Google Antigravity SDK adds support for local Gemma 4 26B models
Google has announced that the Antigravity SDK now supports local AI workflows, enabling developers to run agentic capabilities entirely offline. The initial release features support for the Gemma 4 26B A4B model using Google AI Edge’s LiteRT runtime. This update allows developers to leverage local GPU and RAM resources for private, on-device inference without relying on cloud services.
Key points
- Antigravity SDK now supports offline agentic workflows using Gemma 4 26B A4B via LiteRT.
- A hybrid demo uses Gemini 3.8 Flash for planning and local Gemma 4 26B for execution.
- The SDK supports OpenAI-compatible servers like Ollama and vLLM for flexible local inference.
The SDK includes an "Architect-Builder" pattern where a cloud-based model, such as Gemini 3.8 Flash, acts as a planner, while a local swarm of Gemma 4 26B instances executes tasks. In a demo, this hybrid approach audited and patched vulnerable Python modules while maintaining strict data privacy. The local model also demonstrated the ability to autonomously write, test, and deploy a live-updating terminal resource monitor using a single prompt.
For flexibility, the SDK offers plug-and-play support for any OpenAI-compatible server, including Ollama, LM Studio, and vLLM. This allows developers to switch inference backends without changing their agent orchestration code. Google recommends a machine with 24GB of VRAM or unified memory for optimal performance. Developers can access the updated SDK and example projects via the Antigravity Python SDK repository.
Introducing Support for Local AI Models in the Antigravity SDK
developers.googleblog.com · 23 September 2026
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