Google launches Gemini 4 Hydrogen, a $1.50-per-million-token model for coding and agents
Google has released Gemini 4 Hydrogen, a faster and cheaper tier of its Gemini 4 family aimed at everyday coding and agentic work. It costs $1.50 per million input tokens and $7.50 per million output tokens across a 1M-token window, and is rolling out through the Gemini API, AI Studio and consumer products.
Google announced Gemini 4 Hydrogen on 12 November, positioning it as the "daily driver" for agentic workflows beneath its frontier siblings, Gemini 4 Carbon and Argon, which are built for deep, long-horizon reasoning.
Pricing is flat at $1.50 per million input tokens and $7.50 per million output tokens across the full one-million-token context window. The model offers low, medium, high (the default) and a new xhigh thinking level.
Google's own figures put Hydrogen at 51 on the Artificial Analysis Intelligence Index at high effort, against 50 for Argon, rising to 54 at xhigh. It reports 57 per cent on Terminal-Bench 4.1, up from 18.2 per cent for Gemini 3.8 Flash, and 58.8 per cent on HLE-Diamond. These are vendor-reported results and have not been independently reproduced here.
Google says the model finishes tasks around 2.5 times faster than 3.8 Flash at its default setting. In its Antigravity tool, an orchestrator can switch between Carbon and Hydrogen within a session, which Google says reached near-Carbon success on Terminal-Bench 4.0 while using about 24 per cent less quota.
On safety, Google reports up to 81 per cent less agentic overreach and 2.3 times greater resistance to indirect prompt injection than 3.8 Flash. Availability is global from launch via the Gemini API, Google AI Studio, Android Studio, Gemini for business, Google Sheets, Search and the Gemini app.
Why it matters
The release continues the pattern of frontier-adjacent capability arriving in a cheaper, faster tier within weeks. For teams running agent workloads, token cost and latency, not peak intelligence, usually decide what reaches production.
Flat pricing across the full context window also removes a common budgeting surprise for long-running agents.
Indicops view
Indian enterprises and government teams piloting agents should benchmark Hydrogen against their incumbent model on their own workloads, and route simple steps to the cheaper tier while reserving frontier models for hard reasoning.
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