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LlamaIndex releases Boo Bench, a 179-page parser stress test, and reports LlamaParse at 179/179

2 articles1 sourcesince Oct 29Last article 1h ago ·

Overview

AISummary of 2 articles

LlamaIndex releases Boo Bench, a 179-page benchmark built to push document parsers into repetition loops, with a leaderboard, paper, and dataset on its site and Hugging Face.

In one case the company says a model saw 246 redaction x's on a page and wrote 23,004 of them.

LlamaIndex says its LlamaParse Agentic and Agentic Plus modes scored 179 of 179 with zero failures on the benchmark. It reports the best frontier vision-language models, GPT-6 Luna and GPT-6.1 Terra, reached 99.4%, while open vision-language models scored between 61% and 93%. These figures are LlamaIndex's own results on its own benchmark.

Written by AI from the articles below · updated Oct 29, 12:44 PM ET

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Developments

2 developments

  1. Oct 29, 12:36 PM ET · 1 article
    LlamaIndex reports LlamaParse Agentic results at 179/179 on a document benchmark
    LlamaIndex: LlamaParse Agentic scores 179/179 on document parsing benchmark
  2. Oct 29, 12:36 PM ET · 1 article
    LlamaIndex releases Boo Bench, a document parsing benchmark that induces repetition loops
    LlamaIndex: LlamaIndex releases Boo Bench, a 179-page doc parser stress test

Article timeline

The articles in this story. Times are ET.

Oct 29
  1. LlamaIndex 🦙Official
    LlamaParse Agentic scores 179/179 on document parsing benchmark

    AILlamaIndex says its LlamaParse Agentic and Agentic Plus modes scored 179 of 179 with zero Boos on its benchmark. The post reports the best frontier VLMs, GPT-6 Luna and GPT-6.1 Terra, reached 99.4%, while open VLMs ranged from 61% to 93%.

  2. LlamaIndex 🦙Official
    LlamaIndex releases Boo Bench, a 179-page doc parser stress test

    AILlamaIndex has built Boo Bench, a 179-page benchmark designed to push document parsers into repetition loops. In one case, a model saw 246 redaction x's on a page and wrote 23,004 of them. Results, a leaderboard, a paper, and the dataset are available on LlamaIndex's site and Hugging Face.

    Image from @llama_index's post

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