Models & Labs
Gemini API Introduces Webhooks for Long-Running Jobs
Google AI Bloghigh confidence
Why it matters
- →Webhooks reduce the need for inefficient polling, saving resources and time.
- →Secure and reliable communication is ensured with signed requests and retries.
- →Developers can manage complex workflows more efficiently with real-time notifications.
Google has enhanced its Gemini API by introducing event-driven Webhooks, aimed at improving efficiency for long-running tasks. This new feature allows developers to receive immediate notifications when a job is completed, replacing the need for continuous polling. The Webhooks implementation is secure, adhering to the Standard Webhooks specification, and includes features like signed requests and automatic retries. This update is designed to support complex workflows, making it easier for developers to manage tasks such as deep research and batch processing.
Read originalThe story around this
Earlier coverage that leads up to this article, and what followed. Lines connect each piece to the closest one after it, converging here.
More in Models & Labs
Models & Labsmodels
llama.cpp b12029 adds CUDA 13 and Snapdragon support
This release quietly cements llama.cpp as the universal inference runtime by finally supporting NVIDIA's latest CUDA 13 stack alongside AMD's ROCm 10.0. The inclusion of native builds for Linux arm64 with Snapdragon chips, covering CPU, Adreno GPU, and Hexagon NPU, signals a serious push into mobile edge deployment. While Apple Silicon KleidiAI is disabled in this specific build, the broader hardware coverage means developers no longer need to compile from source for most modern accelerators. It’s less about new features and more about removing friction for anyone running local models on bleeding-edge or diverse hardware.
llama.cpp Releases
© The Verge AIModels & Labsother
