Gemini 4 Hydrogen (High) 亮相 Agent Arena：速度与成本占优
https://t.co/d9shAa5GMh
如果你在挑智能体模型，Hydrogen 值得放进候选清单：速度是 Claude Fable 5.2 的 3 倍，成本不到 GPT-6 Astra 的三分之一，可控性还排第 2。代价是输出 token 烧得多，Code 任务只排第 9。跑高频对话类智能体、对成本敏感的团队可以优先试它。
Google DeepMind 发布的 Gemini 4 Hydrogen (High) 在 Agent Arena 排行榜上首次亮相即位列第 5，基于 6,500 个真实智能体会话评测，净改进幅度达 +14.8%。
速度与成本是它最突出的指标：中位任务耗时 5.3 分钟，是前十名中最快的模型，比排名第 1 的 Claude Fable 5.2 快 3 倍，比 GPT-6 Astra 快 2.4 倍；中位任务成本 $1.6，比 GPT-6 Astra 便宜 3.7 倍，比 Claude Fable 5.1 便宜 4.7 倍。API 定价为每百万 tokens 输入 $1.5、输出 $7.5。代价是输出 token 消耗偏高，比 Carbon 多 41%，是 Argon 的 2.8 倍。
细分信号方面，它在 Steerability（可控性）上以 +21% 排第 2，仅次于 Fable 5.2 的 +33%；Praise vs. Complaint +32% 排第 4，Confirmed Success +15% 排第 5。按任务类别看：Chat 第 3（+19%）、Work 第 7（+13%）、Code 第 9（+12%），整体呈现对话能力强于编程能力的分布。
https://t.co/d9shAa5GMh
x.com/arena/status/2… Arena.ai @arena Gemini 4 Hydrogen (High) by @GoogleDeepMind debuts #5 on Agent Arena with +14.8% net improvement across 6.5k real-world agentic sessions. Hydrogen stands out for its speed and cost efficiency: - Fastest model in the top 10: 5.3 min/task (median), 3x faster than #1 Claude Fable 5.2 and 2.4x faster than GPT-6 Astra - Cost-efficient: $1.6 cost/task (median), 3.7x cheaper than GPT-6 Astra and 4.7x cheaper than Claude Fable 5.1. API token pricing: $1.5/$7.5 input/output per million tokens Notably, it spends more output tokens per task: 41% more than Carbon, 2.8x more than Argon. Strong across key signals: - #2 Steerability: +21% (behind only Fable 5.2 at +33%; ahead of Carbon at +19% and Opus 5.5 at +18%) - #4 Praise vs. Complaint: +32% - #5 Confirmed Success: +15% Ranking by task category: - #3 in Chat: +19% - #7 in Work: +13% - #9 in Code: +12% Hydrogen delivers competitive performance while completing tasks significantly faster and at a fraction of the cost of several leading models. Congrats to the @GoogleDeepMind team on another impressive release! 🔗 View Quoted Tweet📊 2 ⚡
This report is categorized under AITOP's "Models" desk, focusing on US frontier AI labs and Silicon Valley technology leaders. Within our cross-regional analytical framework, it directly maps to US-China foundation model benchmarks and commercialization comparison and AI developer toolchains, coding agents, and engineering workflows. Key entities and technical topics under continuous tracking include Gemini 4 Hydrogen, Google DeepMind, Agent Arena, Claude.
Source attribution: curated from lmarena.ai (@lmarena_ai). Cross-source corroboration: 11 independent sources have covered this development (including Artificial Analysis, Philipp Schmid, IT之家), confirming industry-wide signal strength.
