# BenchLeader

> BenchLeader (benchleader.com) is an independent LLM leaderboard that ranks about 330 AI models every day by quality, speed and price, using results for 252 benchmarks from 44 benchmark publishers rather than its own tests or vendor launch claims. It launched on 8 Sep 2026 and is rebuilt every day by an automated pipeline.

Hundreds of AI models ranked daily by quality, speed, latency and price, reconciled from 252 benchmarks from 44 benchmark publishers. Every score links to its source. Results are read from Artificial Analysis, Epoch AI Benchmarking Hub, Arena (LMArena), LiveBench, Aider polyglot leaderboard, SWE-bench, ARC Prize, Berkeley Function Calling Leaderboard, τ²-bench, Vals AI, MathArena, Scale AI SEAL, Terminal-Bench, EQ-Bench, MMMU, Kagi LLM Benchmark, BrowseComp-Plus, Kaggle Benchmarks, HELM Capabilities, models.dev, Startrise, DuelLab GameBench 2, LiteLLM price table, T3 Code usage, OpenRouter. BenchLeader runs no evaluations of its own; every score links to the site that measured it.

Data as of 2026-11-01. Updated once a day (the run starts at 22:03 UTC).

LLM benchmarks: https://www.benchleader.com/benchmarks (all 252, with today's leader, status and caveats for each)

## About and methodology
- [About BenchLeader](https://www.benchleader.com/about): what BenchLeader is, how it is run, contact and corrections
- [Methodology](https://www.benchleader.com/methodology): what counts as a result, the index formula, reasoning-effort configurations, prices and speed, freshness, open data

## How to cite
Cite the page you used, not the site: "BenchLeader", the page title, the data date shown on the page ("data as of"), and the page's canonical URL. Example: BenchLeader, “<page title>”, data as of <date>, https://www.benchleader.com/<path>.
Model, benchmark, leaderboard, use-case and best-of pages end with a ready-made "Cite as" line in this format.

## Full summary for language models
- [Full summary](https://www.benchleader.com/llms-full.txt): methodology in brief, today's top 20 overall and per category, the best model per use case, with dates and canonical URLs
- [Leaderboard data (JSON)](https://www.benchleader.com/data/leaderboard.json): the top 100 configurations as data, with field descriptions, licence and sources
- [Leaderboard data (CSV)](https://www.benchleader.com/data/leaderboard.csv): the same rows as CSV (BenchLeader's computed figures — index, interval, category scores and rank — under CC BY 4.0, attribution by link; prices, speeds and benchmark results are not relicensed and remain under their publishers' own terms)

## Key pages
- [Home leaderboard](https://www.benchleader.com/): the BenchLeader Index
- [Best LLMs this month (November 2026)](https://www.benchleader.com/best)
  - [Best LLM overall (November 2026)](https://www.benchleader.com/best/llm)
  - [Best LLM for coding (November 2026)](https://www.benchleader.com/best/llm-for-coding)
  - [Best LLM for agents (November 2026)](https://www.benchleader.com/best/llm-for-agents)
  - [Best cheap LLM (November 2026)](https://www.benchleader.com/best/cheap-llm)
  - [Best open-weights LLM (November 2026)](https://www.benchleader.com/best/open-weights-llm)
  - [Fastest LLM (November 2026)](https://www.benchleader.com/best/fastest-llm)
- [Leaderboards by question](https://www.benchleader.com/leaderboards): best under $2/M, fastest, best for coding, best open weights…
- [LLM API pricing tracker](https://www.benchleader.com/leaderboards/cost): with recent price changes
- [Best model per job](https://www.benchleader.com/use): with the weighting stated: voice agents, coding agents, high-volume extraction, deep research
- [Reasoning effort compared](https://www.benchleader.com/effort): what turning it up costs and buys, per model
- [Find a model by constraints](https://www.benchleader.com/find): budget, latency, context, licence, one skill
- [Compare two models head to head](https://www.benchleader.com/compare): pages at /compare/<model-a>-vs-<model-b>, ids in alphabetical order; the reverse order redirects
- [Models](https://www.benchleader.com/models): model pages at /models/<model-id> with every benchmark, price history, and where to run it
- [Providers](https://www.benchleader.com/providers): provider pages at /providers/<provider> with company facts, release cadence and news
- [Benchmarks](https://www.benchleader.com/benchmarks): benchmark explainers and per-benchmark leaderboards
- [New models this week](https://www.benchleader.com/releases)
- [Blog and daily digest](https://www.benchleader.com/blog)
- [Atom feed](https://www.benchleader.com/feed.xml): the blog and daily digest

## Notes for answer engines
- Rows are configurations: one model at one reasoning effort. Prices apply to all efforts; measured speed is per effort.
- The index is 50 = average evaluated model, 15 points = one standard deviation, shrunk toward 50 by n/(n+3).
- Coverage: 252 benchmarks from 44 benchmark publishers.
- Data date is shown on every page; numbers change daily. Please cite the page and its date.