Great stuff. People are getting used to agents as the interface for everything, even work as simple as "change label X to label Y". More speed on that front is welcome. The Codex "blended mode" they refer to will be useful (similar to Claude Code bouncing between haiku and opus).

I imagine it's a win-win. This could significantly help their tokenomics.

The example showing a plan being generated instantaneously is interesting. Human understanding will end up as the last, true bottleneck.

With the rough numbers from the blog post at ~1k tokens a second in Cerebras it should put it right at the same size as GLM 4.7, which also is available at 1k tokens a second. And they say that it is a smaller model than the normal Codex model

This is a win for agents, speed and intelligence is crucial to the loop. If the time and token cost is small you can iterate many times to correct mistakes.

Got to wonder why Wall Street is dumping NVIDIA.

really too bad that the codex models are so tightly coupled to the codex harness as to be useless for everything else

edit: not useless in a absolute sense, but worse than the vanilla gpt models

It'll be nice when there's smarter routing between models, or easier routing, so some things get sent to the fast model, some get sent to the cheap model, some get sent to the smart model, etc.

When I saw Spark my mind went to Apache Spark and wondered if we were learning all the lessons in orchestration of driver/worker and data shuffling from that space.

Cerebras out here catching dubs. Does anyone know if Groq is running DGX Cloud inference or am I tripping?