From the source
The next wave of personal computing isn't about better apps; it's about agents that live on your behalf: managing your calendar, triaging your inbox, tracking your finances, keeping your notes in order.
For agents to work in production, three things have to be true at once: the model has to be accurate, it has to be fast, and it has to be cheap enough to run continuously.
Most models optimize for one or two of these.
Mercury 2 optimizes for all three.
We evaluated Mercury 2 on PinchBench , the open-source benchmark built on top of OpenClaw — the fastest-growing open-source project in GitHub history, with 250K+ stars in under 60 days.
Here's what we found.
The result Mercury 2 sits in the upper-left of the chart: high task success rate and the fastest execution time in its performance class. 78% success rate — matching or exceeding GPT-5 Mini (75%), Gemini 2.5 Flash (71%), DeepSeek Chat (72%), and GPT-4o (71%).
Fastest execution time — completing agentic tasks faster than every model at comparable accuracy, and faster than most models at any accuracy level. <$1 / million tokens — $0.25 per 1M input, $0.75 per 1M output.
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