How Yes-Brainer compares

There are three broad ways to get several AI models onto one question, and they trade off different things. Here is what each kind does well, and where Yes-Brainer sits among them.

Hosted council products

Council AI, Perplexity's Model Council, Anuma, The AI Council (iOS)

These run several models on one question and synthesise the result, as a finished consumer product. Your conversations live on their side, under their account system, behind a subscription — there is no bring-your-own-key and nothing to self-host. What that buys is real: no keys to create, cap or rotate, history that follows you across devices, and features a browser-only app cannot match, like document libraries and web research. If you want the least friction, this is the category to look at.

The open-source llm-council forks

karpathy/llm-council and its 80+ derivatives

Andrej Karpathy's original is why this category exists, and its prompt designs for judge synthesis and peer evaluation are still the reference implementation. It runs one fixed pass — answer, review, synthesize — behind a local server you start yourself. The forks extend it in different directions; the most built-out add multi-user auth, a database and web search, but keep the original single-pass flow. Most of the rest are CLI tools, MCP servers or single-domain demos rather than products.

Multi-model chat aggregators

Big-AGI, LibreChat, ChatHub, LobeChat, Poe, T3 Chat, Msty, AnythingLLM

These put models side by side so you can compare answers, without orchestrating anything between them — with the partial exception of Big-AGI's Beam, which fans out and merges. As chat platforms they are far broader than Yes-Brainer: many providers, agents, personas, and in LibreChat's case multi-user accounts and roles. What they generally do not have is a mechanic that makes the models respond to each other.

Where Yes-Brainer sits

Yes-Brainer's combination — open source under AGPL, a zero-backend browser PWA, bring-your-own-key, an iterative multi-round consensus debate, and data held on-device — is a slot we have not found occupied. The closest contenders each own part of it: the hosted products have the polish but keep your conversations, the OSS forks are open but need a server and run a single pass, and the aggregators have the breadth but no deliberation between models.

Head to head

• Yes-Brainer vs Council AI — Council AI is the most polished consumer product in the multi-model council space. The difference that matters when choosing between them is not the deliberation mechanic — it is where your conversations live and how you pay.
• Yes-Brainer vs Perplexity’s Model Council — Perplexity’s Model Council runs several models on one question and surfaces where they agree and differ. It is a feature of a larger product; Yes-Brainer is a standalone app built around the mechanic.
• Yes-Brainer vs LibreChat — Both are open source and both let you bring your own keys. They solve different problems: LibreChat is a chat platform you host for people; Yes-Brainer is a deliberation app with nothing to host.
• Yes-Brainer vs Big-AGI — Big-AGI’s Beam is the closest open-source analogue to what Yes-Brainer does — several models answer, then their answers get merged. The difference is scope: Beam is one feature of a large workspace; deliberation is the whole of Yes-Brainer.
• Yes-Brainer vs karpathy/llm-council — Yes-Brainer started from Andrej Karpathy’s llm-council — the orchestration concept and his prompt designs for judge synthesis and peer evaluation were the starting point. It is a credit, not a comparison of rivals.

This is a snapshot of a space that moves quickly, and it is written by the people who made one of the things being compared — read it with that in mind, and check each project's own site for what it does today. If you know a closer neighbour that belongs here, open an issue and this page gets more useful.

Every answer any of these tools shows is generated by an AI model and can be confidently wrong. Seeing several models agree is not evidence that they are right.

Yes-Brainer — ask several AI models one question and see where they disagree. Free and open source; no account, and you bring your own API keys.