VFF - The signal in the noise
Model ReleaseTrending

Google DeepMind Releases Gemini 2.0 Ultra with Native Tool Use and Project Astra Integration

Company AnnouncementGoogle DeepMind
Read original
Share
Google DeepMind Releases Gemini 2.0 Ultra with Native Tool Use and Project Astra Integration

Google DeepMind has released Gemini 2.0 Ultra, featuring native tool use, expanded context, and tight integration with Project Astra — the multimodal AI assistant framework. The model sets new benchmarks on video understanding and long-context retrieval.

  • Gemini 2.0 Ultra achieves SOTA on video understanding benchmarks
  • Native tool use allows direct API calling without prompt engineering workarounds
  • 1M token context window with improved long-context accuracy vs Gemini 1.5
  • Project Astra integration enables persistent, multimodal AI assistant capabilities
  • Available in Google AI Studio and Vertex AI today

Gemini 2.0 Ultra strengthens Google's position in the frontier model race after a period where OpenAI and Anthropic had pulled ahead on most benchmarks. The native tool use and Project Astra integration are particularly relevant for developers building agents.

For organizations already in the Google Cloud ecosystem, Gemini 2.0 Ultra's Vertex AI availability makes evaluation straightforward. The video understanding improvements are particularly relevant for media, e-commerce, and content organizations.

  • Google's deep infrastructure integration (Search, Workspace, Cloud) gives Gemini distribution advantages no other model has
  • The native tool use standard could become an important API design pattern
  • Astra's persistent memory capability may set a new UX bar for AI assistants

Watch Google I/O for Gemini integration announcements across Search and Workspace products.

OneUpAI
OneUp Your Business. Get More Done. OneUp Your Business. Get More Done. OneUp Your Business. Get More Done.
Learn More
Share

Subscribe to the newsletter

The latest stories and analysis, delivered to your inbox.

Free. No spam. Unsubscribe any time.

Related stories

OpenAI models arrive on Google Cloud Marketplace

OpenAI models arrive on Google Cloud Marketplace

OpenAI and Google Cloud have partnered to make OpenAI's frontier models and Codex workflows available through Google Cloud Marketplace via Gemini's Model Garden. The integration allows Google Cloud customers to access OpenAI's capabilities within Google's infrastructure and tooling. This represents a significant expansion of OpenAI model availability beyond OpenAI's direct channels.

· OpenAI
Google and Amazon Target Nvidia's Developer Lock-In

Google and Amazon Target Nvidia's Developer Lock-In

Google has released a developer tool enabling PyTorch users to migrate applications away from Nvidia GPUs, following Amazon's similar move into this space. The tool targets a core strength of Nvidia's business: lock-in with AI developers through GPU dependency. This represents a coordinated effort by major cloud providers to reduce developer reliance on Nvidia hardware and create switching pathways to their own silicon and services.

by Julie Bort· TechCrunch AI
Google DeepMind, Singapore build on-device scam detector
TrendingNews

Google DeepMind, Singapore build on-device scam detector

Google DeepMind and Singapore's GovTech have developed a lightweight on-device AI model based on Gemma to detect conversational scams in private messaging without sending data to the cloud. The system intercepts scam attempts in real time while maintaining user privacy through local processing. This collaboration demonstrates a practical application of smaller, efficient AI models for fraud prevention in government and consumer contexts.

· Google Deepmind
Google launches Gemini 4 Argon, tops frontier model benchmarks
TrendingModel Release

Google launches Gemini 4 Argon, tops frontier model benchmarks

Google DeepMind released Gemini 4 Argon, a frontier AI model available globally via API and consumer apps starting October 13, 2026. The model ranks first on the Vals Index for performance across finance, coding, legal, and tax work, with pricing at $2 per million input tokens and $10 per million output tokens. Early deployments at Google show measurable gains in code quality and engineering velocity, including a 35% increase in agentic code submissions and a one-third reduction in rollbacks.

· Google Deepmind