LightweightOpen SourceGoogle

Gemma 2 9B

Gemma 2 9B is Google's open-source lightweight model designed for efficient text generation with an 8K token context window.

Context 8K
Tier Lightweight
Knowledge Feb 2024
License Open Source
Input from
$0.030 / 1M tokens
across 1 provider
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API Pricing

ProviderInput / 1MOutput / 1MUpdated
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OpenRouter
$0.030$0.0904/14/2026

Prices updated daily. Last check: 4/14/2026

Model Details

General

Creator
Google
Family
Gemma
Tier
Lightweight
Context Window
8K
Knowledge Cutoff
Feb 2024
Modalities
Text

Capabilities

Tool Calling
No
Open Source
Yes
Subtypes
Chat Completion

Strengths & Limitations

  • Open source with model weights available for download and local deployment
  • Lightweight 9B parameter architecture enables faster inference and lower resource requirements
  • 8,192 token context window suitable for most standard text generation tasks
  • Part of Google's second-generation Gemma series with performance improvements over original Gemma
  • No usage restrictions for commercial applications unlike some open-source alternatives
  • Compatible with popular inference frameworks and deployment platforms
  • Lower computational costs compared to larger proprietary models
  • No tool calling or function execution capabilities
  • Text-only modality with no image or multimodal input support
  • Knowledge cutoff of February 2024 limits access to recent information
  • Smaller context window compared to frontier models with 200K+ token windows
  • Limited reasoning capabilities compared to larger models in the 70B+ parameter range

Key Features

•8,192 token context window
•Chat completion interface
•Open source model weights
•Text generation and understanding
•Streaming response support
•Local deployment capability
•Commercial usage licensing
•Framework compatibility (Transformers, vLLM, etc.)

About Gemma 2 9B

Gemma 2 9B is Google's lightweight model in the Gemma family, positioned as an open-source alternative for developers seeking efficient text generation capabilities. As part of Google's second-generation Gemma series, it offers improved performance over the original Gemma models while maintaining a compact 9 billion parameter architecture. The model supports text-only interactions through chat completion with an 8,192 token context window and a knowledge cutoff of February 2024. Gemma 2 9B is designed for straightforward text generation tasks without advanced features like tool calling or multimodal capabilities, focusing instead on delivering reliable language understanding and generation within its parameter constraints. As an open-source model, Gemma 2 9B enables developers to run inference locally or deploy on their own infrastructure, making it suitable for applications requiring data privacy, cost control, or offline operation. Its lightweight architecture allows for faster inference and lower computational requirements compared to larger models in Google's portfolio.

Common Use Cases

Gemma 2 9B is well-suited for applications requiring efficient text generation without the complexity of advanced AI capabilities. Its lightweight architecture makes it ideal for content generation, text summarization, basic question answering, and conversational interfaces where response speed and computational efficiency are priorities. The open-source nature enables use cases requiring local deployment, such as privacy-sensitive applications, offline environments, or scenarios where data cannot leave organizational boundaries. Development teams can leverage Gemma 2 9B for prototyping, fine-tuning on domain-specific data, or building cost-effective text generation services that don't require the advanced reasoning capabilities of larger frontier models.

Frequently Asked Questions

How much does Gemma 2 9B cost per million tokens?

Gemma 2 9B pricing varies by provider and deployment method. Since it's open source, you can also run it locally without per-token costs. Check the pricing table above for current rates across cloud providers offering hosted inference.

What is Gemma 2 9B best used for?

Gemma 2 9B excels at efficient text generation tasks including content creation, summarization, basic question answering, and conversational interfaces. Its lightweight architecture makes it particularly suitable for applications prioritizing speed, cost efficiency, or local deployment requirements.

Can I run Gemma 2 9B locally or do I need to use an API?

Gemma 2 9B is open source, so you can download the model weights and run it locally using frameworks like Transformers, vLLM, or Ollama. This enables offline usage, complete data privacy, and eliminates per-token costs, though you'll need adequate hardware to handle the 9B parameter model.