Google Enters the Agentic Era With Gemini 3.5 and Omni
Google announced Gemini 3.5 for agent reasoning and coding, plus Gemini Omni for multimodal generation, at I/O 2026—marking a shift toward proactive AI systems integrated across hardware and apps.
Last verified:
Gemini 3.5 and Omni Mark Google’s Shift to Agent-First AI
Google announced Gemini 3.5 and Gemini Omni during its May 2026 events, positioning the company in what executives call the “agentic” AI era. According to the Google AI Blog, Gemini 3.5 is optimized for agent reasoning and coding tasks, while Gemini Omni expands the model family’s capabilities to multimodal generation—accepting images, audio, video, and text as input to produce video output grounded in real-world knowledge. The announcements span hardware, software, and wellness applications, signaling Google’s intent to embed AI agents across consumer and enterprise workflows.
Hardware Expansion and Consumer Integration
Google introduced the Googlebook and Fitbit Air as new hardware platforms designed to integrate with the updated Gemini tools. According to the Google AI Blog, these devices aim to support the new agentic capabilities across daily tasks. The company also launched the Google Health app, positioned as a personal wellness hub that consolidates health tracking and proactive recommendations. The announcement recap emphasizes that these products are meant to make AI “more proactive, helpful and integrated into your everyday life,” though specific benchmark performance or capability claims were not included in the May announcement summary.
Multimodal Generation Without Benchmark Disclosure
Gemini Omni’s multimodal input-to-video capability represents a technical step beyond Gemini’s prior text-centric generation. The Google AI Blog describes the model as able to combine images, audio, and text “as input and generate high-quality videos grounded in Gemini’s real-world knowledge.” However, Google did not publish comparisons against competitors’ multimodal models (such as OpenAI’s GPT-4V or Anthropic’s Claude Sonnet 4.6’s vision capabilities) or against its own prior Gemini versions on standard video-generation benchmarks. The absence of published eval results limits independent assessment of the claimed improvements.
Why This Matters
Enterprise and consumer teams deciding between Google’s Gemini, OpenAI’s o1, and other agentic platforms cannot yet compare Gemini 3.5’s coding performance on published benchmarks—a gap that matters for teams evaluating agent frameworks for production deployment. Google’s emphasis on hardware integration (Googlebook, Fitbit Air) suggests a bet on device-native AI rather than API-only consumption, which may influence architecture decisions for teams already invested in the Google ecosystem. The lack of independent reproduction of Gemini Omni’s video-generation quality against existing tools means early adoption will rely on user experience rather than published metrics.
Frequently Asked Questions
What is Gemini 3.5 designed to do differently from earlier Gemini versions?
According to the Google AI Blog, Gemini 3.5 is optimized for agent reasoning and coding tasks, marking Google's entry into what the company calls the 'agentic Gemini era.'
Can Gemini Omni accept multiple input types?
Yes. The Google AI Blog reports that Gemini Omni accepts images, audio, video, and text as input and generates high-quality videos grounded in real-world knowledge.
What new hardware did Google announce alongside these models?
Google announced the Googlebook and Fitbit Air as new hardware designed to work with the updated Gemini tools, though the full technical specifications were not detailed in the May announcement recap.
How does Gemini 3.5 compare to OpenAI's o1 on coding benchmarks?
The Google AI Blog did not publish a direct benchmark comparison. Independent third-party evaluation remains pending.