DeepSeek V4 Flash Reasoning Trace on ARC-AGI: Redundant Verification

mhmazur · x · 2026-08-24

The author published a video with the raw reasoning trace of DeepSeek V4 Flash solving a public ARC-AGI task, providing detailed observations:

Pattern Recognition: The model immediately identified the serialized grids and structure as "ARC-like" and knew standard color mappings (e.g., 5 is gray) without explicit prompts.
Coordination: It independently adopted zero-indexed coordinates and correctly reconstructed spatial grids from nested lists.
Efficiency: The correct rule was identified 18% into the trace, and the correct grid was built by 59%. The remaining 41% was spent on redundant rechecking, format conversion, and verifying already-known edge cases.
Language: The fragmented language resembles frontier models ("We need solve puzzle"), with frequent loops of preparing to stop and then continuing.
Transformation Overhead: Significant effort was spent converting between arrays, coordinates, blocks, and rows. While initial abstraction was useful, later conversions were mostly redundant.
Conclusion: There is no clear evidence of memorization; the model derived the rule. The raw trace was 1,219 words (14 mins spoken), though the request completed in 54 seconds.

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