Qwen 3.8 27B on my laptop can interpret model weights, too

Simon Willison tested the "Sparks of Weight-Space Programming" paper's game-identification prompts, which ask a model to name which of four Atari-style games a policy network was trained on using only its raw weights and no tools. Running Qwen 3.8 27B locally via LM Studio, he got correct answers for Pac-Man (46m 12s, 43,506 reasoning tokens), Pong (1h 4m 54s) and Breakout (52m 25s), but it failed on Freeway. He notes critics like Matthew Honnibal and Sean Goedecke dispute the paper's framing, and he focuses on the no-tools question rather than claims that source code is obsolete.