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AI

Google DeepMind introduces Gemini 4 Hydrogen for fast agentic workflows

2026-11-13

Illustrative stock photograph, not the reported people, event or location.

Google introduced Gemini 4 Hydrogen on November 12 for everyday coding, repository debugging, web development and other tasks carried out by AI agents. Its model card describes four configurable thinking levels and distribution through the Gemini app and API, AI Studio, Gemini for business, Antigravity, Google Sheets and Search. Availability and access conditions differ by product.

Published launch pricing is US$1.50 per million input tokens and US$7.50 per million output tokens. Google reports a score of 51 on the Artificial Analysis Intelligence Index at the default high thinking level. Its model card lists 57 percent on the cheating-adjusted Terminal-Bench4.1 evaluation. These are reported benchmark results, not a guarantee of performance on a customer's codebase.

Antigravity's Orchestrator can switch between models for different steps. Google says Hydrogen is intended for rapid execution alongside more reasoning-focused models. The model card still lists hallucinations, occasional slowness and timeouts among known limitations. Users should review code and outputs before relying on them.

Update: one-million-token context and Search rollout

Updated November 14, 2026. The launch information also specifies a one-million-token context window at the quoted US$1.50 input and US$7.50 output price per million tokens. A separate November 12 Search announcement says Hydrogen is available globally in Search, with improved handling of complex questions, more visual responses and links. Global rollout does not mean every feature is identical across products or subscription plans.

For businesses, the practical question is whether a stronger planning model plus a faster execution model completes work more reliably and cheaply than one model alone. Compare both approaches on representative tasks and record successful completion, total cost, latency and recovery from failures. Benchmark rankings alone do not answer those questions. Publishers and small businesses should likewise examine actual referrals and conversions as Search answer formats change, rather than assume that more visual answers and links will necessarily increase traffic.

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