Google•Rank #20NEW

Gemini 4 Hydrogen

Proprietarygeneralreasoningcodingagentfast

Leaderboard Score

58.2

Scale: 0 - 100

Throughput Speed

145 tps

Context Window

API Pricing / 1M

.00

Parameter Scale

Proprietary

Monthly API Cost Calculator

Gemini 4 Hydrogen rates: $1.5/1M input • $7.5/1M output. Pick a workload preset or enter your own token volumes.

Monthly input (M tokens)Monthly output (M tokens)

Same workload on published-rate alternatives

Kimi K3 (Moonshot AI)

Claude Sonnet 4.6 (Anthropic)

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Estimates use listed API rates at time of writing; providers may differ in caching discounts, rate limits, and batching pricing.

Sourced AI Radar & Benchmarks•8 Evaluated Metrics

Capability Radar & Benchmark Scores

Multi-Axis Capability Radar

Comparing Gemini 4 Hydrogen against Frontier Top 10 & Open-Source average

0 - 100 Scale

Gemini 4 Hydrogen

Frontier Top 10 Avg

Open-Source Avg

Performance Vectors

Where Gemini 4 Hydrogen Leads

Coding & SWETop 10: 79.2% • OS: 51.6%

76.5%-2.7% vs Top 10

Reasoning & MathTop 10: 94.6% • OS: 54.3%

92.4%-2.2% vs Top 10

Agent & Tool AutomationTop 10: 80.3% • OS: 37.4%

66.5%-13.8% vs Top 10

Terminal & CLI ExecutionTop 10: 63.5% • OS: 45.8%

54.0%-9.5% vs Top 10

MMLU & Knowledge QATop 10: 50% • OS: 86.7%

72.8%+22.8% vs Top 10

Cyber & Security ExploitsTop 10: 87.3% • OS: 81.2%

55.3%-32.0% vs Top 10

All Verified Benchmark Evaluations

Direct Pass@1 and resolution rates across standardized evaluations.

OverallCodingReasoningAgenticTerminal

Featured Compute Platform

Run Benchmarks on Dedicated AI Clusters

Zero-cold-start inference endpoints with dedicated GPU instances.

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Executive Analysis & Verdict

Gemini 4 Hydrogen by Google DeepMind is a high-speed agentic workhorse model scoring 58.2 overall, delivering 54 on AA Index v5 (Xhigh) and 145 tokens per second across a 1M token context.

Key Strengths & Highlights

•High-efficiency architecture completing multi-step agentic tasks 2.5x faster
•Configurable reasoning effort (Low, Medium, High, Xhigh) reaching 54 on the AA Index v5
•Unified multimodal context across text, code, audio, video, and documents

Limitations & Considerations

•Reasoning tokens are billed as output tokens under standard API tiers

Recommended Workflows

High-throughput coding agent subtasks, automated test debugging, and real-time multimodal data extraction

Architectural Overview & Capability Profile

Gemini 4 Hydrogen is Google DeepMind’s high-efficiency workhorse foundation model, introduced on November 12, 2026 to succeed the Flash tier in the Gemini family. Engineered to operate as an ultra-fast standalone model or as a high-throughput sub-agent coordinated alongside Gemini 4 Carbon and Argon, Gemini 4 Hydrogen scores an overall 58.2 / 100 on RankLLMs’s calibrated evaluation framework.

Featuring a 1,000,000-token unified multimodal context window capable of processing hours of audio, long video sequences, high-resolution imagery, and million-line codebases, Gemini 4 Hydrogen introduces configurable thinking levels (Low, Medium, High, and Xhigh) that enable developers to balance latency and reasoning depth dynamically per request.

Benchmark Performance: Speed, Coding & Intelligence

In evaluation benchmarks published across Google DeepMind, Artificial Analysis, and Vals AI, Gemini 4 Hydrogen establishes impressive efficiency milestones:

Artificial Analysis Intelligence Index v5.0:
- Scores 51 on default High effort and surges to 54 under Xhigh effort—outpacing previous-generation fast tiers (such as Gemini 3.8 Flash at 31) and rivaling early 2026 frontier flagships.
Coding & Data Analytics:
- PlotlyDataAnalyticsBench: Achieves a perfect 43/43 (100%), generating verified interactive visualizations and regression models from complex datasets.
- Terminal-Bench 4.1: Demonstrates significant improvements in CLI task execution and shell tool call reliability compared to earlier flash tiers.
Execution Latency:
- Completes multi-step agentic workflows 2.5x faster than predecessors, with streaming throughput clocking in at 145 tokens per second at steady state.

API Pricing & Token Economics

Gemini 4 Hydrogen is available via Google AI Studio, Vertex AI, and OpenRouter:

Input Pricing: $1.50 per 1M tokens.
Output Pricing: $7.50 per 1M tokens (inclusive of response and reasoning tokens).
Prompt Caching: $0.075 per 1M tokens for cached prompt reads, providing an economical foundation for repetitive agent loops.

Frequently Asked Questions About Gemini 4 Hydrogen

What is Gemini 4 Hydrogen and who developed it?↓

Gemini 4 Hydrogen is a proprietary large language model developed by Google. It ranks #20 on the RankLLMs composite leaderboard, ahead of 83% of the 104 models we track, with an overall score of 58.2 / 100.

Can Gemini 4 Hydrogen handle very long documents and codebases?↓

Gemini 4 Hydrogen supports a 1.0M-token input context window and generates about 145 tps tokens per second in our reference measurements and which is enough to hold entire repositories, long transcripts, or multi-document research sets in a single session..

Why does Gemini 4 Hydrogen cost more than most alternatives?↓

Gemini 4 Hydrogen sits in the premium tier at .00 per 1M tokens - cheaper than only 82% of priced models we track. That pricing buys frontier-tier benchmark results; the cost-per-solved-task math in our best-coding-LLM guide shows when it pays off.

What is Gemini 4 Hydrogen best at?↓

Gemini 4 Hydrogen is strongest in High-efficiency architecture completing multi-step agentic tasks 2.5x faster; Configurable reasoning effort (Low, Medium, High, Xhigh) reaching 54 on the AA Index v5; Unified multimodal context across text, code, audio, video, and documents. Full pillar-by-pillar numbers are in the benchmark tables above.

What should you watch out for with Gemini 4 Hydrogen?↓

Known trade-offs include: Reasoning tokens are billed as output tokens under standard API tiers. Weigh these against the strengths above for your specific workload.