Model Comparison

Codestral-22B vs Gemma 3 27B

Both models are evenly matched across the benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

Codestral-22B outperforms in 1 benchmarks (MBPP), while Gemma 3 27B is better at 1 benchmark (HumanEval).

Both models are evenly matched across the benchmarks.

Wed Apr 22 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Wed Apr 22 2026 • llm-stats.com
Mistral AI
Codestral-22B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Google
Gemma 3 27B
Input tokens$0.10
Output tokens$0.20
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

4.8B diff

Gemma 3 27B has 4.8B more parameters than Codestral-22B, making it 21.6% larger.

Mistral AI
Codestral-22B
22.2Bparameters
Google
Gemma 3 27B
27.0Bparameters
22.2B
Codestral-22B
27.0B
Gemma 3 27B

Context Window

Maximum input and output token capacity

Only Gemma 3 27B specifies input context (131,072 tokens). Only Gemma 3 27B specifies output context (131,072 tokens).

Mistral AI
Codestral-22B
Input- tokens
Output- tokens
Google
Gemma 3 27B
Input131,072 tokens
Output131,072 tokens
Wed Apr 22 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemma 3 27B supports multimodal inputs, whereas Codestral-22B does not.

Gemma 3 27B can handle both text and other forms of data like images, making it suitable for multimodal applications.

Codestral-22B

Text
Images
Audio
Video

Gemma 3 27B

Text
Images
Audio
Video

License

Usage and distribution terms

Codestral-22B is licensed under MNPL-0.1, while Gemma 3 27B uses Gemma.

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

Codestral-22B

MNPL-0.1

Open weights

Gemma 3 27B

Gemma

Open weights

Release Timeline

When each model was launched

Codestral-22B was released on 2024-05-29, while Gemma 3 27B was released on 2025-03-12.

Gemma 3 27B is 10 months newer than Codestral-22B.

Codestral-22B

May 29, 2024

1.9 years ago

Gemma 3 27B

Mar 12, 2025

1.1 years ago

9mo 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
Higher MBPP score (78.2% vs 74.4%)
Google
Larger context window (131,072 tokens)
Supports multimodal inputs
Higher HumanEval score (87.8% vs 81.1%)

Detailed Comparison

AI Model Comparison Table
Feature
Mistral AI
Codestral-22B
Google
Gemma 3 27B

FAQ

Common questions about Codestral-22B vs Gemma 3 27B

Both models are evenly matched across the benchmarks. Codestral-22B is made by Mistral AI and Gemma 3 27B is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
Codestral-22B scores HumanEvalFIM-Average: 91.6%, HumanEval: 81.1%, MBPP: 78.2%, Spider: 63.5%, HumanEval-Average: 61.5%. Gemma 3 27B scores GSM8k: 95.9%, IFEval: 90.4%, MATH: 89.0%, HumanEval: 87.8%, BIG-Bench Hard: 87.6%.
Codestral-22B supports an unknown number of tokens and Gemma 3 27B supports 131K 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 Gemma). See the full comparison above for benchmark-by-benchmark results.
Codestral-22B is developed by Mistral AI and Gemma 3 27B is developed by Google.