Chatbot Arena - The community-driven leaderboard you need to know
Choose the right AI model for your task
Welcome to a new post in the AI Builders Series - helping AI developers and researchers study and deploy the latest breakthroughs reliably and efficiently.
Some of my previous posts covered techniques for reducing LLMs’ cost and latency, tips for choosing the best AI model, and securing LLM-powered apps from prompt attacks.
A NotebookLM-powered podcast episode discussing this post:
The AI landscape shifts rapidly, with new language models dropping weekly. Just recently, Google's Gemini dethroned OpenAI's GPT-4o from its months-long reign at the top of Chatbot Arena, bringing renewed attention to this popular benchmark as it approaches its second anniversary. I covered it and seven other leaderboards a few months ago:
But what sets Chatbot Arena apart, and why should AI engineers and researchers take notice?
The challenge of evaluating LLMs
Evaluating language models is surprisingly complex. Unlike traditional machine learning tasks where we can clearly define correct outputs, LLMs operate in an open-ended space where responses can be creative, subjective, and highly contextual. There's often no single "right" answer.
Traditional academic benchmarks like MMLU (Massive Multitask Language Understanding) or GSM8K (Grade School Math, 8K examples) and industry leaderboards are becoming less reliable indicators of real-world performance for two key reasons:
Data Contamination - modern LLMs are trained on vast amounts of internet data, including these benchmark datasets and their solutions. This makes it increasingly challenging to ensure true test-time evaluation.
System Complexity - leading models like GPT and Claude are no longer just raw language models—they're sophisticated AI systems with complex prompt chains, tool use capabilities, and retrieval-augmented generation. Traditional benchmarks weren't designed to evaluate these aspects.
Conflicts of interest - industry leaderboards like Scale AI’s SEAL also face criticism as these companies often collaborate with the same labs that develop the models they evaluate.
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Many readers expense the paid membership from their learning and development education stipend.Enter Chatbot Arena
Chatbot Arena, developed by researchers from Berkeley and Stanford, took a refreshingly different approach. Instead of relying on predetermined test sets, it leverages real-world user interactions and preferences through a battle system.
How it works
The platform presents human users with two anonymous chat interfaces side by side, à la blind test. Users can simultaneously converse with both models and then choose their preferred response. These binary comparisons are then processed using the Elo rating system, a system that was originally developed to rate chess players by measuring players' (language models) game skills. Players gain or lose points based on whether they win or lose matches. If a player beats someone ranked higher, they gain more points. If they lose to a lower-ranked player, they lose more points.
For example, if Claude-3 Sonnet, with an Elo score of 1000, defeats a lower-ranked GPT-3.5 Turbo (Elo 900), it might earn 5 points. Conversely, losing to Mixtral 8x7B (Elo 800) could cost it 15 points, reflecting the greater penalty for losing to a weaker model.
The Chatbot Arena is a set of multiple leaderboards and charts, all providing insights into models’ performance:
The main leaderboard under the ‘Arena’ tab shows overall model performance with Elo ratings.
Category-specific ratings under the ‘Overview’ tab allow you to focus on specific capabilities, such as coding, math, or creative writing, and languages like French, German, and Spanish.
The legacy leaderboard under the ‘Full Leaderboard’ tab features Elo ratings along with models’ reported performance across academic benchmarks like MT-bench and MMLU.
You might notice multiple models sharing the #1 rank. This happens because Chatbot Arena uses confidence intervals to account for statistical uncertainty. When models' performance ranges overlap, they're considered statistically tied for their position.
Hidden Gems of the Arena
Beyond the headline-grabbing leaderboard, Chatbot Arena offers several advanced and useful analyses that often go unnoticed:
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