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debate.tellodb

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Multi-model adversarial debates help minimize single-LLM bias on complex decisions.

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Free to browse · updated 2026-06-14
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What is debate.tellodb?

Users assemble panels by selecting models from multiple providers and assigning roles such as drafter or reviewer. Each participant receives the full debate history and must respond in structured JSON format listing disagreements, suggested improvements, and a confidence score. The process continues until an arbitrator confirms sufficient alignment or the maximum round limit is reached. Saved configurations called assemblies allow teams to reuse tuned pipelines with custom system prompts, web search toggles, and consensus thresholds. Real-time cost tracking and full transcript visibility support audit requirements in regulated environments. Common applications include legal clause analysis, investment thesis review, clinical differential diagnosis, and architecture document critique where contradictory model outputs can be reconciled before final decisions are made.

Key features

Multi-model adversarial LLM debate pipeline
Structured JSON critiques with confidence scores
Arbitrated consensus with early termination
Customizable assemblies with drag-and-drop sequencing
Real-time cost and token tracking
Full audit trail and context inspection
Community marketplace for shared workflows

AI models debate.tellodb uses

GPT-4o
OpenAI, used as drafter example
GPT-5.5
OpenAI, public drafter in Peer-Review Panel v3
Claude Opus
Anthropic, reviewer in Peer-Review Panel v3
Gemini 2.5
Google, reviewer in Peer-Review Panel v3
Grok 4
xAI, reviewer in Peer-Review Panel v3

What you can use debate.tellodb for

Legal Contract Analysis

Run clauses through models such as Opus, GPT-5.5 and Gemini Pro to surface contradictions that a single model would overlook.

Medical Differential Reasoning

Stress-test diagnostic chains with adversarial reviewers before a clinician spends time on the writeup.

Research Literature Synthesis

Reconcile contradictory papers by forcing models to cite specifics then refine to a single coherent narrative.

How to use debate.tellodb

  1. 1Assemble a panel by drag-and-drop sequencing of frontier models
  2. 2Send the prompt to the first model in the chain
  3. 3Receive structured JSON critiques from each reviewer
  4. 4Allow the arbitrator to score agreement and terminate early if threshold is reached
  5. 5Obtain the final Chairman synthesis with full audit trail

debate.tellodb pricing

Pricing model: Freemium. Plan details are indicative — check the site for current prices.

Free

Free
  • 2 free debates
  • no card
  • All frontier models
  • Full audit trail per debate

Editor's verdict

Pros

  • +Access to all frontier models via single subscription
  • +Reduces single-LLM bias with peer review
  • +Full observability and auditability

Cons

  • Limited to 2 free debates
  • Subscription required for full model access

Our take: debate.tellodb is a solid research & data choice. It's valued for access to all frontier models via single subscription and reduces single-llm bias with peer review. The main trade-off is limited to 2 free debates. A good pick if you want capable AI without a high upfront cost.

Frequently asked questions

It routes queries through an adversarial chain where models from rival providers critique and refine each other's outputs until an arbitrator confirms consensus.

Summary

debate.tellodb is a solid research & data choice. It's valued for access to all frontier models via single subscription and reduces single-llm bias with peer review. The main trade-off is limited to 2 free debates. A good pick if you want capable AI without a high upfront cost.

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