DATAKU vs Humata

DATAKU is a data science site that tracks AI benchmarks, API pricing, and model releases, then packages the numbers into free calculators and downloadable datasets. The homepage archives articles on inference costs, funding rounds, and head-to-head model comparisons, while the Tools section hosts eight utilities such as an LLM cost calculator, benchmark decoder, and model graveyard.

Most AI news sites summarize press releases. DATAKU cross-references provider docs, leaderboard scores, and its own pricing tables, which is why the downloadable datasets page lists 48-row pricing histories and 62-row benchmark score tables under CC BY 4.0 licenses.

Data analysts, ML engineers, and buyers use DATAKU when they need cost-per-token math, benchmark context, or CSV exports instead of marketing claims. The About page describes the project as benchmark and pricing tracking run by a former Tokyo data analyst.

Humata turns uploaded PDFs and documents into a searchable knowledge base you can question in plain language. Upload files, ask questions, and get answers with citations pointing back to the source pages. Teams use it to summarize research papers, compare documents, and pull facts from dense technical reports without reading every page.

General chatbots answer from training data, not your files. Humata reads every document you upload and grounds each response in that content with linked citations. You can ask follow-up questions, request shorter summaries, and embed the chat widget on your own site so customers query your documentation directly.

Researchers, analysts, and educators use Humata to get through long papers faster. Enterprise teams get role-based access controls, encrypted file storage, and department-level permissions on the Team plan. The Expert plan fits small groups of up to three users who need more than the 60-page free allowance.