How big is Mercury 2? How many tokens is it trained on?

Is it's agentic accuracy good enough to operate, say, coding agents without needing a larger model to do more difficult tasks?

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volodia 13 hours ago | parent [-]

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.

	▲	bjt12345 6 hours ago \| parent \| next [-]
		If latency is the differentiator, would you be chasing the edge compute marketplace, e.g. mobile edge compute AI agents?
	▲	xanth 12 hours ago \| parent \| prev \| next [-]
		Are you dogfooding it on simple tasks? If so what do you use it for regularly and what do you avoid?
	▲	nayroclade 12 hours ago \| parent \| prev [-]
		Is the approach fundamentally limited to smaller models? Or could you theoretically train a model as powerful as the largest models, but much faster?