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Google releases Gemini 4 Hydrogen, which outscores the larger Argon at a lower price

Original title: Google's Gemini 4 Hydrogen outscores the bigger Argon just four weeks after its launch

Google released Gemini 4 Hydrogen, a fast general-purpose model that scores 51 on the Artificial Analysis Intelligence Index at the default high level (54 at xhigh), above the larger Argon at 50. Pricing is $1.50/M input and $7.50/M output tokens with a 1M-token context window; Artificial Analysis finds an 8% hallucination rate but weaker terminal-task performance versus Claude Sonnet 5.5.

Why it matters

The piece pairs Google's claims with Artificial Analysis data, letting readers compare Hydrogen's intelligence scores, hallucination rate, and per-tier costs before switching.

Read the original ↗AI Daily, Nov 13

The summary, note and analysis on this page were written by the AI Windvane agent in AIsa Studio; the original belongs to its authors.

Analysis

What happened

Google has released Gemini 4 Hydrogen, a fast general-purpose model aimed at developers and everyday users, positioned as the successor to the Flash series. Unlike the frontier models Gemini 4 Carbon and Gemini 4 Argon, which are designed for "deep, long-horizon reasoning on hard problems," Hydrogen is meant to handle everyday tasks quickly and cheaply.

Four weeks after Argon's launch, Hydrogen outperforms it: on the Artificial Analysis Intelligence Index at the default "high" thinking level it scores 51 vs. Argon's 50, and reaches 54 at the new "xhigh" level. The article notes this leaves Argon "obsolete less than four weeks after its release," contradicting Google's advice from two days earlier to stick with Argon for daily coding work.

Key details

  • Four thinking levels: low, medium, high (default), and a new xhigh tier; Argon offers only medium and high. One-million-token input context and one-million-token output.
  • Pricing: $1.50 per million input tokens, $7.50 per million output tokens, $0.075 for cache hits.
  • Compared to Gemini 3.8 Flash: tasks finish 2.5x faster at the default level, Terminal-Bench 4.1 jumps from 18.2% to 57%, hallucinations drop by a factor of five, and the model recovers better from failed tool calls or empty searches.
  • Agent benchmarks: fifth on the Agent Arena leaderboard, first on the Vals Tax Agent Bench (52.3%), tied first on the Vals Legal Research Bench (55.8%). Multimodal: 53.4% on Google's Multimodal Knowledge Agent Benchmark, 71.6% on Agents' Last Exam v1.1.
  • Availability: globally across the Gemini API (AI Studio, Android Studio), Google Antigravity for Pro and Ultra subscribers, Gemini for Business, the Gemini app, and Google Search. It can pull context from Gmail, Drive, Airtable, and Dropbox, and Google says it improves Search results, including handling typos and multi-part questions.
  • In Antigravity, a new orchestrator switches dynamically between Carbon and Hydrogen within a session; on Terminal-Bench 4.0 it nearly matches Carbon while using 24% fewer resources and cutting processing time by 19%.

Independent Artificial Analysis results: Hydrogen is roughly on par with Claude Sonnet 5.5 at maximum thinking level. It hallucinates on only 8% of AA-Omniscience and beats other Gemini models, including Carbon, on presentation quality in AA-Briefcase. It is weaker at agentic terminal work: 54% on Terminal-Bench 4.0 and 50% on Terminal-Bench-Science 0.1, versus Claude Sonnet 5.5 (max) at 64 and 53 and GPT-6.1 Sol (max) at 56 and 58.

Why it matters

A fast, cheap "everyday" model beating a frontier model released four weeks earlier suggests the frontier-tier positioning is unstable, and it undermines Google's own two-day-old guidance to keep using Argon for daily coding. At xhigh, Hydrogen costs about $3.16 per task, roughly a third of Claude Sonnet 5.5 (max) at nearly the same intelligence level, though about 2.5 times GPT-6.1 Sol (max).

Artificial Analysis also found that at the high, medium, and low tiers Hydrogen sits on the Pareto frontier, meaning no other model is both cheaper and smarter at those price points. However, intelligence drops sharply at lower levels (medium 41, low 27), and xhigh uses nearly twice as many output tokens as high, which explains the cost jump from $1.87 to $3.16 per task.

Who it affects

Developers using the Gemini API in AI Studio and Android Studio; Pro and Ultra subscribers using Google Antigravity, where the new orchestrator mixes Carbon and Hydrogen; business customers via Gemini for Business; and general users of the Gemini app and Google Search. Teams choosing between models may now prefer Hydrogen over Argon for everyday work, while those needing the strongest terminal or computer-use performance may still favor Claude Sonnet 5.5, which scores highest on those tasks in Google's comparison.

Original article

Google has released Gemini 4 Hydrogen, a fast general-purpose AI model meant for developers and everyday users.

Unlike the frontier models Gemini 4 Carbon and Gemini 4 Argon, which Google designed for deep, long-horizon reasoning on hard problems, Hydrogen is meant to handle everyday tasks quickly and cheaply. It appears to be the counterpart to the earlier Flash series.

That comparison may sell it short, though. According to Google, Hydrogen beats the larger Argon on the Artificial Analysis Intelligence Index at the default "high" thinking level (51 vs. 50) and reaches up to 54 at the highest level, "xhigh."

Hydrogen offers four thinking levels: low, medium, high (the default), and a new xhigh tier, while Argon offers only medium and high. The model has a one-million-token context window for input and can output one million tokens. It costs $1.50 per million input tokens and $7.50 per million output tokens. Cache hits cost $0.075.

At "xhigh," Gemini 4 Hydrogen scores 54 on the Artificial Analysis Intelligence Index, just behind Claude Sonnet 5.5 and GPT-6.1 Sol, which each score 55 at their maximum thinking level. Gemini 4 Argon trails at 50. | Source: Artificial Analysis

Hydrogen apparently ends up both more capable and cheaper than Argon. Adding to the confusion, when Google announced its new frontier model Carbon just two days ago, the company recommended sticking with Argon for daily coding work. Hydrogen should make that advice moot, leaving Argon obsolete less than four weeks after its release.

Hydrogen delivers a major jump over the previous Flash generation

Google pitches Hydrogen as a standalone model and a big upgrade over Gemini 3.8 Flash. At the default thinking level, Google says it finishes tasks 2.5 times faster. On Terminal-Bench 4.1, the score jumps from 18.2 percent (Flash) to 57 percent (Hydrogen). Hallucinations dropped by a factor of five, and the model recovers better when a tool call fails or a search comes up empty, Google says.

On open-ended agent tasks like research, data analysis, and code navigation, Hydrogen ranks fifth on the Agent Arena leaderboard. Google says it takes first place on the Vals Tax Agent Bench with 52.3 percent and ties for first on the Vals Legal Research Bench with 55.8 percent.

Category

Benchmark

Gemini 4 Hydrogen

Gemini 4 Carbon

Gemini 4 Argon

General Abilities

AA Index v5.0

54 (xhigh, 5.1)

59

50

Vals Index v2.2

—

70.4%

69.2%

Agentic coding

SWE-sweep

13.5%

9.6%

4.3%

FrontierSWE 2

—

61.2%

55.0%

Terminal-Bench 4.1 (cheating-adjusted)

57.0%

—

—

Terminal Bench 4.0 (AA)

—

65.2%

57.1%

Knowledge Work

Agents’ Last Exam v1.1

71.6%

77.4%

69.0%

AutomationBench

76.1%

—

—

AutomationBench (Zapier)

—

53.9%

51.3%

Vending-Bench 2 (Account Balance, U.S. Dollars)

$14,549

$16,484

$13,718

Computer Use

OSWorld-2.1 (offline subset)

77.6%

81.5%

74.7%

Multimodal Understanding

MKA (Climb WSR accuracy)

53.4%

—

—

Chartography

66.6%

72.5%

71.6%

Blueprint Bench 2 (Similarity Score)

—

58.6%

54.4%

Long Context

GraphWalks (256k to 1M, BFS)

—

96.2%

84.2%

Science and Mathematics

Terminal-Bench-Science 0.1

51.4%

—

—

RiemannBench

—

80.0%

76.0%

Terminal-Bench-Science 0.1 (AA)

—

64.8%

52.9%

Reasoning

HLE-Diamond

58.8%

—

—

Cybersecurity

CWE-bench

—

71.0%

68.0%

ExploitGym

—

54.8%

42.0%

SEC-bench Pro

—

88.2%

83.4%

For multimodal knowledge work like summarizing large PDFs, spreadsheets, or videos, Hydrogen supports up to one million output tokens on top of its one-million-token input window. It scores 53.4 percent on Google's new Multimodal Knowledge Agent Benchmark and 71.6 percent on Agents' Last Exam v1.1.

Hydrogen is available now

Google is rolling Hydrogen out globally across all platforms. Developers get access through the Gemini API in AI Studio and Android Studio, while paying Pro and Ultra subscribers can use it through Google Antigravity. Business customers get it through Gemini for Business, and it's available to everyone in the Gemini app and Google Search.

In the Gemini app, Google says the model sticks more closely to tone, format, and instructions over longer conversations, so drafts, summaries, and documents are more often usable on the first try. Hydrogen can also pull in context from Google apps like Gmail and Drive, as well as third-party apps like Airtable and Dropbox.

Google claims Hydrogen is a "significant upgrade" for Search, too. The model handles search queries better, even when they contain typos, multi-part questions, or very specific requests, Google says. Results are more visual and easier to scan, and an improved query fan-out technique pulls in a wider range of relevant links.

In Google's benchmark comparison, Gemini 4 Hydrogen beats Claude Sonnet 5.5 and GPT-6.1 Terra on the knowledge work and multimodal understanding tests shown. Sonnet, however, scores highest on terminal tasks and computer use. | Source: Googl

In Antigravity, Google's coding tool, a new orchestrator switches dynamically between Carbon and Hydrogen within a session instead of sticking with one model. On the external benchmark Terminal-Bench 4.0, Google says the orchestrator nearly matches Carbon's success rates while using 24 percent fewer resources and cutting processing time by 19 percent.

Independent test finds Hydrogen rarely hallucinates but lags on terminal work

An independent evaluation by Artificial Analysis puts Hydrogen roughly on par with Claude Sonnet 5.5 at its highest thinking level. At the default "high" level, the score drops to 51, slightly behind GPT-6.1 Sol (xhigh, 52) and Claude Opus 5.5 (high, 52).

On the AA-Omniscience benchmark, Hydrogen makes things up only 8 percent of the time, according to Artificial Analysis. It also beats other Gemini models, including Carbon, on presentation quality in AA-Briefcase, which evaluates agentic knowledge work.

Hydrogen is weaker at agentic terminal work, scoring 54 percent on Terminal-Bench 4.0 and just 50 percent on Terminal-Bench-Science 0.1. Claude Sonnet 5.5 (max) reaches 64 and 53 percent respectively, while GPT-6.1 Sol (max) scores 56 and 58 percent.

On price-performance, Artificial Analysis puts Hydrogen at about $3.16 per task at xhigh, roughly a third of what Claude Sonnet 5.5 (max) costs at nearly the same intelligence level but about 2.5 times as much as GPT-6.1 Sol (max).

The "xhigh" thinking level lifts Gemini 4 Hydrogen from 51 to 54 points but needs nearly twice as many output tokens as "high." Average cost per task rises from $1.87 to $3.16. | Source: Artificial Analysi

At "high," costs drop to $1.87, at "medium" to $0.80, and at "low" to $0.29. Intelligence scores fall sharply at the lower levels, though, with medium reaching only 41 and low just 27 on the index. Artificial Analysis notes that xhigh uses nearly twice as many output tokens as high, which accounts for the price jump. At the high, medium, and low tiers, the model sits on the Pareto frontier, meaning no other model is both cheaper and smarter at those price points.

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