Frequently Asked Questions

FindLLM is a free, independent platform that helps you compare Large Language Models (LLMs) by quality, speed, and price. We aggregate benchmark scores from Artificial Analysis, pricing from OpenRouter, and metadata from HuggingFace to give you a comprehensive, up-to-date view of the AI model landscape.

We pull data from three main sources: Artificial Analysis for benchmarks and quality scores, OpenRouter for real-time pricing and provider availability, and HuggingFace for community metrics like downloads and trending scores. Data is refreshed hourly to daily depending on the source.

The Quality Index is a composite score (0–100) created by Artificial Analysis that reflects a model's performance across multiple benchmarks including MMLU, HumanEval, MATH, GPQA, and others. Higher is better. It's the most holistic single measure of a model's capability.

Blended price is the average cost per million tokens, weighting both input and output token prices. The typical weighting we use is 3:1 input-to-output, which reflects common real-world usage patterns. This gives you a single, comparable price point across models.

Start with the LLM Selector tool — answer a few questions about your use case (coding, chat, analysis) and budget, and we'll rank models for you. Or use the Explore page to compare models on a scatter plot of quality vs. price. For specific tasks, check the relevant Leaderboard.

Yes, completely free. No account required, no paywalls. Our goal is to make LLM comparison accessible to everyone.

Benchmark data from Artificial Analysis is refreshed every few hours. Pricing from OpenRouter updates multiple times per day. HuggingFace metrics are pulled daily. The exact frequency depends on each source's API.

We track the main benchmarks reported by Artificial Analysis, including MMLU, HumanEval, MATH, GPQA, MT-Bench, and others. Each model's benchmark breakdown is visible on its detail page. We also track output speed (tokens per second) and time-to-first-token latency.