Gemini 4 Hydrogen

Introducing Gemini 4 Hydrogen Nov 12, 2026 | x.com Facebook LinkedIn Mail Copy link Hydrogen brings cutting-edge intelligence to everyone. Koray Kavukcuoglu SVP, Google DeepMind and Chief AI Architect, Google Share x.com Facebook LinkedIn Mail Copy link Your browser does not support the audio element. Listen to article [[duration]] minutes This content is generated by Google AI. Generative AI is experimental Voice Speed Voice Speed 0.75X 1X 1.5X 2X In this article Today, we’re introducing Gemini 4 Hydrogen, bringing cutting-edge intelligence to everyone — with speed and efficiency for everyday coding and agentic workflows. While our frontier models, Gemini 4 Carbon and Gemini 4 Argon , excel at deep, long-horizon reasoning on your hardest problems, Hydrogen is built for rapid execution across diverse agentic workflows. With Hydrogen, we’re also bringing Gemini 4 to everyone — for all tiers of Google AI Studio , the Gemini API, Gemini for business , the Gemini app , Google Search , and paid Google AI Pro and Ultra subscribers in Google Antigravity . Hydrogen surpasses Argon on the Artificial Analysis Intelligence Index at its default high thinking level (51 vs. 50, and reaching 54 at its highest xhigh thinking setting), while often completing tasks faster than models in its class. Gemini 4 Hydrogen is priced flat across its entire 1 million-token context window at $1.50 per million input tokens and $7.50 per million output tokens. Unlocking efficiencies in multi-model workloads In real-world software development, while teams rely on frontier models like Carbon and Argon for deep architectural judgment when designing systems or untangling subtle bugs, they still need a fast, disciplined execution model for writing code, running tests, and verifying changes. Hydrogen is built to stand on its own as a model for everyday work — or to pair with Carbon and Argon as the high-efficiency execution engine in multi-model workflows. To help make this multi-model collaboration automatic, we’re introducing Orchestrator in Google Antigravity . Rather than using a single model from start to finish, Orchestrator dynamically switches between models like Carbon and Hydrogen within the same session. On Terminal-Bench 4.0 , Orchestrator reached near-Carbon task success rates while, on average, consuming 24% less quota and completing 19% faster. For workflows that require parallel agents, Carbon can act as the coordinator while Hydrogen can power worker and verifier agents to build and test changes simultaneously across isolated workspaces — helping teams ship complex projects faster without driving up token costs. Scaling developer and enterprise workflows Beyond multi-model workflows, Hydrogen is a major standalone upgrade for teams migrating from Gemini 3.8 Flash. It delivers significant leaps in both speed and intelligence — finishing tasks 2.5 times faster at its high default setting while more than tripling Terminal-Bench 4.1 scores (57% vs. 18.2%), cutting fabricated claims by more than 5x, and adapting cleanly when a tool call fails or a search returns empty. It also matches or outperforms competing models in its class across core developer and enterprise workflows: Iterative repository coding and debugging: Hydrogen handles issue resolution, debugging, rapid iteration, and codebase Q&A with focused, surgical edits — delivering cleaner, production-ready code without rewriting unrelated files. It outperforms similar-tier models on SWE-sweep where it has to discover and repair bugs without breaking existing code. To explore large repositories efficiently, the model excels at natively batching file-read and search calls in parallel rather than inspecting files one by one; in early testing across complex graphs, SQL, and data-heavy enterprise workflows, our partners have seen Hydrogen run 2x to 2.8x faster while reducing token usage by 12% to 23%, compared to 3.8 Flash. Open-ended agentic execution: On multi-step tasks like deep research, data analysis, and broad codebase navigation, Hydrogen ranks #5 on Agent Arena , arena.ai’s live benchmark. For deep domain reasoning and analysis, it leads its class on HLE-Diamond (58.8%), ranks #1 overall on Vals Tax Agent Bench (52.3%), ties for #1 on the Vals Legal Research Bench (55.8%), and leads its class on AutomationBench-AA . Multimodal knowledge work: Hydrogen pairs native 1 million-token input with up to 1 million output tokens to synthesize dense PDFs, spreadsheets, charts, audio, and recorded video into polished, cited reports and structured deliverables. It outperforms other models on the new Multimodal Knowledge Agent (MKA) benchmark (53.4%) for end-to-end agentic knowledge work over complex visual files, and on Agents’ Last Exam v1.1 (71.6%) for end-to-end professional workflows. Web development : On tasks where speed matters to developers, like live UI prototyping, design-to-code iteration, and interactive app building, Hydrogen generates more functional, feature-complete layouts in fewer prompts. Using Hydrogen for on-the-fly 3D coding, Geminisland lets anyone add to a shared voxel island from a single prompt to generate custom structures live on the map that players can walk around and explore in first person. Try the live app. Paired with our new Gemini front end design skill in Google Antigravity, Hydrogen built an e-commerce storefront in one shot complete with a WebGL2 topographic shader, pinned four-stage scrollytelling, a thermal split-slider, a 3D wireframe spec card, and a live finish configurator. Try the live app and Gemini front end design skill . In Google Antigravity, Hydrogen turned Google Sheets into an animated pixel canvas by shrinking thousands of cells combining Python, native =LET(...) formulas, and conditional formatting to paint and animate full-motion scenes directly inside a live spreadsheet. Starting from a YouTube keynote video and a design template in Google Antigravity, Hydrogen generated a multi-slide presentation directly in Google Slides, then ran an autonomous audit-and-fix loop to catch overlapping text and clean up every slide layout. With Gemini in Google Sheets, Hydrogen can help teams rapidly turn financial data into interactive models that dynamically adjust based on various forecasting scenarios, generating outputs over 30% faster than previous models in Sheets canvas. Adaptable speed and intelligence across four thinking levels We built Gemini 4 Hydrogen for real-world usability. Hydrogen’s four thinking levels — low, medium, high (default), and a new xhigh tier — offer a wide range of options across quality, latency, and cost, scaling in a smooth, predictable progression so you only wait and pay for the reasoning depth a task requires. Across thinking levels, Hydrogen matches or outperforms some of the competing models in its class while often finishing tasks faster and using fewer output tokens. Fast, everyday help in the Gemini app and Search For consumers, Gemini 4 Hydrogen makes it easier to get things done, staying on track and following instructions more closely across multi-turn conversations. In the Gemini app, Hydrogen makes your everyday assistant even more helpful — it’s better at following your guidance, calling the right tools, and getting you to a reliable output with less back-and-forth. Ready-to-go writing, research, and everyday work: Hydrogen sticks closely to your tone, format, and specific rules, so email drafts, study guides, rewrites, and documents come back ready to use on the first try. When you are comparing products or synthesizing dense material, it pulls together clear tables and visual breakdowns without dropping key details. Connects the dots and gets more tasks done: Hydrogen breaks down your goal step-by-step, pulling relevant context from your uploads, Google apps like Gmail and Google Drive, and Connected Apps like Airtable and Dropbox. When you