LLM Blokus Benchmark Analysis
Published:Jan 4, 2026 04:14
•1 min read
•r/singularity
Analysis
This article describes a new benchmark, LLM Blokus, designed to evaluate the visual reasoning capabilities of Large Language Models (LLMs). The benchmark uses the board game Blokus, requiring LLMs to perform tasks such as piece rotation, coordinate tracking, and spatial reasoning. The author provides a scoring system based on the total number of squares covered and presents initial results for several LLMs, highlighting their varying performance levels. The benchmark's design focuses on visual reasoning and spatial understanding, making it a valuable tool for assessing LLMs' abilities in these areas. The author's anticipation of future model evaluations suggests an ongoing effort to refine and utilize this benchmark.
Key Takeaways
- •A new benchmark, LLM Blokus, is introduced to evaluate LLMs' visual reasoning.
- •The benchmark uses the board game Blokus, focusing on spatial reasoning tasks.
- •Initial results are provided for several LLMs, showcasing varying performance.
- •The benchmark is designed to assess abilities in piece rotation, coordinate tracking, and spatial understanding.
Reference
“The benchmark demands a lot of model's visual reasoning: they must mentally rotate pieces, count coordinates properly, keep track of each piece's starred square, and determine the relationship between different pieces on the board.”