NEW DeepSeek V4 Pro: Testing Reveals Critical Flaws

2026-04-24 · Source: Discover AI · Field: Technology & Digital — Artificial Intelligence & Machine Learning · Depth: Expert, long

Summary

This analysis compares DeepSeek V4 Pro and DeepSeek V4 Flash models on a complex "Elevator Puzzle" designed to test causal reasoning, logic, and interwoven optimization. The puzzle requires navigating an elevator from floor 0 to 50 with specific button functions, prime number checks, limited energy, and token constraints, often necessitating a return to floor 29 before proceeding. DeepSeek V4 Flash successfully solved the puzzle with nine button presses, satisfying all constraints including energy and token limits, and demonstrated a trial-and-error approach that surprisingly yielded a valid solution. In contrast, DeepSeek V4 Pro struggled significantly, entering optimization loops, failing to discover critical strategic paths like the emergency exit at floor 29, and ultimately crashing or getting lost in brute-force trial-and-error without an effective strategy, failing to find a solution within the given time and resources.

Key takeaway

For AI engineers evaluating large language models for complex problem-solving, you should not assume "Pro" versions inherently possess superior strategic reasoning. Your testing should include multi-layered, non-linear causal reasoning puzzles like the "Elevator Puzzle" to uncover actual strategic capabilities versus brute-force trial-and-error, as DeepSeek V4 Flash's unexpected success over V4 Pro demonstrates the importance of diverse, challenging benchmarks.

Key insights

DeepSeek V4 Flash outperformed V4 Pro on a complex causal reasoning puzzle, despite V4 Pro's "strategic" intent.

Principles

• Complex puzzles expose model strategic weaknesses.
• Trial-and-error can sometimes succeed where strategy fails.

Method

The "Elevator Puzzle" tests causal reasoning, logic, and interwoven optimization by requiring navigation through floors with specific button functions, energy limits, and token constraints, often involving non-linear paths.

In practice

• Use causal reasoning puzzles for model evaluation.
• Design tests with non-linear solution paths.
• Observe reasoning traces for strategic insights.

Topics

• DeepSeek V4 Pro
• DeepSeek V4 Flash
• Elevator Puzzle Test
• Causal Reasoning
• Model Performance

Best for: AI Engineer, AI Scientist, Machine Learning Engineer, Research Scientist

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Editorial summary, takeaway, and curation by AIssential. Original article published by Discover AI.