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The Best AI Models for Agents: Planning vs. Cost Audit

AI agents require reliable planning, structured JSON outputs, and accurate tool-calling. Let's evaluate major models across these capabilities to identify the best options for agent architectures.

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1. Function-Calling Accuracy Benchmarks

Claude 3.5 Sonnet and GPT-4o lead in function-calling accuracy, successfully parsing parameters and complying with structural constraints, which reduces retry loops.

2. Caching Economics for Agent Memory

Agents carry conversation history, which increases token costs. Claude 3.5 Sonnet's 90% prompt caching discount makes it highly cost-effective for long sessions.

3. Open Weights Alternatives for Agents

For budget-friendly setups, Llama 3.3 70B and Qwen 2.5 72B support native tool calling, offering competitive accuracy on serverless hosting platforms.

Frequently Asked Questions

Which model is best for multi-agent systems?

Claude 3.5 Sonnet is highly recommended due to its logical reasoning capabilities and cheap caching reads.

Can I use GPT-4o-mini for agents?

Yes, for simple routing or data-entry tasks. For multi-step planning, premium models are recommended to avoid execution loops.