Model Comparison

Codestral-22B vs DeepSeek R1 Distill Qwen 1.5BWhich is better in 2026?

Comparing Codestral-22B and DeepSeek R1 Distill Qwen 1.5B across benchmarks, pricing, and capabilities.

Verdict: Codestral-22B vs DeepSeek R1 Distill Qwen 1.5B — which is better?

Codestral-22B (by Mistral AI) and DeepSeek R1 Distill Qwen 1.5B (by DeepSeek) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

Choose Codestral-22B if…

  • you are already invested in the Mistral AI ecosystem

Choose DeepSeek R1 Distill Qwen 1.5B if…

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

Comparative analysis across standard metrics

No common benchmarks found

Codestral-22B and DeepSeek R1 Distill Qwen 1.5B 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

20.4B diff

Codestral-22B has 20.4B more parameters than DeepSeek R1 Distill Qwen 1.5B, making it 1147.2% larger.

Mistral AI
Codestral-22B
22.2Bparameters
DeepSeek
DeepSeek R1 Distill Qwen 1.5B
1.8Bparameters
22.2B
Codestral-22B
1.8B
DeepSeek R1 Distill Qwen 1.5B

License

Usage and distribution terms

Codestral-22B is licensed under MNPL-0.1, while DeepSeek R1 Distill Qwen 1.5B uses MIT.

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

Codestral-22B

MNPL-0.1

Open weights

DeepSeek R1 Distill Qwen 1.5B

MIT

Open weights

Release Timeline

When each model was launched

Codestral-22B was released on 2024-05-29, while DeepSeek R1 Distill Qwen 1.5B was released on 2025-01-20.

DeepSeek R1 Distill Qwen 1.5B is 8 months newer than Codestral-22B.

Codestral-22B

May 29, 2024

2.0 years ago

DeepSeek R1 Distill Qwen 1.5B

Jan 20, 2025

1.4 years ago

7mo 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→

Key Takeaways

Mistral AI

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

DeepSeek

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

Detailed Comparison

AI Model Comparison Table
Feature
Mistral AI
Codestral-22B
DeepSeek
DeepSeek R1 Distill Qwen 1.5B

FAQ

Common questions about Codestral-22B vs DeepSeek R1 Distill Qwen 1.5B.

Which is better, Codestral-22B or DeepSeek R1 Distill Qwen 1.5B?

Codestral-22B (Mistral AI) and DeepSeek R1 Distill Qwen 1.5B (DeepSeek) 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 DeepSeek R1 Distill Qwen 1.5B in benchmarks?

Codestral-22B scores HumanEvalFIM-Average: 91.6%, HumanEval: 81.1%, MBPP: 78.2%, Spider: 63.5%, HumanEval-Average: 61.5%. DeepSeek R1 Distill Qwen 1.5B scores MATH-500: 83.9%, AIME 2024: 52.7%, GPQA: 33.8%, LiveCodeBench: 16.9%.

What are the main differences between Codestral-22B and DeepSeek R1 Distill Qwen 1.5B?

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

Who makes Codestral-22B and DeepSeek R1 Distill Qwen 1.5B?

Codestral-22B is developed by Mistral AI and DeepSeek R1 Distill Qwen 1.5B is developed by DeepSeek.

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