Model Comparison

Codestral-22B vs Llama 3.2 90B Instruct

Comparing Codestral-22B and Llama 3.2 90B Instruct across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Codestral-22B and Llama 3.2 90B Instruct 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
Sun Apr 05 2026 • llm-stats.com
Mistral AI
Codestral-22B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Meta
Llama 3.2 90B Instruct
Input tokens$0.35
Output tokens$0.40
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

67.8B diff

Llama 3.2 90B Instruct has 67.8B more parameters than Codestral-22B, making it 305.4% larger.

Mistral AI
Codestral-22B
22.2Bparameters
Meta
Llama 3.2 90B Instruct
90.0Bparameters
22.2B
Codestral-22B
90.0B
Llama 3.2 90B Instruct

Context Window

Maximum input and output token capacity

Only Llama 3.2 90B Instruct specifies input context (128,000 tokens). Only Llama 3.2 90B Instruct specifies output context (128,000 tokens).

Mistral AI
Codestral-22B
Input- tokens
Output- tokens
Meta
Llama 3.2 90B Instruct
Input128,000 tokens
Output128,000 tokens
Sun Apr 05 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Llama 3.2 90B Instruct supports multimodal inputs, whereas Codestral-22B does not.

Llama 3.2 90B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

Codestral-22B

Text
Images
Audio
Video

Llama 3.2 90B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

Codestral-22B is licensed under MNPL-0.1, while Llama 3.2 90B Instruct uses Llama 3.2.

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

Codestral-22B

MNPL-0.1

Open weights

Llama 3.2 90B Instruct

Llama 3.2

Open weights

Release Timeline

When each model was launched

Codestral-22B was released on 2024-05-29, while Llama 3.2 90B Instruct was released on 2024-09-25.

Llama 3.2 90B Instruct is 4 months newer than Codestral-22B.

Codestral-22B

May 29, 2024

1.9 years ago

Llama 3.2 90B Instruct

Sep 25, 2024

1.5 years ago

3mo 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

Mistral AI
Meta
Larger context window (128,000 tokens)
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
Mistral AI
Codestral-22B
Meta
Llama 3.2 90B Instruct

FAQ

Common questions about Codestral-22B vs Llama 3.2 90B Instruct

Codestral-22B (Mistral AI) and Llama 3.2 90B Instruct (Meta) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
Codestral-22B scores HumanEvalFIM-Average: 91.6%, HumanEval: 81.1%, MBPP: 78.2%, Spider: 63.5%, HumanEval-Average: 61.5%. Llama 3.2 90B Instruct scores AI2D: 92.3%, DocVQA: 90.1%, MGSM: 86.9%, MMLU: 86.0%, ChartQA: 85.5%.
Codestral-22B supports an unknown number of tokens and Llama 3.2 90B Instruct supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include multimodal support (no vs yes), licensing (MNPL-0.1 vs Llama 3.2). See the full comparison above for benchmark-by-benchmark results.
Codestral-22B is developed by Mistral AI and Llama 3.2 90B Instruct is developed by Meta.