We watched Kimi K3 and Claude Fable 5 work through the same tasks, and they showed completely different personalities. Fable plans everything upfront, then fires one giant batched call. It cleaned up an entire CRM (searching Salesforce, HubSpot, and Gmail in parallel) in just 2 tool calls. Kimi works step by step. It searches for tools mid-task as it needs them and makes more, smaller calls. The same CRM job took 7 tool calls. When something broke, both models improvised. A tool search returned a result too large to read. Fable dropped into the shell and grepped the raw file. Kimi did the same, but inside Composio’s remote sandbox instead of locally. The tradeoff: Fable’s batching finished ~2.5× faster. Kimi’s step-by-step style kept its context smaller, using 40% fewer tokens for the same work. Both are incredibly competent models. They just approach work differently.