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New Agentic Coding Index ranks LLMs by intelligence density

A Reddit user has developed a new metric called the Agentic Coding Index (ACI) to evaluate Large Language Models (LLMs) on coding tasks. The ACI aggregates scores from several coding benchmarks, including SWE-bench Pro, DeepSWE v1.1, and Terminal-Bench, using a weighted formula. This index aims to measure a model's 'intelligence density' by considering its parameter count and performance across these diverse coding evaluations, with a focus on rewarding true autonomous mastery. AI

IMPACT Provides a new metric for evaluating LLM coding capabilities, potentially influencing future model development and comparisons.

RANK_REASON User-created benchmark aggregation and metric. [lever_c_demoted from research: ic=1 ai=1.0]

Read on r/LocalLLaMA →

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

New Agentic Coding Index ranks LLMs by intelligence density

How we ranked this

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5 / 100
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Tool
User-created benchmark aggregation and metric. [lever_c_demoted from research: ic=1 ai=1.0]
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High
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Breaking (< 6h)
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Full methodology in our editorial standards.

COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/Informal-Trouble2183 ·

    I collected every single LLM coding benchmark, and computed their Intelligence Density

    <table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1w2v97w/i_collected_every_single_llm_coding_benchmark_and/"> <img alt="I collected every single LLM coding benchmark, and computed their Intelligence Density" src="https://preview.redd.it/wq4aplazzkmh1.png?wid…