Radio Hoosh: AI Deep Dives

OpenAI and Anthropic have cut LLM API prices by as much as 80% in a few months. We look at Max Woolf's analysis of what is driving the cuts and what it means for developers.

Show Notes

AI-generated: both hosts are AI voices (Google NotebookLM), and the conversation is based on the sources listed below.

In this episode we discuss Max Woolf's post on the steep price cuts OpenAI and Anthropic made to their LLM APIs over recent months, some as large as 80%. We go through the possible reasons he raises: more efficient inference, competition from open-weight models, and a push for market share. We also cover why the post drew more than 300 comments on Hacker News.

API pricing decides which LLM and AI agent workloads make economic sense. Developers who build AI features need to know whether these lower prices will last, because the answer shapes how they design products, choose models and budget for inference costs.

  • OpenAI and Anthropic have cut some LLM API prices by up to 80% in a few months
  • Cheaper inference may be one driver behind the cuts
  • Open-weight models add competitive pressure on the large AI labs
  • The cuts may also be a deliberate push for market share
  • Whether the cuts last affects how developers build and budget AI agents

Sources:

What is Radio Hoosh: AI Deep Dives?

Radio Hoosh takes each day's biggest AI story (a new model, a research paper, a lab announcement or a developer tool) and unpacks it in a 20–45 minute conversation. Both hosts are AI-generated voices (Google NotebookLM), and episodes are produced automatically from public sources such as Hacker News and Hugging Face Daily Papers, then published by Kasra Qasempour. "Hoosh" is Persian for intelligence; a Persian edition is available as رادیو هوش.