Model Comparison

Codestral-22B vs Qwen3-Next-80B-A3B-Thinking

Comparing Codestral-22B and Qwen3-Next-80B-A3B-Thinking across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Codestral-22B and Qwen3-Next-80B-A3B-Thinking 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

57.8B diff

Qwen3-Next-80B-A3B-Thinking has 57.8B more parameters than Codestral-22B, making it 260.4% larger.

Codestral-22B

22.2Bparameters

Qwen3-Next-80B-A3B-Thinking

80.0Bparameters

22.2B

Codestral-22B

80.0B

Qwen3-Next-80B-A3B-Thinking

Context Window

Maximum input and output token capacity

Only Qwen3-Next-80B-A3B-Thinking specifies input context (65,536 tokens). Only Qwen3-Next-80B-A3B-Thinking specifies output context (65,536 tokens).

Codestral-22B

Input- tokens

Output- tokens

Qwen3-Next-80B-A3B-Thinking

Input65,536 tokens

Output65,536 tokens

Fri May 15 2026 • llm-stats.com

License

Usage and distribution terms

Codestral-22B is licensed under MNPL-0.1, while Qwen3-Next-80B-A3B-Thinking 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

Qwen3-Next-80B-A3B-Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

Codestral-22B was released on 2024-05-29, while Qwen3-Next-80B-A3B-Thinking was released on 2025-09-10.

Qwen3-Next-80B-A3B-Thinking is 16 months newer than Codestral-22B.

Codestral-22B

May 29, 2024

2.0 years ago

Qwen3-Next-80B-A3B-Thinking

Sep 10, 2025

8 months ago

1.3yr 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

Codestral-22B

View details

Mistral AI

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

Qwen3-Next-80B-A3B-Thinking

View details

Alibaba Cloud / Qwen Team

Larger context window (65,536 tokens)

Detailed Comparison

AI Model Comparison Table
Feature	Codestral-22B	Qwen3-Next-80B-A3B-Thinking

FAQ

Common questions about Codestral-22B vs Qwen3-Next-80B-A3B-Thinking.

Which is better, Codestral-22B or Qwen3-Next-80B-A3B-Thinking?

Codestral-22B (Mistral AI) and Qwen3-Next-80B-A3B-Thinking (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 Qwen3-Next-80B-A3B-Thinking in benchmarks?

Codestral-22B scores HumanEvalFIM-Average: 91.6%, HumanEval: 81.1%, MBPP: 78.2%, Spider: 63.5%, HumanEval-Average: 61.5%. Qwen3-Next-80B-A3B-Thinking scores MMLU-Redux: 92.5%, IFEval: 88.9%, AIME 2025: 87.8%, WritingBench: 84.6%, MMLU-Pro: 82.7%.

What are the context window sizes for Codestral-22B and Qwen3-Next-80B-A3B-Thinking?

Codestral-22B supports an unknown number of tokens and Qwen3-Next-80B-A3B-Thinking supports 66K 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 Qwen3-Next-80B-A3B-Thinking?

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 Qwen3-Next-80B-A3B-Thinking?

Codestral-22B is developed by Mistral AI and Qwen3-Next-80B-A3B-Thinking is developed by Alibaba Cloud / Qwen Team.