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Perplexity 的网站图标

Perplexity

浏览以下提供商提供的模型: Perplexity (服务条款)

9 个模型

OpenRouter 处理的 token 数

  • perplexity 的网站图标
    Perplexity: Decider Flash V1.2Decider Flash V1.2

    Decider Flash V1.2 is a 4B-parameter decision model from Perplexity, a smaller, lower-cost sibling of Decider V1.2 with the same API contract. Instead of generating text, it reads content passed as state (text, JSON, or images) and returns typed, probabilistic answers to one or more named questions in a single request: the probability of yes for a yes/no question (noul), a probability for every option plus the most likely one (choice, up to 255 options), or a probability for every level of an ordered rubric plus the expected score (score). It suits high-volume classification, routing, and moderation where application code thresholds the returned numbers rather than parsing a chat reply.

    作者: perplexity2026年10月16日US$0.01/M 输入 tokenUS$0/M 输出 token
  • perplexity 的网站图标
    Perplexity: Decider V1.2Decider V1.2

    Decider V1.2 is a new 27B checkpoint of Perplexity's decision model, succeeding Decider V1.1 27B with the same API contract. Instead of generating text, it reads content passed as state (text, JSON, or images) and returns typed, probabilistic answers to one or more named questions in a single request: the probability of yes for a yes/no question (noul), a probability for every option plus the most likely one (choice, up to 255 options), or a probability for every level of an ordered rubric plus the expected score (score). It is built for classification, routing, moderation, and rubric grading where application code thresholds the returned numbers rather than parsing a chat reply. For a smaller, lower-cost option with the same contract, see Decider Flash V1.2.

    作者: perplexity2026年10月16日US$0.02/M 输入 tokenUS$0/M 输出 token
  • perplexity 的网站图标
    Perplexity: Embed V1 4BEmbed V1 4B

    pplx-embed-v1 -4B is one of Perplexity's state-of-the-art text embedding models built for real-world, web-scale retrieval. pplx-embed-v1 is optimized for standard dense text retrieval with the 4B parameter model maximizing retrieval quality.

    作者: perplexity2026年3月16日US$0.03/M tokens
  • perplexity 的网站图标
    Perplexity: Embed V1 0.6BEmbed V1 0.6B

    pplx-embed-v1-0.6B is one of Perplexity's state-of-the-art text embedding models built for real-world, web-scale retrieval. pplx-embed-v1 is optimized for standard dense text retrieval with the 0.6B parameter model targeting lightweight, low-latency embedding generation.

    作者: perplexity2026年3月16日US$0.004/M tokens
  • perplexity 的网站图标
    Perplexity: Sonar Pro SearchSonar Pro Search

    Exclusively available on the OpenRouter API, Sonar Pro's new Pro Search mode is Perplexity's most advanced agentic search system. It is designed for deeper reasoning and analysis. Pricing is based on tokens plus $18 per thousand requests. This model powers the Pro Search mode on the Perplexity platform. Sonar Pro Search adds autonomous, multi-step reasoning to Sonar Pro. So, instead of just one query + synthesis, it plans and executes entire research workflows using tools.

    作者: perplexity2025年10月30日200K 上下文US$3/M 输入 tokenUS$15/M 输出 token
  • perplexity 的网站图标
    Perplexity: Sonar Reasoning ProSonar Reasoning Pro

    Note: Sonar Pro pricing includes Perplexity search pricing. See details here Sonar Reasoning Pro is a premier reasoning model powered by DeepSeek R1 with Chain of Thought (CoT). Designed for advanced use cases, it supports in-depth, multi-step queries with a larger context window and can surface more citations per search, enabling more comprehensive and extensible responses.

    作者: perplexity2025年3月7日128K 上下文US$2/M 输入 tokenUS$8/M 输出 token
  • perplexity 的网站图标
    Perplexity: Sonar ProSonar Pro

    Note: Sonar Pro pricing includes Perplexity search pricing. See details here For enterprises seeking more advanced capabilities, the Sonar Pro API can handle in-depth, multi-step queries with added extensibility, like double the number of citations per search as Sonar on average. Plus, with a larger context window, it can handle longer and more nuanced searches and follow-up questions.

    作者: perplexity2025年3月7日200K 上下文US$3/M 输入 tokenUS$15/M 输出 token
  • perplexity 的网站图标
    Perplexity: Sonar Deep ResearchSonar Deep Research

    Sonar Deep Research is a research-focused model designed for multi-step retrieval, synthesis, and reasoning across complex topics. It autonomously searches, reads, and evaluates sources, refining its approach as it gathers information. This enables comprehensive report generation across domains like finance, technology, health, and current events. Notes on Pricing (Source) - Input tokens comprise of Prompt tokens (user prompt) + Citation tokens (these are processed tokens from running searches) - Deep Research runs multiple searches to conduct exhaustive research. Searches are priced at $5/1000 searches. A request that does 30 searches will cost $0.15 in this step. - Reasoning is a distinct step in Deep Research since it does extensive automated reasoning through all the material it gathers during its research phase. Reasoning tokens here are a bit different than the CoTs in the answer - these are tokens that we use to reason through the research material prior to generating the outputs via the CoTs. Reasoning tokens are priced at $3/1M tokens

    作者: perplexity2025年3月7日128K 上下文US$2/M 输入 tokenUS$8/M 输出 token
  • perplexity 的网站图标
    Perplexity: SonarSonar

    Sonar is lightweight, affordable, fast, and simple to use — now featuring citations and the ability to customize sources. It is designed for companies seeking to integrate lightweight question-and-answer features optimized for speed.

    作者: perplexity2025年1月27日127K 上下文US$1/M 输入 tokenUS$1/M 输出 token