Perplexity、クラウド版「Model Council」を公開し複数モデルによる多角的回答を実現

Hold on tight to your tokens: AI search firm Perplexity on Tuesday expanded its five-month-old Model Council to its cloud-based Computer platform, giving users more ways to configure multi-model queries. The idea behind the Model Council, Perplexity said in Tuesday’s release, is to “allow users to build a board of top models for a single issue.” Models assigned to a council and given a prompt will tackle the problem independently, resulting in a synthesis report that explains where their conclusions agree and diverge. According to Perplexity comms chief Jesse Dwyer, Model Council functions as a skill that tells an orchestrator model to spin up parallel subagents, each acting as a full agent harness and tackling the problem independently. “A wait barrier holds until every perspective finishes, then the model the user selected acts as the ‘chair,’” Dwyer told us in an email. “It reads all the perspective outputs and synthesizes them, explicitly surfacing where the models agree and where they diverge.” When originally launched back in February, the Model Council was restricted to three models available on Perplexity with no user choice. Ask a query, get an answer put together by a synthesizer model from whichever models aren’t on their smoke break - that was that. With the addition of Model Council to Computer, users can now choose from two to eight models for their AI advisory board, with options ranging from models supplied by frontier labs such as OpenAI, Anthropic, and Google to open-weight models including GLM and Kimi. Analysis depth can also be customized, and while a synthesizer model still puts together the report, Computer can also “turn that synthesis into outputs like reports, board decks, and other work-ready assets,” Perplexity said. Computer, for those unfamiliar with it, is essentially a web interface for a model orchestration layer. Perplexity describes the overhauled and expanded Model Council as being ideal for ambiguous questions involving “judgment calls, tradeoffs, assessing risks or other situations where there’s no one right answer” because model-to-model dialogue “shows where there’s consensus and where there’s conflict.” “Consensus gives people more confidence to move forward,” the company said. “Gaps show them where to go deeper.” Model Council has a number of intended use cases, Perplexity said, like legal questions, financial queries, corporate decision making, business growth modeling, and even engineering. Being added to Computer makes it even more useful, apparently, because users can now ask it for additional details to “sharpen the answer,” and ask pointed follow-up questions to get a stronger result. Perplexity also encourages users to ask the Council for confidence levels to see what different models think of their collective answer. “Disagreements often come from different starting assumptions, so ask each model to state the assumptions behind its conclusions.” Of course, all of this comes at a price. Access to Model Council was previously restricted to enterprise tiers (either $34/month per seat for Pro or $271 for Max) and individual Max ($200/month) customers. With the expansion into Computer, the Council will now serve individual Max and Pro ($20/month) users, as well as those on enterprise tiers. But that’s not the only cost associated with the reformed Model Council, because Computer relies on usage-based billing. Pro users get an initial pool of 4,000 bonus credits, while Max customers get 35k and a renewing 10k a month. Enterprise Pro customers get 8,000 bonus credits and 500 a month per seat, while Enterprise Max customers start with a 45k bonus pool and get 15k per seat per month. According to Perplexity, 100 Computer credits are equal to $1. A "light" task, like summarizing a document and pulling out key points, can eat between 100 and 350 credits. A "heavy" task, which Perplexity describes as creating work-ready assets like pitch decks, can eat as many as 2,275 credits. Because Computer credits function at the product level rather than mapping directly to raw AI token usage, it's not clear how many credits a Model Council session could burn, and Perplexity didn't get specific. In other words, if you want the Council to weigh in on one of those aforementioned ambiguous questions, it could cost you. AI tokens can get quite expensive, after all. “Query complexity will affect token usage more than the specific model selection,” Dwyer explained. “Simple queries in Computer can cost less than a penny while complex tasks run higher.” ®