Benchmarking GPT-6 Astra, Claude Fable 5.1, and GPT-5.6

This post details a tutorial on benchmarking GPT-6 Astra, Claude Fable 5.1, and GPT-5.6 Sol using W&B Weave. It analyzes benchmark scores, token usage, response times, and estimated API costs across HumanEval coding tasks and other LLM evaluations. The post discusses benchmark saturation and the relationship between benchmark scores and cost per task, providing specific cost breakdowns for each model. It also highlights the use of agentic workflows for evaluating LLM performance in complex tasks.