A lightweight, open model built as a foundation for creating specialized function calling models.
This model requires a specialized High-VRAM environment. Ensure you have the latest CUDA Drivers or Metal Framework installed.
Minimum VRAM: 9GB VRAM Recommended
The FunctionGemma 9B model by Google is a 9B parameter architecture optimized for code tasks. It requires approximately 6.5GB of VRAM to comfortably run locally using a Q4_K_M quantization. Extending the context window up to 128,000 tokens will dynamically allocate further VRAM, meaning high-bandwidth memory hardware is strictly advised.
For running FunctionGemma 9B at maximum tokens-per-second, we recommend using LM Studio or Ollama with a GGUF quantization (Q4_K_M or Q6_K). If you are multi-GPU, use vLLM to distribute the layers across your VRAM pool for optimal throughput.
You will need a GPU with at least 9GB of VRAM to run the Q4_K_M quantized version smoothly with a moderate context window.
The simplest method is utilizing Ollama by executing 'ollama run functiongemma' directly in your command line. Alternatively, you can search for the model via LM Studio's interface.