←Back to feed
🧠 AI🔴 BearishImportance 7/10
CostBench: Evaluating Multi-Turn Cost-Optimal Planning and Adaptation in Dynamic Environments for LLM Tool-Use Agents
arXiv – CS AI|Jiayu Liu, Cheng Qian, Zhaochen Su, Qing Zong, Shijue Huang, Bingxiang He, Yi R. Fung|
🤖AI Summary
Researchers introduce CostBench, a new benchmark for evaluating AI agents' ability to make cost-optimal decisions and adapt to changing conditions. Testing reveals significant weaknesses in current LLMs, with even GPT-5 achieving less than 75% accuracy on complex cost-optimization tasks, dropping further under dynamic conditions.
Key Takeaways
- →CostBench introduces the first comprehensive benchmark focused on economic reasoning and cost-optimal planning for AI agents.
- →Current AI agent evaluations overlook critical resource efficiency and adaptability capabilities in favor of simple task completion.
- →Even advanced models like GPT-5 struggle with cost-optimization, achieving less than 75% accuracy on the most challenging tasks.
- →Performance drops approximately 40% when agents must adapt to dynamic conditions like tool failures and cost changes.
- →The benchmark reveals a substantial gap between current AI capabilities and real-world economic decision-making requirements.
Mentioned in AI
Models
GPT-5OpenAI
#ai-agents#benchmarking#cost-optimization#llm-evaluation#economic-reasoning#adaptive-planning#gpt-5#performance-analysis
Read Original →via arXiv – CS AI
Act on this with AI
Stay ahead of the market.
Connect your wallet to an AI agent. It reads balances, proposes swaps and bridges across 15 chains — you keep full control of your keys.
Related Articles