Google: Gemma 2 9B
Efficient reasoning. Open weights.
Deploy Fast. Scale Smart.
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.
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
import requestsresponse = requests.post("https://modelslab.com/api/v7/llm/chat/completions",json={"key": "YOUR_API_KEY","prompt": "","model_id": ""})print(response.json())
Ready to create?
Start generating with Google: Gemma 2 9B on ModelsLab.