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.
Model page: Gemma 4 26B A4B →
Introducing Support for Local AI Models in the Antigravity SDK
developers.googleblog.com · 23 September 2026
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