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We've added a new "reasoning" focus (beta) on Perplexity for Pro users. It will use the new OpenAI o1-mini. There is no search integration yet. The model is slow, and usage is limited because of rate limits. It is good for puzzles, math, and coding. Pro searches are your... show more

Aravind Srinivas

547,314 subscribers

288,789 次观看 • 1 年前 •via X (Twitter)

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10 条评论

Aravind Srinivas 的头像

Aravind Srinivas1 年前

10 uses/day

Mohamed 的头像

Mohamed1 年前

Just want you to know i discovered Perplexity from your Lex interview and it has become my favorite company in the world at the moment. Your UI, UX, direct answers, rabbit hole chases, and your marketing are all incredible. Keep it up!

Intellectus Partners 的头像

Intellectus Partners1 年前

Very cool @AravSrinivas we love the speed of iteration. It’s insanely good!!

Matt 的头像

Matt1 年前

Is it an in house model or based off of o1?

Aravind Srinivas 的头像

Aravind Srinivas1 年前

It’s literally just o1

Sagar Patil 的头像

Sagar Patil1 年前

Genuine question: OpenAI just announced new rate limits for o1-mini. 50 messages a day. Why would someone use perplexity (o1-mini) if it doesn't have search integration?

Samar Singh 的头像

Samar Singh1 年前

@youdotcom has it and integrated with search as well.

Marvin Baumann 的头像

Marvin Baumann1 年前

@perplexity_ai For research purposes on different topics, do you recommend the large perplexity model or the Anthropic model and why?

Seth Rose 的头像

Seth Rose1 年前

Everyone immediately typing "How many r's are in the word 'strawberry'." 🙄

arun 的头像

arun1 年前

love this from the team!

相关视频

OpenAI just announced API access to o1 (advanced reasoning model) yesterday. I'm delighted to announce today a new short course, Reasoning with o1, built with OpenAI, and taught by Colin Jarvis, Head of AI Solutions at OpenAI, to show you how to use this effectively! Unlike previous language models which generate output directly, o1 “thinks before it responds,” and generates many reasoning tokens before returning a more thoughtful and accurate response. It is great at complex reasoning -- including planning for agentic workflows, coding, and domain-specific reasoning in STEM fields like law. But how you should use it is quite different from other LLMs. I think o1 will be a game changer for many AI applications; and in this course, you'll learn how to use it effectively. In detail, you’ll: - Learn to recognize what tasks o1 is suited for, and when to use a smaller model, or combine o1 with a smaller model - Understand the new principles of prompting reasoning models: Be simple and direct; no explicit chain-of-thought required; use structure; show rather than tell - Implement multi-step orchestration in which o1 plans, and hands tasks over to gpt-4o-mini to execute specific steps; this illustrates a design pattern to optimize intelligence (accuracy) and cost - Use o1 for a coding task to build a new application, edit existing code, and test performance by running a coding competition between o1-mini and GPT 4o - Use o1 for image understanding and learn how it performs better with a "hierarchy of reasoning," in which it incurs the latency and cost upfront, preprocessing the image and indexing it with rich details so it can be used for Q&A later - Learn a technique called meta-prompting, in which you use o1 to improve your prompts. Using a customer support evaluation set, you'll iteratively use o1 to modify a prompt to improve performance You'll also learn about how OpenAI used reinforcement learning to produce a model that uses "test-time compute" to improve performance. I think you'll find this course enjoyable and valuable. Please sign up for it here:

OpenAI just announced API access to o1 (advanced reasoning model) yesterday. I'm delighted to announce today a new short course, Reasoning with o1, built with OpenAI, and taught by Colin Jarvis, Head of AI Solutions at OpenAI, to show you how to use this effectively! Unlike previous language models which generate output directly, o1 “thinks before it responds,” and generates many reasoning tokens before returning a more thoughtful and accurate response. It is great at complex reasoning -- including planning for agentic workflows, coding, and domain-specific reasoning in STEM fields like law. But how you should use it is quite different from other LLMs. I think o1 will be a game changer for many AI applications; and in this course, you'll learn how to use it effectively. In detail, you’ll: - Learn to recognize what tasks o1 is suited for, and when to use a smaller model, or combine o1 with a smaller model - Understand the new principles of prompting reasoning models: Be simple and direct; no explicit chain-of-thought required; use structure; show rather than tell - Implement multi-step orchestration in which o1 plans, and hands tasks over to gpt-4o-mini to execute specific steps; this illustrates a design pattern to optimize intelligence (accuracy) and cost - Use o1 for a coding task to build a new application, edit existing code, and test performance by running a coding competition between o1-mini and GPT 4o - Use o1 for image understanding and learn how it performs better with a "hierarchy of reasoning," in which it incurs the latency and cost upfront, preprocessing the image and indexing it with rich details so it can be used for Q&A later - Learn a technique called meta-prompting, in which you use o1 to improve your prompts. Using a customer support evaluation set, you'll iteratively use o1 to modify a prompt to improve performance You'll also learn about how OpenAI used reinforcement learning to produce a model that uses "test-time compute" to improve performance. I think you'll find this course enjoyable and valuable. Please sign up for it here:

Andrew Ng

357,401 次观看 • 1 年前

OpenAI o1 is now out of preview in ChatGPT. What’s changed since the preview? A faster, more powerful reasoning model that’s better at coding, math & writing. o1 now also supports image uploads, allowing it to apply reasoning to visuals for more detailed & useful responses.

OpenAI o1 is now out of preview in ChatGPT. What’s changed since the preview? A faster, more powerful reasoning model that’s better at coding, math & writing. o1 now also supports image uploads, allowing it to apply reasoning to visuals for more detailed & useful responses.

OpenAI

2,342,172 次观看 • 1 年前

Perplexity Pro is transitioning to a reasoning powered search agent for harder queries that involve several minutes of browsing and workflows. Check it out! It’s still in beta and has some issues but we’re going to keep making it better!

Perplexity Pro is transitioning to a reasoning powered search agent for harder queries that involve several minutes of browsing and workflows. Check it out! It’s still in beta and has some issues but we’re going to keep making it better!

Aravind Srinivas

256,917 次观看 • 1 年前

Introducing Jan-v1: 4B model for web search, an open-source alternative to Perplexity Pro. In our evals, Jan v1 delivers 91% SimpleQA accuracy, slightly outperforming Perplexity Pro while running fully locally. Use cases: - Web search - Deep Research Built on the new version of Qwen's Qwen3-4B-Thinking (up to 256k context length), fine-tuned for reasoning and tool use in Jan. You can run the model in Jan, llama.cpp, or vLLM. To enable search in Jan, go to Settings → Experimental Features → On, then Settings → MCP Servers → enable a search-related MCP such as Serper. Use the model: - Jan-v1-4B: - Jan-v1-4B-GGUF: Credit to the Qwen team for Qwen3 4B Thinking & Georgi Gerganov for llama.cpp.

Introducing Jan-v1: 4B model for web search, an open-source alternative to Perplexity Pro. In our evals, Jan v1 delivers 91% SimpleQA accuracy, slightly outperforming Perplexity Pro while running fully locally. Use cases: - Web search - Deep Research Built on the new version of Qwen's Qwen3-4B-Thinking (up to 256k context length), fine-tuned for reasoning and tool use in Jan. You can run the model in Jan, llama.cpp, or vLLM. To enable search in Jan, go to Settings → Experimental Features → On, then Settings → MCP Servers → enable a search-related MCP such as Serper. Use the model: - Jan-v1-4B: - Jan-v1-4B-GGUF: Credit to the Qwen team for Qwen3 4B Thinking & Georgi Gerganov for llama.cpp.

👋 Jan

689,722 次观看 • 10 个月前

BREAKING 🚨: Perplexity is testing a new "Sonar Testing" reasoning model internally. Potentially, it will arrive as a reasoning upgrade to the existing Sonar model. Imo, "Sonar Testing" is the best name ever 👀

BREAKING 🚨: Perplexity is testing a new "Sonar Testing" reasoning model internally. Potentially, it will arrive as a reasoning upgrade to the existing Sonar model. Imo, "Sonar Testing" is the best name ever 👀

TestingCatalog News 🗞

26,030 次观看 • 8 个月前

Web search is now available with OpenAI o3, o3-pro, and o4-mini. The model can search the web within its chain-of-thought! 🧠🌐 $10 / 1K tool calls

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OpenAI Developers

190,139 次观看 • 11 个月前

Most search models need the cloud. II-Search-4B doesn’t. 4B model tuned for reasoning with search tools, built for local use. Performance of models 10x its size. Search that is small, smart, and open.

Most search models need the cloud. II-Search-4B doesn’t. 4B model tuned for reasoning with search tools, built for local use. Performance of models 10x its size. Search that is small, smart, and open.

Intelligent Internet

499,961 次观看 • 10 个月前

Nano Banana Pro + Gamma is here! Try Nano Banana Pro for your presentations, or take it a step further and use Studio Mode to create cinematic slides with it. We've made this model available to all Gamma users through the end of the year. Nano Banana Pro HD (4k edition) is also available to Gamma Ultra users.

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Gamma

27,341 次观看 • 5 个月前

Jan v1 is now more reliable when handling searches. It's an open-source alternative to Perplexity Pro, and it now avoids infinite loops with Jan v1 2509. Performance updates: - Gains on reasoning & creativity benchmarks - Small drop on SimpleQA (91.1 -> 90.7), still competitive with Perplexity Pro The updated version is live on Jan Hub. You can run the model in Jan, llama.cpp, or vLLM. Use the model: - Model: - GGUF: Shoutout to the Qwen team for Qwen3-4B Thinking and Georgi Gerganov for llama.cpp.

Jan v1 is now more reliable when handling searches. It's an open-source alternative to Perplexity Pro, and it now avoids infinite loops with Jan v1 2509. Performance updates: - Gains on reasoning & creativity benchmarks - Small drop on SimpleQA (91.1 -> 90.7), still competitive with Perplexity Pro The updated version is live on Jan Hub. You can run the model in Jan, llama.cpp, or vLLM. Use the model: - Model: - GGUF: Shoutout to the Qwen team for Qwen3-4B Thinking and Georgi Gerganov for llama.cpp.

👋 Jan

17,759 次观看 • 9 个月前

BREAKING 🚨: Perplexity is rolling out Perplexity Computer to PRO users along with a new "Usage and Credits" page. Users will likely get 4000 bonus credits as well. Pro Computer 👀

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🚨 AI News | TestingCatalog

102,640 次观看 • 3 个月前

o1-pro is probably the best model i've used for coding, hands down i gave it a pretty complicated codebase and asked it to refactor while referencing docs the difference between claude/gemini/o1 and o1 pro is night and day. first time in a while i've been this impressed. full comparison in the video + code.

o1-pro is probably the best model i've used for coding, hands down i gave it a pretty complicated codebase and asked it to refactor while referencing docs the difference between claude/gemini/o1 and o1 pro is night and day. first time in a while i've been this impressed. full comparison in the video + code.

Sully

255,348 次观看 • 1 年前

ROUTE LLM - SUPER INTELLIGENCE IN THE MAKING RouteLLM combines the superpowers of o1-preview, Sonnet 3.5, Gemini Flash, o1-mini, 4o, and 4o-mini! Based on your query, it optimizes for latency, cost, and quality of the response. The cool thing about RouteLLM is it combines. - coding ability of Sonnet 3.5 - reasoning ability of o1-preview - hard-coding ability of o1-mini - 1M context of Gemini - speed of 4o-mini Similar to ensemble models that are very effective in classical ML, RouteLLM and similar models will be the most effective in the LLM ecosystem

ROUTE LLM - SUPER INTELLIGENCE IN THE MAKING RouteLLM combines the superpowers of o1-preview, Sonnet 3.5, Gemini Flash, o1-mini, 4o, and 4o-mini! Based on your query, it optimizes for latency, cost, and quality of the response. The cool thing about RouteLLM is it combines. - coding ability of Sonnet 3.5 - reasoning ability of o1-preview - hard-coding ability of o1-mini - 1M context of Gemini - speed of 4o-mini Similar to ensemble models that are very effective in classical ML, RouteLLM and similar models will be the most effective in the LLM ecosystem

Bindu Reddy

66,374 次观看 • 1 年前

Introducing OpenAI o3 and o4-mini—our smartest and most capable models to date. For the first time, our reasoning models can agentically use and combine every tool within ChatGPT, including web search, Python, image analysis, file interpretation, and image generation.

Introducing OpenAI o3 and o4-mini—our smartest and most capable models to date. For the first time, our reasoning models can agentically use and combine every tool within ChatGPT, including web search, Python, image analysis, file interpretation, and image generation.

OpenAI

3,719,622 次观看 • 1 年前

Sentient took AI Startup of the Year at the Minsky Awards 🙌 ROMA Search achieved an industry-leading 81.7% accuracy, significantly surpassing competitors on the FRAMES benchmark for multi-step reasoning. On the SEAL-0 benchmark for complex, multi-source reasoning, ROMA with 45.6% accuracy more than doubled the score of Gemini 2.5 Pro (19.8%). ROMA is available on GitHub, try it out today👇

Sentient took AI Startup of the Year at the Minsky Awards 🙌 ROMA Search achieved an industry-leading 81.7% accuracy, significantly surpassing competitors on the FRAMES benchmark for multi-step reasoning. On the SEAL-0 benchmark for complex, multi-source reasoning, ROMA with 45.6% accuracy more than doubled the score of Gemini 2.5 Pro (19.8%). ROMA is available on GitHub, try it out today👇

Sentient

482,307 次观看 • 8 个月前

Introducing a brand new way to use Jan 💛 You can now search the web, do deep research, and let Jan use your browser. Powered by Jan-v2-VL-Max, 30B model beating Gemini 2.5 Pro & DeepSeek R1 on execution benchmarks. Try it:

👋 Jan

29,403 次观看 • 5 个月前

This is the best way to use Claude Fable in Claude Code without immediately hitting your limits. 1. Model set to Fable 5 2. Reasoning on Max 3. Instruct Claude to run a dynamic workflow where: 3a. Fable is the orchestrator 3b. Opus does the reasoning heavy phases Fable is so overpowered that you don't need its intelligence for every step. Let it orchestrate Opus or even Sonnet.

This is the best way to use Claude Fable in Claude Code without immediately hitting your limits. 1. Model set to Fable 5 2. Reasoning on Max 3. Instruct Claude to run a dynamic workflow where: 3a. Fable is the orchestrator 3b. Opus does the reasoning heavy phases Fable is so overpowered that you don't need its intelligence for every step. Let it orchestrate Opus or even Sonnet.

Dan McAteer

457,009 次观看 • 23 小时前

Mind = BLOWN 🤯 Grok 3 just launched with reasoning abilities that put other AIs to shame. Just spent hours testing it vs ChatGPT. My honest breakdown: • Reasoning mode destroys basic Grok for complex tasks • Image generation is SIGNIFICANTLY better than ChatGPT • Coding still needs work (ChatGPT wins here) • Includes web search similar to Perplexity ($16/mo for 50 searches) • New platform with sharable chats that index on Google Who's trying it?

Mind = BLOWN 🤯 Grok 3 just launched with reasoning abilities that put other AIs to shame. Just spent hours testing it vs ChatGPT. My honest breakdown: • Reasoning mode destroys basic Grok for complex tasks • Image generation is SIGNIFICANTLY better than ChatGPT • Coding still needs work (ChatGPT wins here) • Includes web search similar to Perplexity ($16/mo for 50 searches) • New platform with sharable chats that index on Google Who's trying it?

Julian Goldie SEO

11,517 次观看 • 1 年前

Just made an MCP server to use Anthropic’s new web search tool. What I love about it is that the search is agentic. You can use any model to call a Claude instance that returns processed search results. Or specify how deep the search should be. 🔗 Link in the comments.

Just made an MCP server to use Anthropic’s new web search tool. What I love about it is that the search is agentic. You can use any model to call a Claude instance that returns processed search results. Or specify how deep the search should be. 🔗 Link in the comments.

Pietro Schirano

29,189 次观看 • 1 年前

Sam Altman announces the release of OpenAI's full o1 reasoning AI model and ChatGPT Pro, which will cost $200 a month, and allow unlimited access to o1 in Pro Mode

Sam Altman announces the release of OpenAI's full o1 reasoning AI model and ChatGPT Pro, which will cost $200 a month, and allow unlimited access to o1 in Pro Mode

Tsarathustra

91,869 次观看 • 1 年前