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DecipherLM: How a Tiny LLM Cracked a Mixed Caesar Cipher That Stumped the Rest

Line 2 screams shift +17. The rest? +9. A simple poem turns nightmare for codebreakers—until a 500M-param model sniffed out the pattern. Here's the gritty path to automating Caesar ciphers with LLMs.

DevTools Feed Apr 04, 2026 4 min read
Decrypted poem from FrancisTRDEV riddle solved by DecipherLM using Qwen2.5 perplexity scoring

⚡ Key Takeaways

  • Smaller LLMs like Qwen2.5-0.5B crush larger ones on noisy, short-text tasks like ciphers due to better tokenization. 𝕏
  • Trusted shift pools + contextual history = the killer combo for mixed Caesar puzzles, hitting 100% accuracy. 𝕏
  • Bigger isn't better—SLMs signal a shift to efficient, local AI for dev tools. 𝕏
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#Caesar cipher solver #DecipherLM #LLM perplexity #small language models

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Originally reported by dev.to

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