---
title: Google Gemma 2 9B — Fast Open LLM | ModelsLab
description: Generate text with Google Gemma 2 9B. Fast, efficient open-source LLM for content creation, reasoning, and code. Try it now.
url: https://modelslab.com/google-gemma-2-9b
canonical: https://modelslab.com/google-gemma-2-9b
type: website
component: Seo/ModelPage
generated_at: 2026-04-15T03:52:09.695651Z
---

Available now on ModelsLab · Language Model

Google: Gemma 2 9B
Efficient reasoning. Open weights.
---

[Try Google: Gemma 2 9B](/models/open_router/google-gemma-2-9b-it) [API Documentation](https://docs.modelslab.com)

Deploy Fast. Scale Smart.
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Class-Leading Performance

### Outperforms Llama 3 8B

Delivers results across reasoning, knowledge, and code generation benchmarks.

Inference Efficiency

### Single GPU Deployment

Runs full precision on H100, A100, or TPU with minimal computational overhead.

Versatile Applications

### Content to Code Generation

Handles poetry, copywriting, summarization, question answering, and chatbot workflows.

Examples

See what Google: Gemma 2 9B can create
---

Copy any prompt below and try it yourself in the [playground](/models/open_router/google-gemma-2-9b-it).

Product Description

“Write a compelling product description for a minimalist wireless headphone. Include key features like 30-hour battery life, active noise cancellation, and premium materials. Keep it under 150 words.”

Code Generation

“Generate a Python function that validates email addresses using regex. Include error handling and return True for valid emails, False otherwise.”

Content Summarization

“Summarize the following technical documentation into 3 key takeaways for a developer audience: \[paste documentation\]. Focus on practical implementation details.”

Reasoning Task

“A store sells apples at $2 each and oranges at $3 each. If someone buys 5 apples and 4 oranges, what's the total cost? Show your work step-by-step.”

For Developers

A few lines of code.
Nine billion parameters. Three lines.
---

ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed.

- **Serverless:** scales to zero, scales to millions
- **Pay per token,** no minimums
- **Python and JavaScript SDKs,** plus REST API

[API Documentation ](https://docs.modelslab.com)

PythonJavaScriptcURL

Copy

```
<code>import requests

response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
  "key": "YOUR_API_KEY",
  "prompt": "",
  "model_id": ""
}
)
print(response.json())</code>
```

FAQ

Common questions about Google: Gemma 2 9B
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[Read the docs ](https://docs.modelslab.com)

### What is Google Gemma 2 9B?

### How does Gemma 2 9B compare to other open models?

### What are the key technical features?

### Can I run Gemma 2 9B locally?

### What are common use cases?

### Is Gemma 2 9B open source?

Ready to create?
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Start generating with Google: Gemma 2 9B on ModelsLab.

[Try Google: Gemma 2 9B](/models/open_router/google-gemma-2-9b-it) [API Documentation](https://docs.modelslab.com)

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*This markdown version is optimized for AI agents and LLMs.*

**Links:**
- [Website](https://modelslab.com)
- [API Documentation](https://docs.modelslab.com)
- [Blog](https://modelslab.com/blog)

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*Generated by ModelsLab - 2026-04-15*