9.8B more parameters than Codestral-22B, making it 44.1% larger.

Mistral AI
Codestral-22B
22.2Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5-Coder 32B Instruct
32.0Bparameters
22.2B
Codestral-22B
32.0B
Qwen2.5-Coder 32B Instruct

Context Window

Maximum input and output token capacity

Only Qwen2.5-Coder 32B Instruct specifies input context (128,000 tokens). Only Qwen2.5-Coder 32B Instruct specifies output context (128,000 tokens).

Mistral AI
Codestral-22B
Input- tokens
Output- tokens
Alibaba Cloud / Qwen Team
Qwen2.5-Coder 32B Instruct
Input128,000 tokens
Output128,000 tokens
Tue Mar 31 2026 • llm-stats.com

License

Usage and distribution terms

Codestral-22B is licensed under MNPL-0.1, while Qwen2.5-Coder 32B Instruct 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

Qwen2.5-Coder 32B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

Codestral-22B was released on 2024-05-29, while Qwen2.5-Coder 32B Instruct was released on 2024-09-19.

Qwen2.5-Coder 32B Instruct is 4 months newer than Codestral-22B.

Codestral-22B

May 29, 2024

1.8 years ago

Qwen2.5-Coder 32B Instruct

Sep 19, 2024

1.5 years ago

3mo 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

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Key Takeaways

Mistral AI
Alibaba Cloud / Qwen Team
Larger context window (128,000 tokens)
Higher HumanEval score (92.7% vs 81.1%)
Higher MBPP score (90.2% vs 78.2%)

Detailed Comparison

AI Model Comparison Table
Feature
Mistral AI
Codestral-22B
Alibaba Cloud / Qwen Team
Qwen2.5-Coder 32B Instruct

FAQ

Common questions about Codestral-22B vs Qwen2.5-Coder 32B Instruct

Qwen2.5-Coder 32B Instruct significantly outperforms across most benchmarks. Codestral-22B is made by Mistral AI and Qwen2.5-Coder 32B Instruct is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
Codestral-22B scores HumanEvalFIM-Average: 91.6%, HumanEval: 81.1%, MBPP: 78.2%, Spider: 63.5%, HumanEval-Average: 61.5%. Qwen2.5-Coder 32B Instruct scores HumanEval: 92.7%, GSM8k: 91.1%, MBPP: 90.2%, HellaSwag: 83.0%, Winogrande: 80.8%.
Codestral-22B supports an unknown number of tokens and Qwen2.5-Coder 32B Instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (MNPL-0.1 vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
Codestral-22B is developed by Mistral AI and Qwen2.5-Coder 32B Instruct is developed by Alibaba Cloud / Qwen Team.