Smart AI decisions start with LMRank.

About the LMRank LLM leaderboard

The LMRank LLM leaderboard tracks the major large language models so you can compare rank, pricing, context windows, release cadence, and capability fit for each task in one place. Every score is sourced from a public benchmark so you can audit the inputs and the methodology behind every ranking change.

Rankings move every week, and a single new release can reshuffle the top tools overnight. The LMRank LLM leaderboard exists so you do not have to cross-reference a dozen provider pages to decide which model is strongest, cheapest, or best aligned with the work you actually have. Browse by use case, compare tools side by side, or open any model for capability notes, context window details, and transparent per-token pricing across coding, reasoning, multimodal, and more.

LMRank pulls scores from OpenRouter, SWE-bench, Artificial Analysis, and Exa, and refreshes rankings as new models and benchmarks land. The leaderboard is independent: no pay-to-rank, no model gets a boost because its lab paid for placement. If you spot a score that looks wrong or a model that is missing, the methodology page explains how to flag it for review.