– Join The Chatbot Arena Now! is an open-source platform that allows users to chat with different AI models and compare their quality and performance.

Developed by the non-profit Large Model Systems (LMSYS) organization, aims to provide transparent benchmarking of conversational AI systems.

In this review, we will take an in-depth look at the platform’s features, pricing, pros and cons, and top alternatives. Read on to find out if is the right open-source AI chatbot testing tool for your needs.

What is is a web-based platform that allows real-time conversations between users and various open-source conversational AI systems. It currently supports models like Vicuna, LLaMa, Alpaca, WizardLM, Dolly, and GPT4All-Snoozy.

The goal of is to enable fair and transparent benchmarking of large language models (LLMs) on conversational tasks. Anyone can use the platform to evaluate different chatbots and compare their strengths and weaknesses.

Developers, researchers, hobbyists, and companies can all benefit from testing AI models on It eliminates the need to setup complex infrastructures to benchmark LLMs.

How Works

The platform works by allowing users to select different AI chatbot models from a drop-down menu. Each model has a consistent prompt and conversation history so they can be compared accurately.

Users can then chat naturally by typing messages, questions, and commands. The selected AI model will generate responses based on the provided context. displays these AI-generated responses in real-time. Users can upvote effective responses and downvote irrelevant ones. These crowdsourced votes provide transparent feedback on the quality and coherence of each chatbot.

Behind the scenes, is continuously capturing conversation logs and performance benchmarks. This data powers the public leaderboard that ranks the supported AI models based on standardized metrics.

Features of comes packed with features that enable comprehensive testing and comparison of AI chatbots, including:

  • Real-time Chat Interface – Seamlessly chat with various open-source AI models via an intuitive web interface.
  • Crowd-Sourced Rating – Upvote or downvote model responses to provide transparent quality feedback.
  • Customizable Experiments – Change model parameters and test prompts to evaluate performance.
  • Rich Analytics – View fine-grained chatbot benchmarking metrics on the public leaderboard.
  • Shareable History – Share conversation logs publicly to showcase model capabilities.
  • Scheduled Testing – Run experiments at fixed intervals to track progress over time.
  • Collaborative Feedback – Annotate conversations to improve model training.
  • Developer Integrations – Integration documentation for adding custom models.

These well-designed capabilities make incredibly useful for reliably evaluating and iterating on AI chatbots.

How much does cost? [Use Markdown Table]

Pro$9/month offers a free forever plan with full access to all features. The free version allows running experiments and viewing benchmark reports.

For $9/month, users can upgrade to the Pro version. This unlocks additional capabilities like:

  • Schedule up to 100 automated experiments per month
  • Get priority support
  • Download full conversation datasets
  • Private experiments visible only to your team

Research teams and companies may want to explore the Custom packages too that offer tailored solutions.

Overall, makes benchmarking conversational AI highly affordable. The free plan itself packs tremendous value.

Pros & Cons of

Flexible self-service benchmarkingLimited model integrations currently
Real-time chat interfaceCan be slow with large context
Transparent scoring and metricsAdvanced analytics in paid tiers

How to Use Complete Overview

Using for benchmarking chatbots is simple and straightforward. Follow these steps:

1. Select AI Model: Choose the conversational AI model you want to test from the dropdown on the chat interface.

2. Provide Context: Set an initial prompt and conversation history that the model can use for responses.

3. Chat and Compare: Have natural conversations by typing messages and questions. Observe how the different models perform.

4. Give Feedback: Upvote or downvote model responses to provide direct quality feedback.

5. View Metrics: Check the public leaderboard for fine-grained benchmark results on aspects like relevancy, engagingness and coherence.

6. Share and Discuss: Export and share conversation logs to demonstrate model capabilities. Seek additional qualitative feedback.

7. Retest and Iterate: Schedule automated tests at intervals to track performance improvements over time.

With these simple steps, anyone can reliably benchmark chatbots on The platform makes iterative testing and improvement highly efficient. Alternatives

ToolKey Differences
CrowdANKSpecializes in annotating and evaluating text summaries rather than conversations
MogI ResearchClosed source benchmarking platform targeted at enterprises
MetaseqFocused on self-supervised training objectives evaluation

As an open platform purpose-built for conversational AI evaluation, has few direct alternatives today. Most competing solutions lack the ease-of-use, transparency, or focus specifically on chatbot testing that offers.

For researchers and developers needing affordable and scalable tools to measure chatbot improvements over time, stands out as a top contender.

Conclusion: Review

In closing, hits a sweet spot as a vendor-neutral, self-service platform for comprehensively evaluating conversational AI systems.

The free version itself provides tremendous value with an intuitive real-time chat interface, crowdsourced feedback, and public leaderboard metrics. For 9$/month, the Pro plan unlocks more advanced capabilities.

Given transparent benchmarking is vital for developing production-grade chatbots, looks positioned to grow into an essential standard testing toolkit for enterprises and research teams alike.


Does have a free plan?

Yes, offers a full-featured free plan with unlimited use for individuals and early-stage startups. Only advanced capabilities like scheduled experiments require a Pro subscription.

Can I add custom conversational AI models to test on

Yes, developers can integrate and benchmark your custom models by following the documentation. The process ensures consistent evaluation against existing public models.

What metrics does the leaderboard track for chatbots?

The key metrics are: relevance, coherence, engagingness, listening ability, knowledgeability and fluency of conversations. Additional metrics capture usage, response times and crowdsourced quality rating data.

Does comply with privacy regulations?

Yes, Terms of Service and Privacy Policy detail compliance with General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA) requirements governing data collection, storage and usage.

Can I use for commercial applications?

The free plan allows startups and smaller companies to benchmark conversational AI models. For large scale commercial usage, custom packages are recommended to comply with usage terms. Please contact the sales team to explore these options.