Arena.ai· @arena · X·· 3 小时前AI 评分49
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Agent Arena 过去 14 天近 3 万个任务运行超一小时，平均每个模型发起 332 次工具调用，长周期任务中选对模型最多可省 66% 成本。
正文
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.
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.在 X 查看被引用的帖子
来源：Arena.ai · x.com