OpenAIvsUnstructured

How 10 AI models weigh OpenAI against Unstructured on the 1 buying question where both came up.

OpenAI
3%of answers named it
Unstructured
45%of answers named it
Placed higher
1–18times OpenAI vs Unstructured, over 19 model rankings that listed either
Models leaning
0–9toward OpenAI vs Unstructured; 1 even

Which models prefer which

Share of each model's answers that named each product, and how often its ranking put one above the other (a product listed beats one left off) · On the 1 shared question, every wording

ModelOpenAIUnstructuredPlaced higherLeans
Claude Haiku 5.50%38%0–2Unstructured
GPT-6 Luna0%75%0–2Unstructured
Gemini 4 Argon0%75%0–3Unstructured
Qwen 3.8 Flash0%13%0–1Unstructured
DeepSeek V4.1 Flash0%63%0–2Unstructured
GLM-5.30%50%0–2Unstructured
Kimi K30%63%0–3Unstructured
MiniMax M30%13%0–1Unstructured
Mistral Large 40%25%0–1Unstructured
Nemotron 3.5 Super VL25%38%1–1Even

What the models say about OpenAI

One reason per model, from the shared questions

No reasons given.

What the models say about Unstructured

One reason per model, from the shared questions

  • Claude Haiku 5.5Purpose-built document parsing for LLM agents across PDFs and Office formats
  • GPT-6 LunaStrong document ingestion and parsing for extracting structured content for AI.
  • Gemini 4 ArgonIndustry standard for ingesting, chunking, and preprocessing Office and PDF files for agent workflows.
  • DeepSeek V4.1 FlashBroadest format coverage and mature partitioning pipeline; enterprise-grade.
  • GLM-5.3Broadest format coverage and mature pipelines for RAG and agent ingestion.
  • Kimi K3Purpose-built ingestion SDK; best Office/PDF parsing with element metadata.
  • MiniMax M3Broad format coverage and solid ETL pipeline integration
  • Mistral Large 4Best-in-class parsing for PDFs, Office docs, and messy files into LLM-ready data.
  • Nemotron 3.5 Super VLPowerful document parsing and preprocessing for AI pipelines.

Over time

Share of answers that named each, on the questions where both came up, each time the panel answered

Panel runOpenAIUnstructured
October 26, 20263%45%
October 25, 20260%44%

Question by question

Share of all answers that named each, every wording pooled, with its place among every product named · Both-named questions first