Model Comparison

DeepSeek R1 Distill Llama 70B vs Codestral-22B

Comparing DeepSeek R1 Distill Llama 70B and Codestral-22B across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek R1 Distill Llama 70B and Codestral-22B don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Sat Apr 04 2026 • llm-stats.com
DeepSeek
DeepSeek R1 Distill Llama 70B
Input tokens$0.10
Output tokens$0.40
Best providerDeepinfra
Mistral AI
Codestral-22B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

48.4B diff

DeepSeek R1 Distill Llama 70B has 48.4B more parameters than Codestral-22B, making it 218.0% larger.

DeepSeek
DeepSeek R1 Distill Llama 70B
70.6Bparameters
Mistral AI
Codestral-22B
22.2Bparameters
70.6B
DeepSeek R1 Distill Llama 70B
22.2B
Codestral-22B

Context Window

Maximum input and output token capacity

Only DeepSeek R1 Distill Llama 70B specifies input context (128,000 tokens). Only DeepSeek R1 Distill Llama 70B specifies output context (128,000 tokens).

DeepSeek
DeepSeek R1 Distill Llama 70B
Input128,000 tokens
Output128,000 tokens
Mistral AI
Codestral-22B
Input- tokens
Output- tokens
Sat Apr 04 2026 • llm-stats.com

License

Usage and distribution terms

DeepSeek R1 Distill Llama 70B is licensed under MIT, while Codestral-22B uses MNPL-0.1.

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

DeepSeek R1 Distill Llama 70B

MIT

Open weights

Codestral-22B

MNPL-0.1

Open weights

Release Timeline

When each model was launched

DeepSeek R1 Distill Llama 70B was released on 2025-01-20, while Codestral-22B was released on 2024-05-29.

DeepSeek R1 Distill Llama 70B is 8 months newer than Codestral-22B.

DeepSeek R1 Distill Llama 70B

Jan 20, 2025

1.2 years ago

7mo newer
Codestral-22B

May 29, 2024

1.8 years ago

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

DeepSeek
Larger context window (128,000 tokens)
Mistral AI

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek R1 Distill Llama 70B
Mistral AI
Codestral-22B

FAQ

Common questions about DeepSeek R1 Distill Llama 70B vs Codestral-22B

DeepSeek R1 Distill Llama 70B (DeepSeek) and Codestral-22B (Mistral AI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
DeepSeek R1 Distill Llama 70B scores MATH-500: 94.5%, AIME 2024: 86.7%, GPQA: 65.2%, LiveCodeBench: 57.5%. Codestral-22B scores HumanEvalFIM-Average: 91.6%, HumanEval: 81.1%, MBPP: 78.2%, Spider: 63.5%, HumanEval-Average: 61.5%.
DeepSeek R1 Distill Llama 70B supports 128K tokens and Codestral-22B supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include licensing (MIT vs MNPL-0.1). See the full comparison above for benchmark-by-benchmark results.
DeepSeek R1 Distill Llama 70B is developed by DeepSeek and Codestral-22B is developed by Mistral AI.