This market resolves each option as NO if the date passes and Kenshin9000 (or anyone) has not defeated stockfish with an LLM-based chess engine.
All remaining options resolve YES once an LLM-based engine defeats stockfish (or top engine).
My resolution criteria are more strict than Mira’s:
The LLM engine must have higher ELO than the latest stockfish (or whatever the top engine is at resolution time) at blitz timings with 99.9% confidence and be reproduced by 3+ people.
The LLM engine must not use another chess engine at runtime.
For the purposes of this market, Large Language Models are 100M+ parameter general-purpose generative text models. A fine-tune of an LLM is ok, but the model cannot be solely trained on chess data. An LLM-based engine may use search, but node evaluation must be performed by invoking the LLM on each node (similar to AlphaZero, which is a DNN+search).
The LLM engine and Stockfish will run on the same hardware with the same time controls. The testing hardware should be either a commodity desktop or equivalent to the TCEC or other popular chess software tournament standards.
1,000