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Kilo AI made the Kimi K2.5 model free for a week and saw 3x expected usage, exceeding 50B tokens daily. The model quickly became a top performer in Architect mode for system design tasks. While automatic context caching reduces input costs by 75%, the model's verbosity undermines savings—it generates 2.5x more tokens than DeepSeek-V3.2 and executes up to 1,500 tool calls per task, making output costs significantly higher. Despite strong capabilities, cost-effectiveness depends heavily on specific use cases, with alternatives like MiniMax M2.1 offering better efficiency for many workflows.

What We Learned from a Week of Free Kimi K2.5

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