Gemma-2|7B
FreeState-of-the-art open models built from Gemini research
FreeFree tier
Inputs: textOutputs: text
About Gemma-2|7B
Gemma is a family of lightweight, state-of-the-art open models from Google DeepMind, built using the same research and technology as the Gemini models. Released in two sizes (2B and 7B parameters), each with pre-trained and instruction-tuned variants, Gemma is designed for responsible AI development and runs on laptops, workstations, or cloud platforms. It includes a Responsible Generative AI Toolkit, supports major frameworks (JAX, PyTorch, TensorFlow via Keras 3.0), and integrates with tools like Hugging Face, Colab, Kaggle, Vertex AI, GKE, NVIDIA GPUs, and Google Cloud TPUs. Commercial usage is permitted under its terms.
Key Features
Two model sizes: Gemma 2B and Gemma 7B
Pre-trained and instruction-tuned variants for each size
Built from the same research and technology as Gemini models
Responsible Generative AI Toolkit with safety classifiers and debugging tools
Toolchains for inference and SFT across JAX, PyTorch, and TensorFlow via Keras 3.0
Ready-to-use Colab and Kaggle notebooks
Integration with Hugging Face, MaxText, NVIDIA NeMo, and TensorRT-LLM
Deployment on Vertex AI and Google Kubernetes Engine (GKE)
Optimized for NVIDIA GPUs and Google Cloud TPUs
Permits responsible commercial usage and distribution
Pros & Cons
Pros
- State-of-the-art performance for its size, surpassing larger models on key benchmarks
- Lightweight enough to run on a developer laptop or desktop
- Built with responsible AI principles, including automated filtering and RLHF alignment
- Uses infrastructure components from the advanced Gemini models
- Free and open with commercial usage allowed for all organizations
Cons
- Limited to relatively small model sizes (2B and 7B parameters) compared to larger LLMs
- Requires substantial compute for fine-tuning or large-scale deployment
- May not match the capabilities of much larger models on complex tasks
Best For
Running state-of-the-art language models on a developer laptop or workstationBuilding responsible AI applications with guided safety toolkitsFine-tuning and inference for research and commercial projectsDeploying LLMs on Google Cloud (Vertex AI, GKE)Experimenting with pre-trained models in Colab or Kaggle notebooks
FAQ
What are Gemma open models?
Gemma is a family of lightweight, state-of-the-art open models from Google DeepMind, built from the same research and technology used to create the Gemini models. They are available in 2B and 7B parameter sizes with pre-trained and instruction-tuned variants.
How do Gemma models differ from Gemini?
Gemma shares technical and infrastructure components with Gemini, Google's largest and most capable AI model, but is designed as a lightweight, open model for developers and researchers.
What sizes and variants are available?
Gemma 2B and Gemma 7B are available, each with a pre-trained and an instruction-tuned version.
What tools and integrations are supported?
Gemma supports toolchains for JAX, PyTorch, and TensorFlow (via Keras 3.0), and integrates with Hugging Face, Colab, Kaggle, MaxText, NVIDIA NeMo, TensorRT-LLM, Vertex AI, GKE, NVIDIA GPUs, and Google Cloud TPUs.
Can I use Gemma commercially?
Yes, the terms of use permit responsible commercial usage and distribution for all organizations, regardless of size.
How does Gemma ensure responsible AI?
Gemma uses automated filtering to remove personal information from training data, extensive fine-tuning and RLHF to align instruction-tuned models, and robust evaluations including red-teaming and adversarial testing. A Responsible Generative AI Toolkit is also provided.