Google just rolled out major updates to Gemini API Managed Agents, making Gemini 3.6 Flash the new default model. Developers can now run custom pre- and post-tool scripts inside remote sandboxes to lint or block actions, set hard token limits to stop runaway costs, and test autonomous workflows on a free tier.
Google just integrated computer use directly into its mainstream Gemini 3.5 Flash model, doing away with the standalone Gemini 2.5 experimental setup. Developers can now build agents that observe and act across browser, mobile, and desktop environments out of the box, backed by new prompt injection safeguards and optional approval gates. It gives Google a fast, production-ready competitor in the automated workflow race.
Google just made Gemini Embedding 2 generally available via the Gemini API. The natively multimodal embedding model can search and reason across text, images, video, and audio in a single pipeline, helping developers move complex multimodal search and analysis projects straight into production.
Google just launched Veo 3.1 Lite, its most cost-effective video generation model yet. It delivers the same speed as Veo 3.1 Fast at less than half the cost, supporting text-to-video and image-to-video at up to 1080p. Developers can access it now via Google AI Studio and the Gemini API, with price cuts for Veo 3.1 Fast slated for April 7.
Google just launched Gemini Embedding 2 in public preview, its first natively multimodal embedding model. It maps text, images, audio, up to 120 seconds of video, and PDFs into a single vector space, even handling mixed inputs in one request. Matryoshka Representation Learning lets developers scale dimensions down from 3072 to cut storage costs.
Google just launched File Search, a fully managed RAG pipeline integrated directly into the Gemini API. The tool automates file storage, chunking, vector retrieval, and automated source citations. Google is also waiving storage and query-time embedding fees, charging only a one-time indexing fee of $0.15 per million tokens. Developers can now ground Gemini models in custom documents without wrestling with custom vector databases.
Google just upgraded Structured Outputs in the Gemini API, adding full JSON Schema support that works out-of-the-box with Pydantic and Zod. The update brings support for unions, recursive schemas, and strictly preserves key ordering across Gemini 2.5 models. For developers building multi-agent systems, it means finally putting an end to broken JSON responses in production.
Google just launched the Gemini 2.5 Computer Use model in public preview, letting developers build agents that navigate web and mobile interfaces by clicking, scrolling, and filling out forms. Built on Gemini 2.5 Pro, it tops browser benchmarks with lower latency and step-by-step safety controls. Why it matters: AI can now tackle messy real-world web chores that lack structured APIs.
Google just updated Veo 3 and Veo 3 Fast, bringing lower pricing across the board alongside new support for 9:16 vertical video and 1080p HD outputs. Both video generation models are now marked production-ready in the Gemini API and continue to include SynthID watermarking.
Google just opened its Veo 2 video model to developers through Google AI Studio and the paid Gemini API tier. The model turns text or image prompts into eight-second clips with realistic physics and camera controls. It means apps can now generate commercial-grade motion clips without custom video pipelines.
Google just opened native image generation in Gemini 2.0 Flash to all developers via Google AI Studio and its API. Built from the ground up to output images natively, the model handles multi-turn conversational editing, preserves character consistency across prompts, and renders in-image text far better than typical diffusion models.
Google just launched an experimental text embedding model, gemini-embedding-exp-03-07, through the Gemini API. Trained directly on Gemini, it took the top spot on the MTEB Multilingual leaderboard with a score of 68.32, beating the runner-up by 5.81 points. Developers can try it out immediately using the existing embed_content endpoint.
Google just opened up its flagship Imagen 3 image generation model to developers via the Gemini API. Priced at $0.03 per image, it delivers high-fidelity visuals across styles while embedding SynthID watermarks. Paid API users get access first, with a free-tier rollout coming soon.
Google just added Grounding with Google Search to Google AI Studio and the Gemini API, letting Gemini 1.5 fetch live web answers with inline citations. Testing is free inside AI Studio, while API access runs $35 per 1,000 grounded queries. Why it matters: developers can finally plug Google's web index directly into Gemini without messy custom retrieval pipelines.
Google just slashed Gemini 1.5 Flash pricing, cutting input costs by 78% to $0.075 per million tokens and output by 71% starting August 12. The update also rolls out text tuning to all developers via AI Studio and the Gemini API, alongside native multimodal understanding for image-heavy PDFs.
