Model Comparison

Gemma 2 27B vs Mistral Small 3.1 24B Base

Both models are evenly matched across the benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

Gemma 2 27B outperforms in 1 benchmarks (TriviaQA), while Mistral Small 3.1 24B Base is better at 1 benchmark (MMLU).

Both models are evenly matched across the benchmarks.

Sun Apr 19 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
Sun Apr 19 2026 • llm-stats.com
Google
Gemma 2 27B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Mistral AI
Mistral Small 3.1 24B Base
Input tokens$0.10
Output tokens$0.30
Best providerMistral
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

3.2B diff

Gemma 2 27B has 3.2B more parameters than Mistral Small 3.1 24B Base, making it 13.3% larger.

Google
Gemma 2 27B
27.2Bparameters
Mistral AI
Mistral Small 3.1 24B Base
24.0Bparameters
27.2B
Gemma 2 27B
24.0B
Mistral Small 3.1 24B Base

Context Window

Maximum input and output token capacity

Only Mistral Small 3.1 24B Base specifies input context (128,000 tokens). Only Mistral Small 3.1 24B Base specifies output context (128,000 tokens).

Google
Gemma 2 27B
Input- tokens
Output- tokens
Mistral AI
Mistral Small 3.1 24B Base
Input128,000 tokens
Output128,000 tokens
Sun Apr 19 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Mistral Small 3.1 24B Base supports multimodal inputs, whereas Gemma 2 27B does not.

Mistral Small 3.1 24B Base can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemma 2 27B

Text
Images
Audio
Video

Mistral Small 3.1 24B Base

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 2 27B is licensed under Gemma, while Mistral Small 3.1 24B Base uses Apache 2.0.

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

Gemma 2 27B

Gemma

Open weights

Mistral Small 3.1 24B Base

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemma 2 27B was released on 2024-06-27, while Mistral Small 3.1 24B Base was released on 2025-03-17.

Mistral Small 3.1 24B Base is 9 months newer than Gemma 2 27B.

Gemma 2 27B

Jun 27, 2024

1.8 years ago

Mistral Small 3.1 24B Base

Mar 17, 2025

1.1 years ago

8mo 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

Google
Higher TriviaQA score (83.7% vs 80.5%)
Mistral AI
Larger context window (128,000 tokens)
Supports multimodal inputs
Higher MMLU score (81.0% vs 75.2%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemma 2 27B
Mistral AI
Mistral Small 3.1 24B Base

FAQ

Common questions about Gemma 2 27B vs Mistral Small 3.1 24B Base

Both models are evenly matched across the benchmarks. Gemma 2 27B is made by Google and Mistral Small 3.1 24B Base is made by Mistral AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
Gemma 2 27B scores ARC-E: 88.6%, HellaSwag: 86.4%, BoolQ: 84.8%, TriviaQA: 83.7%, Winogrande: 83.7%. Mistral Small 3.1 24B Base scores MMLU: 81.0%, TriviaQA: 80.5%, MMMU: 59.3%, MMLU-Pro: 56.0%, GPQA: 37.5%.
Gemma 2 27B supports an unknown number of tokens and Mistral Small 3.1 24B Base 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 (Gemma vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
Gemma 2 27B is developed by Google and Mistral Small 3.1 24B Base is developed by Mistral AI.