Model Comparison

Gemma 2 9B vs Pixtral Large

Comparing Gemma 2 9B and Pixtral Large across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

Gemma 2 9B and Pixtral Large don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Model Size

Parameter count comparison

114.8B diff

Pixtral Large has 114.8B more parameters than Gemma 2 9B, making it 1242.0% larger.

Google
Gemma 2 9B
9.2Bparameters
Mistral AI
Pixtral Large
124.0Bparameters
9.2B
Gemma 2 9B
124.0B
Pixtral Large

Context Window

Maximum input and output token capacity

Only Pixtral Large specifies input context (128,000 tokens). Only Pixtral Large specifies output context (128,000 tokens).

Google
Gemma 2 9B
Input- tokens
Output- tokens
Mistral AI
Pixtral Large
Input128,000 tokens
Output128,000 tokens
Wed May 06 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Pixtral Large supports multimodal inputs, whereas Gemma 2 9B does not.

Pixtral Large can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemma 2 9B

Text
Images
Audio
Video

Pixtral Large

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 2 9B is licensed under Gemma, while Pixtral Large uses Mistral Research License (MRL) for research; Mistral Commercial License for commercial use.

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

Gemma 2 9B

Gemma

Open weights

Pixtral Large

Mistral Research License (MRL) for research; Mistral Commercial License for commercial use

Open weights

Release Timeline

When each model was launched

Gemma 2 9B was released on 2024-06-27, while Pixtral Large was released on 2024-11-18.

Pixtral Large is 5 months newer than Gemma 2 9B.

Gemma 2 9B

Jun 27, 2024

1.9 years ago

Pixtral Large

Nov 18, 2024

1.5 years ago

4mo 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→

Key Takeaways

Google

No standout differentiators in the data we have for this pair.

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

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemma 2 9B
Mistral AI
Pixtral Large

FAQ

Common questions about Gemma 2 9B vs Pixtral Large.

Which is better, Gemma 2 9B or Pixtral Large?

Gemma 2 9B (Google) and Pixtral Large (Mistral AI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does Gemma 2 9B compare to Pixtral Large in benchmarks?

Gemma 2 9B scores ARC-E: 88.0%, BoolQ: 84.2%, HellaSwag: 81.9%, PIQA: 81.7%, Winogrande: 80.6%. Pixtral Large scores AI2D: 93.8%, DocVQA: 93.3%, ChartQA: 88.1%, VQAv2: 80.9%, MM-MT-Bench: 74.0%.

What are the context window sizes for Gemma 2 9B and Pixtral Large?

Gemma 2 9B supports an unknown number of tokens and Pixtral Large supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemma 2 9B and Pixtral Large?

Key differences include multimodal support (no vs yes), licensing (Gemma vs Mistral Research License (MRL) for research; Mistral Commercial License for commercial use). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemma 2 9B and Pixtral Large?

Gemma 2 9B is developed by Google and Pixtral Large is developed by Mistral AI.