About LLMPodium

The definitive leaderboard for comparing large language models. We aggregate benchmark data, pricing, and performance metrics from five independent sources to help you make informed decisions about AI models.

Our Mission

The AI landscape is evolving rapidly. New models launch every week, benchmarks are constantly updated, and pricing changes frequently. LLMPodium exists to cut through the noise — providing a single, comprehensive source of truth for model comparison. Today we track 700 models across 25 benchmarks and 17 categories, with a curated weekly ranking of the 60 flagship models.

How It Works

Our composite Podium Score aggregates five independent signals — arena Elo (35%), benchmark average (30%), intelligence index (20%) and LLM Stats (15%) — into a single 0–100 number. Each signal is min-max normalized, and missing signals are re-weighted so no model is penalized for a source gap. The full formula, normalization rules and limitations are on our Methodology page.

Data Sources

All rankings are built exclusively from public data. We link to every source we use, and each sync is timestamped:

• Arena.ai — last synced 2026-08-04
• Artificial Analysis — last synced 2026-08-03
• LLM Stats — last synced 2026-08-02
• Vellum Leaderboard — last synced 2026-07-24
• LLMBase — last synced 2026-08-04

Pricing and speed figures are taken from official provider API documentation. A machine-readable summary of the whole site is available at llms.txt, and raw data exports on the Cost per Task page.

Editorial Process & Independence

LLMPodium is an independent project. We are not affiliated with, sponsored by, or paid by any model provider — and we never accept payment for rankings or placements. Data is synced weekly; major model releases trigger an immediate refresh, and every change is recorded in our changelog. When a benchmark or source is retired, we document it rather than silently rewriting history.

Who We Are

LLMPodium is maintained by a small independent team of data engineers and ML practitioners who build the aggregation pipeline, verify source data, and write the analysis in our blog. We answer to readers, not to labs: if you spot a data error, we want to hear about it.

Contact

Corrections, data questions, or partnership inquiries: hello@llmpodium.com. For common questions about the ranking, see the FAQ.