What is DualMind Arena? v2.0
DualMind Arena is a blind AI model comparison platform — submit a prompt, receive responses from two competing models simultaneously, vote on the better one, and contribute to a community-driven . The key insight: knowing a model’s name changes how you judge it. DualMind hides model identities until after you vote — so quality determines the ranking, not brand recognition.Arena Battle Mode
Submit one prompt to two AI models simultaneously. Vote blind. See the truth.
ELO Leaderboard
Every vote shifts real ELO ratings. The leaderboard reflects collective human preference, not marketing budgets.
Conversation Threads
Organize comparisons into persistent threads. Share publicly, keep private, or distribute via link.
Live Latency Metrics
Time to First Token and Tokens/Second tracked for every response. Speed is measured separately — never folded into quality.
How it works
Platform modes
- ⚔️ Arena Battle
- 💬 Single Chat
- 📂 Threaded Conversations
Two randomly-selected models. One prompt. Zero brand bias.Responses appear side-by-side under anonymous labels — Model A and Model B. Vote for the better response, then see which models you were actually comparing.This is the primary mode for leaderboard contributions. Every vote carries statistical weight in the ELO system.
What makes this different
Why blind testing?
Why blind testing?
In every study on AI evaluation, knowing a model’s identity introduces measurable bias. Users consistently rate GPT-4 responses higher when they know it’s GPT-4 — even when the content is identical to a competitor’s output.Blind testing removes this entirely at the architecture level. Model names are never sent to the client until after a vote is submitted. This is enforced as a data contract, not a UI convention.
Why ELO instead of win rate?
Why ELO instead of win rate?
Win rate is a static snapshot. A model with a 60% win rate against weak opponents tells you nothing about how it performs against the best.ELO is dynamic. It adjusts based on the strength of who you beat. A model that defeats high-ranked competitors gains more points than one that beats weak ones. This produces a leaderboard that reflects true relative quality, not raw vote counts.
Why measure latency separately?
Why measure latency separately?
A faster model response creates an immediate impression of fluency, even before the user reads a word. This is well-documented in UX research.Latency is infrastructure — it reflects hosting, not intelligence. The Arena displays Time to First Token (TTFT) and Tokens per Second (TPS) as separate, transparent metrics — never folded into a quality score.
Start here
Quickstart
Run your first comparison in under two minutes.
How DualMind Works
Deep dive into blind comparison, ELO scoring, and streaming architecture.
Evaluation Philosophy
The reasoning behind how we design fair, meaningful AI comparisons.
Roadmap
What we’re building next and why.
Ready? Head to the Quickstart guide and run your first comparison.