[volodia]

You can think of Mercury 2 as roughly in the same intelligence tier as other speed-optimized models (e.g., Haiku 4.5, Grok Fast, GPT-Mini–class systems). The main differentiator is latency — it’s ~5× faster at comparable quality.

We’re not positioning it as competing with the largest models (Opus 4.5, etc.) on hardest-case reasoning. It’s more of a “fast agent” model (like Composer in Cursor, or Haiku 4.5 in some IDEs): strong on common coding and tool-use tasks, and providing very quick iteration loops.

[nayroclade]

Is the approach fundamentally limited to smaller models? Or could you theoretically train a model as powerful as the largest models, but much faster?

[xanth]

Are you dogfooding it on simple tasks? If so what do you use it for regularly and what do you avoid?

[bjt12345]

If latency is the differentiator, would you be chasing the edge compute marketplace, e.g. mobile edge compute AI agents?