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Codestral-22B vs DeepSeek R1 Zero

DeepSeek R1 Zero leads the LLM Stats Score 16.0 to 0.0.

Mistral AI · DeepSeek · Updated for 2026

Which is better?

DeepSeek R1 Zero leads the overall LLM Stats Score 16.0 to 0.0, ranking #226 overall.

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 DeepSeek R1 Zero

  • overall performance matters — it scores 16.0 and ranks #226 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Jan 2025

At a glance

The differences that matter most.

Codestral-22B
Mistral AI
DeepSeek R1 Zero
DeepSeek
Core performance indexes
LLM Stats Score
0.0
#326
16.0
#226
Reasoning
-0.1
#318
16.3
#216
Coding
2.5
#225
4.3
#209
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
— / M
Output price
— / M
— / M
Context window
—
—

Individual benchmarks

7 reported for Codestral-22B · 4 for DeepSeek R1 Zero

No common benchmarks found

Codestral-22B and DeepSeek R1 Zerodon'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

648.8B diff

DeepSeek R1 Zero has 648.8B more parameters than Codestral-22B, making it 2922.5% larger.

Mistral AI
Codestral-22B
22.2Bparameters
DeepSeek
DeepSeek R1 Zero
671.0Bparameters
22.2B
Codestral-22B
671.0B
DeepSeek R1 Zero

License

Usage and distribution terms

Codestral-22B is licensed under MNPL-0.1, while DeepSeek R1 Zero 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 Zero

MIT

Open weights

Release Timeline

When each model was launched

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

DeepSeek R1 Zero is 8 months newer than Codestral-22B.

Codestral-22B

May 29, 2024

2.3 years ago

DeepSeek R1 Zero

Jan 20, 2025

1.7 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→

Judge for yourself.

Run your own prompts against Codestral-22B and DeepSeek R1 Zero side-by-side, then vote on the output you prefer.

Codestral-22B
✓ Preferred
DeepSeek R1 Zero
Open in Playground

FAQ

Common questions about Codestral-22B vs DeepSeek R1 Zero.

Which is better, Codestral-22B or DeepSeek R1 Zero?

DeepSeek R1 Zero leads the LLM Stats Score 16.0 to 0.0. Codestral-22B is made by Mistral AI and DeepSeek R1 Zero is made by DeepSeek. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Codestral-22B compare to DeepSeek R1 Zero in benchmarks?

Codestral-22B scores HumanEvalFIM-Average: 91.6%, HumanEval: 81.1%, MBPP: 78.2%, Spider: 63.5%, HumanEval-Average: 61.5%. DeepSeek R1 Zero scores MATH-500: 95.9%, AIME 2024: 86.7%, GPQA: 73.3%, LiveCodeBench: 50.0%.

What are the main differences between Codestral-22B and DeepSeek R1 Zero?

Key differences include LLM Stats Score (0.0 vs 16.0), licensing (MNPL-0.1 vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Codestral-22B and DeepSeek R1 Zero?

Codestral-22B is developed by Mistral AI and DeepSeek R1 Zero is developed by DeepSeek.

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