Simon Willison — 2026-07-16#
Highlight#
The most substantive post today is Simon’s breakdown of Moonshot AI’s new Kimi K3 model and his deep reflection on his famous “pelican riding a bicycle” benchmark. It perfectly captures his hands-on evaluation style, demonstrating how a simple programmatic prompt can reveal critical details about model pricing, token usage, and hidden system prompts.
Posts#
Kimi K3, and what we can still learn from the pelican benchmark Chinese AI lab Moonshot AI announced Kimi K3, a massive 2.8 trillion parameter model that currently leads the Arena.ai Frontend Code arena. Simon highlights its high pricing at $3 per million input tokens and $15 per million output tokens, which makes it the most expensive Chinese model to date. By running his traditional “pelican riding a bicycle” SVG test, he discovered that K3’s single “max” reasoning effort consumed over 13,000 reasoning tokens, making a single generation cost 25 cents. Simon reflects that while the pelican test no longer accurately measures complex agentic capabilities, it remains invaluable as a “hello world” prompt for estimating reasoning costs, confirming spatial awareness, and uncovering hidden system prompt lengths.