DexHoldem Agentic Perception - Robot Chip Inventory: leaderboard

DexHoldem agentic perception bench (Chen et al., 2026): an agent in its native harness (Codex, Claude Code or Gemini CLI) at a medium thinking budget parses one captured poker-table image, given earlier states, into the structured game state; 36 problems, mean of three runs. Accuracy in percent on the exact per-denomination count of the robot's own chips, on 16 problems; higher is better.

Metric: Field accuracy (%; exact per-denomination count of the robot's chips, 16 problems; 36 tabletop states from real games, mean of three runs; the perceiver parses the image with its harness at a medium thinking budget). Source: arxiv.org. Saturation forecast: Around February 2027. 8 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.5 (Medium)62.5#48 (GPT-5.5)
2GPT-5.4 (Medium)56.2#121 (GPT-5.4)
3Claude Opus 4.7 (Medium)37.5#75 (Claude Opus 4.7)
4GPT-5.4 Mini (Medium)29.2#389 (GPT-5.4 Mini)
5Claude Sonnet 4.6 (Medium)29.2#158 (Claude Sonnet 4.6)
6Gemini 3 Flash (Medium)29.2#159 (Gemini 3 Flash)
7Gemini 3.1 Flash Lite (Medium)22.9#363 (Gemini 3.1 Flash Lite)

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=dexholdem-agentic-perception-robot-chip-inventory · How It Works · Data refreshed daily, snapshot 2026-11-12.