Agents
A public leaderboard that ranks models by crowdsourced human preference: a user submits a prompt, two anonymous models answer, and the user votes for the better response before the model names are revealed.
A public leaderboard that ranks models by crowdsourced human preference: a user submits a prompt, two anonymous models answer, and the user votes for the better response before the model names are revealed. It started in 2023 as Chatbot Arena, built by LMSYS and UC Berkeley researchers, later became LMArena, and now runs as Arena at arena.ai. Votes are combined into ratings with a Bradley-Terry model, so scores reflect preference on real user prompts rather than correctness on a fixed test set. Separate arenas such as WebDev Arena rank models on specific task types.
Primary source: arxiv.org
Example
Separate arenas such as WebDev Arena rank models on specific task types.
Hands-on guides, comparisons, and tutorials that cover Agents.
FAQ
A public leaderboard that ranks models by crowdsourced human preference: a user submits a prompt, two anonymous models answer, and the user votes for the better response before the model names are revealed.
LMArena sits in the Agents part of the AI stack. Understanding it helps you make better decisions when building, debugging, and shipping AI features.
Developers Digest publishes tutorials and videos that cover Agents topics including LMArena. Check the blog and YouTube channel for hands-on walkthroughs.
Related
Tasks that take an agent many steps and a long time to finish, measured in hours of equivalent human work rather than one prompt and reply.
An ensemble technique where several LLMs answer the same prompt in layers.
Recording each step of an LLM application as a tree of timed spans, so you can see which prompts, model responses, tool calls, and handoffs happened in one request and how long each took.

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