New benchmark shows strong link between Base64 generation and AI intelligence

A new benchmark called Encode Bench has revealed a strong correlation between a language model's ability to generate Base64 encoded responses and its intelligence scores. The benchmark, which tests models on tasks requiring problem-solving, exact answer preservation, and correct encoding, found a Pearson correlation of 0.91 with the AA Intelligence Index. While this suggests a potential crude measure of multi-step reliability, the creator cautions that it does not prove causation and could reflect other factors like tokenizer behavior or reasoning limits. AI

IMPACT This benchmark may offer a novel, albeit crude, method for assessing LLM capabilities beyond traditional metrics.

RANK_REASON The item describes a new benchmark and its findings regarding LLM capabilities, which falls under research. [lever_c_demoted from research: ic=1 ai=1.0]

Read on r/LocalLLaMA →

• AA Intelligence Index
• Base64
• Claude Sonnet 5
• DeepSeek V4 Flash
• Encode Bench
• Gemini 3.5 Flash
• Gemma 4 26B A4B IT
• GPT-5.6 Sol
• Kimi K3
• Nemotron 3 Nano 30B A3B

• product
• other

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →