Agent Arena 数据显示长程任务模型每小时成本最大相差 66%

Arena.ai· @arena · X·2026-11-05 01:49· 1 小时前AI 评分53

AI 导读

Agent Arena 统计近 14 天近 30000 个任务运行超过一小时，平均模型每小时发起 332 次工具调用。长程任务上模型选择最多可省 66% 成本：Gemini 4 Carbon 每小时任务中位成本 $10.51，Claude Opus 5.5 为 $21.13，GPT-6 Astra 为 $31.08。

正文 · 原文

In the last 14 days, nearly 30,000 tasks ran for over an hour on Agent Arena. Within that hour, the average model made 332 tool calls.

In these long-horizon tasks, the right model choice can cut the cost by up to 66%.

In Agent Arena, an hour of work costs a median $10.51 per task with Gemini 4 Carbon, $21.13 with Claude Opus 5.5 by @AnthropicAI and $31.08 with GPT-6 Astra by @OpenAI.

That makes Gemini 4 Carbon by @GoogleDeepmind 50% cheaper than Opus and 66% cheaper than Astra for an hour-long task.

For long-running jobs, weighing cost against capability becomes critical: Claude Opus 5.5 still scores higher, but costs twice as much per hour of work.

引用Arena.ai@arena

Agent Arena measures complex, real-world tasks. Data shows that these long-horizon sessions amplify differences in frontier models. Long-horizon tasks in Agent Arena span hundreds of turns, from porting a codebase to Rust and auditing an investment strategy document to writing a math textbook, and more. Comparing the top model from each of the 5 leading labs on Agent Arena reveals a 55-minute gap in how long they spend on long-horizon tasks. The models are: - Claude Opus 5.5 by @AnthropicAI - Gemini 4 Carbon by @GoogleDeepMind - GPT-6 Astra by @OpenAI - Muse Wonder Full by @AIatMeta - Kimi K3.1 Pro by @Kimi_Moonshot In this group, Claude Opus 5.5, #1 in Agent Arena, takes the longest at every task length, peaking at 1 hour 51 minutes. In contrast, Kimi K3.1 Pro spends the least time at every length, with 56 minutes on long-horizon tasks.

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来源：Arena.ai · x.com