DATAKU vs RunPod

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.

RunPod rents on-demand GPUs for training, fine-tuning, and deploying AI models through Pods, Serverless endpoints, and multi-node Clusters. Spin up 30+ GPU SKUs from RTX 4090s to B200s in under 30 seconds, scale Serverless workers from zero, and keep the same account from experiment to production.

Hyperscaler GPU rentals often lock you into long contracts and higher per-hour rates. RunPod bills Pods per second or per hour across Community and Secure Cloud tiers, with published RTX 4090 rates from $0.34 per hour and Serverless workers billed only while they run.

ML engineers, AI startups, and inference teams use RunPod to prototype in a pod, ship Serverless APIs, and scale across 31 global regions from one account. Customer logos on the site include Cursor, Hugging Face, Perplexity, and Replit.