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Codestral-22B vs Qwen2.5 VL 7B Instruct

Codestral-22B and Qwen2.5 VL 7B Instruct are closely matched at 0.0 and 6.5 on the LLM Stats Score.

Mistral AI · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

Codestral-22B and Qwen2.5 VL 7B Instruct are closely matched on the overall LLM Stats Score at 0.0 and 6.5.

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 Qwen2.5 VL 7B Instruct

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

At a glance

The differences that matter most.

Core performance indexes
0.0
#334
6.5
#300
-0.1
#326
3.0
#310
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
— / M
Output price
— / M
— / M
Context window
—
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Individual benchmarks

7 reported for Codestral-22B · 32 for Qwen2.5 VL 7B Instruct

No common benchmarks found

Codestral-22B and Qwen2.5 VL 7B Instructdon'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

13.9B diff

Codestral-22B has 13.9B more parameters than Qwen2.5 VL 7B Instruct, making it 167.8% larger.

Mistral AI
Codestral-22B
22.2Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5 VL 7B Instruct
8.3Bparameters
22.2B
Codestral-22B
8.3B
Qwen2.5 VL 7B Instruct

Input capabilities

Documented input modalities across available providers

Qwen2.5 VL 7B Instruct supports multimodal inputs, whereas Codestral-22B does not.

Qwen2.5 VL 7B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

Codestral-22B

Text
Images
Audio
Video

Qwen2.5 VL 7B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Codestral-22B is licensed under MNPL-0.1, while Qwen2.5 VL 7B 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 VL 7B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

Codestral-22B was released on 2024-05-29, while Qwen2.5 VL 7B Instruct was released on 2025-01-26.

Qwen2.5 VL 7B Instruct is 8 months newer than Codestral-22B.

Codestral-22B

May 29, 2024

2.3 years ago

Qwen2.5 VL 7B Instruct

Jan 26, 2025

1.7 years ago

8mo 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?

Judge for yourself.

Run your own prompts against Codestral-22B and Qwen2.5 VL 7B Instruct side-by-side, then vote on the output you prefer.

Codestral-22B
✓ Preferred
Qwen2.5 VL 7B Instruct
Open in Playground

FAQ

Common questions about Codestral-22B vs Qwen2.5 VL 7B Instruct.

Which is better, Codestral-22B or Qwen2.5 VL 7B Instruct?

Codestral-22B and Qwen2.5 VL 7B Instruct are closely matched on the LLM Stats Score at 0.0 and 6.5. Codestral-22B is made by Mistral AI and Qwen2.5 VL 7B Instruct is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Codestral-22B compare to Qwen2.5 VL 7B Instruct in benchmarks?

Codestral-22B scores HumanEvalFIM-Average: 91.6%, HumanEval: 81.1%, MBPP: 78.2%, Spider: 63.5%, HumanEval-Average: 61.5%. Qwen2.5 VL 7B Instruct scores DocVQA: 95.7%, Android Control Low_EM: 91.4%, MobileMiniWob++_SR: 91.4%, ChartQA: 87.3%, OCRBench: 86.4%.

What are the main differences between Codestral-22B and Qwen2.5 VL 7B Instruct?

Key differences include LLM Stats Score (0.0 vs 6.5), multimodal support (no vs yes), licensing (MNPL-0.1 vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Codestral-22B and Qwen2.5 VL 7B Instruct?

Codestral-22B is developed by Mistral AI and Qwen2.5 VL 7B Instruct is developed by Alibaba Cloud / Qwen Team.