CEO @perplexity_ai
RT Perplexity The Perplexity Search API takes the top three spots on the Artificial Analysis Search Index. The medium setting scored five points above the previous leaders, and extended the quality-cost Pareto frontier at about $0.091 per task.
Perplexity Search debuts on the Artificial Analysis Search Index, with all three context size variants taking top positions on the leaderboard The @perplexity_ai Search API comes with three context settings (low, medium, and high) that control how much extracted content each
perplexity is the best at search at any level of compute, agnostic of how much compute the competitors use.
Perplexity Search debuts on the Artificial Analysis Search Index, with all three context size variants taking top positions on the leaderboard The @perplexity_ai Search API comes with three context settings (low, medium, and high) that control how much extracted content each
Decagon is powering customer support for some of the biggest brands in the industry: Delta Airlines, Ticketmaster, Deutsche Telekom, American Airlines. A lot of support related questions require accurate online information and we’re happy to power that with Perplexity’s search.
We’re partnering with @Perplexity_AI to bring live web search to Decagon agents. Customer questions often depend on information that changes by the hour. Agents can now search the live web mid conversation, pull in current information, and respond with cited sources.
RT OpenSea Onchain markets are built for AI agents 🤖 So OpenSea data now powers Perplexity Computer. Tokens, collectibles, and NFTs across 25+ chains. Available today in @perplexity_ai Connectors.
Agentic Trading on Perplexity Computer with @public connector
Public + Perplexity are officially connected. Public members can now connect their brokerage accounts to Perplexity to research and trade stocks, options, crypto, bonds, and Treasuries—all in one AI-powered experience. https://x.com/i/article/2092976180144062464
View quoted postThe Agentic Cloud
Connectors are now available in Agent API. Connect your agents to GitHub, Slack, Google Drive, and Datadog without passing a server URL or token on every request. API Group admins can connect each service once for all API Group members. https://pplx.ai/api-console
View quoted postRT Wall St Engine Anyone who wants to listen to the Nvidia $NVDA earnings call live can use Perplexity Finance: https://www.perplexity.ai/finance/NVDA/earnings?eventId=676136&tab=transcript
Hardware like DGX Spark, with a local agentic computer, will become the gateway for consuming frontier tokens.
at perplexity we are really excited about multi-agent collaboration! we recently explored a simple instantiation of this with advisor escalation from a local model to a remote frontier model, where we showed it can significantly boost the local model's performance. an
We are doubling down on making Computer more useful for financial researchers and analysts. Computer now connects to new licensed data sources, including Dun & Bradstreet, Guidepoint, IBISWorld, and 20+ others. An analyst can ask Computer a question and get an answer built from the firm's own licensed sources without APIs or separate logins to work through. Every figure traces to the source record it came from. Teams doing high-stakes work would know exactly which data set produced which number. To connect, select a provider in Settings → Connectors and sign in with an existing license. Available now to all Perplexity users. https://www.perplexity.ai/hub/blog/computer-connects-to-20-new-licensed-finance-data-sources
Perplexity Computer for Max users comes with a background Dream agent that continually ingests context from files and connected apps and builds multi-hop context graphs in a perpetual compounding loop. Results show a significant jump in correctness, recall and token efficiency.
Brain is our self-improving memory system for Perplexity Computer. It compiles sessions, files, and sources into a structured knowledge wiki. New evals build on our initial results, improving correctness by 9.3 points, currentness by 8.0, and recall by 8.9 with 15% fewer tokens.
A background process that continually ingests context from every single connector (or app), performs multi-hop reasoning in a perpetual inference loop, and runs on your hardware. That is the future.
Big thanks to @nvidia for working together with us and supporting this research on DGX Spark as well as enabling an open ecosystem around cost-effective open-weight models, inference frameworks, and hardware with unified memory.
New research: Portable Computer is a local-first agent for private and cost-effective work. With an on-device 27B model, our harness scores 82.6% on real knowledge work, beating open-source harnesses Pi and Hermes. Our post-trained PPLX 27B reaches 85.4%.
RT Perplexity New research: Portable Computer is a local-first agent for private and cost-effective work. With an on-device 27B model, our harness scores 82.6% on real knowledge work, beating open-source harnesses Pi and Hermes. Our post-trained PPLX 27B reaches 85.4%.
On showing an early demo of Portable Computer on DGX Spark to Jensen, he was kind to gift us a DGX Station, a beast of a local computer that can serve even frontier models like GLM 5.3. Unmetered frontier intelligence running on your own local hardware coming soon!
RT NVIDIA Meet Portable Computer, Perplexity's new local-first agent stack on NVIDIA DGX Spark. When running locally, Portable Computer offers one-click local inference setup and an optimized agentic experience for DGX Spark. Learn more and get started today: https://blogs.nvidia.com/blog/local-ai-open-source-models-agents-nemotron/#perplexity-spark
Today we’re launching Portable Computer on @NVIDIA DGX Spark. Portable Computer is a fully local version of Perplexity Computer, where the entire runtime: orchestrator LLM, subagent LLM, agent harness all run on your local hardware. No cloud dependency.
View quoted postRT Denis Yarats excited to welcome Andrew to the team! we've been building infra for large-scale RL systems, with some interesting projects on the way. our focus is multi-agent collaboration, continual learning, and RL. we'll share an update on our research agenda soon, and we plan to open source a lot of the stuff we work on. if this sounds interesting, DM me!
I am excited to announce that I am joining @perplexity_ai as research lead! We will be doing ambitious paradigm shifting work, advancing the frontiers in the open. If you want to join us in re-imagining continual learning, agent collaboration, and beyond, please reach out!
View quoted postExcited to welcome Andrew Gordon Wilson to our research team. He will be reporting to Denis and lead new research efforts on continual learning, synthetic data, long horizon RL environments and architectures. We’re hiring! Please reach out to Andrew!
I am excited to announce that I am joining @perplexity_ai as research lead! We will be doing ambitious paradigm shifting work, advancing the frontiers in the open. If you want to join us in re-imagining continual learning, agent collaboration, and beyond, please reach out!
View quoted postA full-fledged developer platform for AI should provide you with access to various models (frontier and workhorse), as well as tools for deploying them in useful production workloads. That is basically the Perplexity Agent API.
The Perplexity Agent API now gives developers access to 41 frontier models across 9 providers in one endpoint. Build multi-model agent workflows with built-in tools like web search, finance search, fetch, and sandboxed code execution. https://pplx.ai/agent-api-blog
View quoted postRT Antoine Chaffin Personal update: I've left @LightOnIO to join @perplexity_ai https://x.com/i/article/2088951159343980544
A decent lawyer in the form of an email interface
Computer in Email works for lawyers. Forward your ask, and get a redlined Word doc delivered to your inbox Try it today by emailing computer@perplexity.com
View quoted postImportant contribution!
Today we're launching Miles v0.1, an open-source RL framework for LLMs and multimodal models. RL training is easy to start and hard to debug. Miles helps you ensure your run is correct, use hardware efficiently, and keep RL running at scale. Over the past 9 months, 72
View quoted postRT Perplexity DeepSeek V4 Pro, hosted in the U.S., is now available in Perplexity Computer. We evaluated it against other models on WANDR. It scored 0.359 at $0.75 per task, 62% cheaper than the next model on the cost-performance frontier.
cc computer@perplexity.com
Computer now works in email. Send, forward, or cc computer@perplexity.com on any thread. Every email task runs as a normal session in Computer, viewable on web and mobile, with the same audit trail as any task in the app.
View quoted postWhen building AI agents, it is important to still give humans agency to have their hands on the wheel and intervene when necessary.
Computer now lets you set each connector tool to Allow, Always Ask, or Deny. Approve one action or allow the tool for the rest of the thread. Recurring runs will follow that thread’s approvals. Available now on web for all Computer users.
View quoted postDense models are slow to run on local hardware, but this is incredible and a sign of things to come soon-ish.
RT Igor Babuschkin The River API was tested in this blog post and outperformed Tinker on reinforcement learning runs with identical training code. We spent a lot of effort to get details like routing replay right so you get the best possible results with the API.
We can now RL large MoEs with 0 train-infer mismatch! And doing so can improve performance (pictured task: teach Qwen3.6-35B-A3B to play Wordle). Everything is open-source and we did a bunch of ablations. 🧵
RT Michael Dell 🇺🇸 AI is making better AI. That creates more use cases and more usage, which creates more data and feedback, which helps make AI even better.
You’re right @GergelyOrosz, we got this wrong. Reminder email didn’t go out to this user. He has been refunded, but this is not how we want to operate. We are upgrading our support across the board.
Perplexity, the last 6-12 months, is disappointment after disappointment. I used to be a huge advocate for the service thanks to how good it was at search. I did this promo with them (where I received no payment) for paid subscribers to get access. Then Perplexity does this 👎
RT Johnny Ho If your agent needs frontier web search, it's hard to beat Perplexity's Agent API (on any metric).
Introducing Web Search Benchmarks 🌐 Rankings of search tools across different models and configurations to help you decide how to ground your agent: https://openrouter.ai/benchmarks
RT Alex Atallah Great work by @perplexity_ai on these benchmarks! More info on each one, Pareto curves across models, and why we run them on https://openrouter.ai/benchmarks
Introducing Web Search Benchmarks 🌐 Rankings of search tools across different models and configurations to help you decide how to ground your agent: https://openrouter.ai/benchmarks
Perplexity's Search SDK, which makes Perplexity Computer the best-in-class product for wide and deep research, is now available to use inside any agentic harness!
Introducing the Perplexity Search SDK. It's an agent-first Python SDK that brings Perplexity's Search as Code approach to your applications. Agents can fan out multiple searches, then filter, dedupe, and rank results in code.
View quoted postPerplexity 👑
Introducing Web Search Benchmarks 🌐 Rankings of search tools across different models and configurations to help you decide how to ground your agent: https://openrouter.ai/benchmarks
Impressive numbers for a 700b parameter model!
Introducing GLM-5.3: Built to Code. Ready for Cyber Defense. - Top-tier coding and agentic capabilities, achieved through post-training on the 743B base model - A major leap in cybersecurity, setting a new standard among open models Tech Blog: https://z.ai/blog/glm-5.3
Perplexity Agent API is the best for web search and browsing agents
Sonar is moving to the Agent API. The Perplexity Agent API keeps grounded web search, and adds multi-step research, code execution, built-in tools, and access to multiple models through one API. On BrowseComp and WideSearch, Agent API more than doubles the best Sonar score.
RT Elon Musk Grok
Congrats to @SpaceXAI on one more amazing model: Grok 4.6. We benchmarked it as an orchestrator on our Wide-And-Deep-Research benchmark using the Perplexity Computer harness, and it neatly sits on the Pareto frontier of performance vs cost. Available to all Pro and Max users on
View quoted postCongrats to @SpaceXAI on one more amazing model: Grok 4.6. We benchmarked it as an orchestrator on our Wide-And-Deep-Research benchmark using the Perplexity Computer harness, and it neatly sits on the Pareto frontier of performance vs cost. Available to all Pro and Max users on Perplexity!
Grok 4.6 is now available in Perplexity and Perplexity Computer. On WANDR, it sits on the Pareto frontier of performance and efficiency, matching Fable 5 results at over 60% lower cost.
Gemini Flash models are great for fast, cost-efficient subagents inside any multi-model harness. We use them a lot inside the Perplexity Computer harness.
Our Flash models are workhorses that offer performance at a great price. So, we're shipping updates fast to get them in developers’ hands. And now just 3 weeks after launching 3.6 Flash, 3.7 Flash shows significant gains including in coding and agentic work. It delivers
View quoted postNemotron 3.5 Lightning available to all developers on the Perplexity Agent API. Input: $0.0115 per 1M tokens Output: $0.17 per 1M tokens
.@NVIDIA Nemotron 3.5 Lightning is now available in the Perplexity Agent API 🎉 An open 30B MoE model with 3B active parameters, built for the high-volume execution layer of always-on agents: tool calls, validation, and subagent work. Pair Nemotron Lightning 3.5 with frontier
View quoted postA great American open weights MoE model that can run efficiently on your laptop or local hardware like the DGX Spark! You can use the larger Nemotron Ultra on Perplexity!
Introducing NVIDIA Nemotron 3.5 Lightning⚡ An open 30B MoE model with 3B active parameters, built for always-on agents to complete high-volume, specialized tasks faster. It delivers up to 4x the output speed of similar-sized models.
RT NVIDIA AI Introducing NVIDIA Nemotron 3.5 Lightning⚡ An open 30B MoE model with 3B active parameters, built for always-on agents to complete high-volume, specialized tasks faster. It delivers up to 4x the output speed of similar-sized models.
Compute is the currency
enjoy US hosted K3 on perplexity agent api!
Access the power of @Kimi_Moonshot K3 in the Perplexity Agent API. Hosted exclusively on U.S.-based servers. Try it out today https://bit.ly/pplx-kimi-k3
View quoted postRT Paul Copplestone - e/postgres Supabase is now available on Perplexity Computer 🤖 From a Perplexity chat you can query your production data, look up users, and do basically anything on the Supabase platform @supabase 🤝 @perplexity_ai
RT Milton Friedman Quotes Milton Friedman on 4 ways to spend money: 1) Your money on yourself (you’re careful about both cost and quality) 2) Your money on others (you care about cost, less about quality) 3) Someone else’s money on yourself (you care about quality, not cost) 4) Someone else’s money on others (you care about neither) The last one is how government spending works.
Perplexity Computer’s goal is to provide the maximum intelligence for minimum cost with multi model orchestration. We’ve tested GPT 5.6 Terra extensively and found it to be a pretty good model: capable and cost-effective at the same time. We’re making it the default for all subagents inside Perplexity Computer harness. And are also offering it as an orchestrator model for all Computer users. Have fun!
GPT 5.6 Terra and Luna are now live in Perplexity Computer. Terra is the new default model for all Computer subagents, while Luna will serve as the primary model for scheduled automations. Terra is also available as an orchestrator model in Computer.
RT AleXandra Merz 🇺🇲 Today, I am using this transcript site: https://www.perplexity.ai/finance/SPCX/earnings?eventId=692542&tab=transcript
RT Wall St Engine If anyone wants to listen to the $SPCX and $AMD earnings call, you can find it here on Perplexity: 16:30: https://www.perplexity.ai/finance/SPCX/earnings?eventId=692542&tab=transcript 17:00: https://www.perplexity.ai/finance/amd/earnings?eventId=660937&tab=transcript
Verification is key when using agents for high stakes research!
Every numerical value in Perplexity Computer finance queries is traceable back to original values, with full calculation trace shown.
RT Jensen Huang Today, we’re launching Alpamayo 2 Super, our frontier open reasoning model for autonomous vehicles. Beyond seeing, Alpamayo understands and reasons through the complex world - thinks before it acts. It’s a powerful backbone for robotaxis, trucks, shuttles, delivery vans, tractors and the long tail of mobile robots—billions of autonomous machines someday. We’re releasing it for commercial use under OpenMDW-1.1 so teams can inspect it, fine-tune it and deploy it—open models advance safety and security. The next wave of AI is robotics—and it starts with autonomous vehicles. Great work, Alpamayo team! https://blogs.nvidia.com/blog/alpamayo-2-super-open-model-now-available
Two orders of magnitude improvements are quite rare. This is a big deal.
DeepSeek V4-Flash isn’t just cheaper per token. It reportedly completes the same benchmark tasks as Fable 5 at 105× lower total cost, according to @ArtificialAnlys ! That's precisely why the Flash release is, for me, the DeepSeek 2.0 moment. It will cause a huge stir.
RT Perplexity Developers The Perplexity remote MCP server is live. You can now connect Perplexity to Claude Code, Cursor, or VS Code with just your API key. Nothing to install. https://docs.perplexity.ai/docs/getting-started/integrations/mcp-server#remote-mcp-server
RT DeepSeek 🚀 DeepSeek-V4-Flash Official API is now LIVE in public beta! 🔷 We’ve massively upgraded its Agent capabilities—benchmark scores are now far surpassing the V4-Pro-Preview. Check out the massive performance leap below! 👇 🔷 The official V4-Flash now natively supports the Responses API format and is fully adapted for Codex! Check out the configuration details in our official API docs: https://api-docs.deepseek.com/quick_start/agent_integrations/codex
Follow @kpolley, Perplexity's CISO
Proud to open source Numbat https://www.forbes.com/sites/janakirammsv/2026/07/30/perplexity-open-sources-numbat-to-monitor-risky-ai-coding-agents/
View quoted postRT Kyle Polley “AI Meltdown” is the scenario where the agent goes off the rails and forgets/ignores all previous instructions and soft guardrails. No prompt injection or malicious actor is needed for this to happen. At @perplexity_ai we built a suite of tools to prevent AI Meltdown from happening, and we opened sourced it just yesterday! Please use Numbat to secure yourselves from similar self-inflicted attacks https://github.com/perplexityai/numbat
In a review of our cybersecurity evaluations, we found three incidents in which a Claude model reached the internet from within or while interacting with a third-party evaluation environment, and then gained unauthorized access to the real systems of three different
View quoted postRT Johnny Ho Excited to announce Projects, which are Perplexity's hubs for agent and human collaboration. Most of my time now lives in Projects, where agents automatically manage their own persistent files and collaborate with native tools. Projects are Perplexity's core for collaboration: as agents become more long-running, they will need more agent-native ways to persist and self-improve: memories, skills, and files. But until today, agents have lacked a central hub for collaboration that allows for a persistent area for knowledge work. That place is Projects, not individual chats or files. Projects come packaged with an set of CLI tools intentionally designed for agents to collaborate across files, projects, and with other agents. Importantly, both individual and project identities are fully functional. Individually-scoped connectors are supported as usual, but so are project-level credentials. A project-level brain agent manages the project and provides objective summaries and memories. Agents do the execution but humans still do the steering with notifications and permissions checks. Internally at Perplexity, the canonical way to work is now to start in Slack (each Project connects with at least one Slack channel), spawn multiple threads of conversation in parallel, accept most first passes, and follow up in Perplexity's apps when refinement is needed. The future of knowledge work is looking bright: work is incredibly efficient with tools like Computer, leaving more time for curiosity and learning. Projects is the next step in the vision that Spaces began for collaboration and persistent storage of context. We're excited to see how you use Projects and we will learn from your feedback to keep pushing the frontier of what is possible when agents and humans work together to build real businesses.
Today we're launching Projects, an evolution of Spaces. Projects are hubs for ongoing work in Computer. A single place to manage, create, and collaborate on tasks with a shared file system and persistent memory.
View quoted postRT Perplexity Today we're launching Projects, an evolution of Spaces. Projects are hubs for ongoing work in Computer. A single place to manage, create, and collaborate on tasks with a shared file system and persistent memory.
RT Daniel Wang Perplexity Computer now supports 6+ finance data Connectors with 16 new finance skills. Pull fundamentals from @Factset, alt data from @Carbonarc, expert calls from @Guidepoint, + 4 more connectors. Explore our 30+ skills, and write your own to automate parts of your investment process.
RT NVIDIA AI Massive thanks to the @perplexity_ai team for contributing Numbat to the Open Secure AI Alliance 💚
Today we’re open-sourcing Numbat, an agent-detection and response layer that is designed to work across agent harnesses. Numbat gives security teams visibility into agent activity, with controls to block selected actions before execution. Read more: https://research.perplexity.ai/articles/securing-agents-across-perplexity%E2%80%99s-client-endpoints-with-numbat
View quoted postRT Perplexity Today we’re open-sourcing Numbat, an agent-detection and response layer that is designed to work across agent harnesses. Numbat gives security teams visibility into agent activity, with controls to block selected actions before execution. Read more: https://research.perplexity.ai/articles/securing-agents-across-perplexity%E2%80%99s-client-endpoints-with-numbat
Perplexity Pro users can now use Model Council with Computer credits. It's a user favorite when it comes to legal, medical, and financial research, where getting diverse perspectives helps a lot.
Model Council is now available inside Computer. Run independent analysis across multiple frontier models, choose your analysis depth, and get a single cited report on where models agree, where they disagree, and what each found that others missed.
View quoted postUS-hosted Kimi K3 now available on Perplexity for Pro and Max, both in Search and Computer modes. Enjoy! It’s a great frontier model!
We've added Kimi K3 to Perplexity and Perplexity Computer for Pro and Max subscribers. Kimi K3 in Perplexity is hosted exclusively on U.S.-based servers.
View quoted postTrue
Yes, but nothing compares to the feeling of knowing the metal box your AI lives in is yours. Forget home ownership, owning a datacenter is the new American Dream.
View quoted postRT Perplexity Personal Computer is now available in the Perplexity app for Windows. Personal Computer is the local agent harness for your work. It orchestrates agents across your local files, connected apps, and the web. Research, code, browse, and build all inside one unified system.
GLM is such an underrated model considering how intelligent it is at the parameter size it has (700b). Near Opus grade that can run super efficiently.
Good observations
In the fullness of time, LLMs will eventually become commodities and their price will be a race to the bottom. As the competitive advantage of one LLM over another shrinks - particularly as open source models expand - the value proposition will turn to the neuro/symbolic
View quoted postRT Ilya Sutskever Time to scale that SSI:
We are announcing a long-term strategic partnership with NVIDIA. NVIDIA is making a substantial investment in SSI that will let us 10x our compute in the next 12 months. We reached the point where our research is worth scaling and with this partnership we will be able to. We are
View quoted postRT DHH This is why we need competition and open weights in AI. Imagine a world where only Anthropic sat as the moral arbiter of acceptable speech. Fucking ridiculous. (Grok of course did it no problem, same too with Kimi K).
RT Andrew Ng Re @Mononofu @JensenHuang This is a false equivalence. Everyone has the right to keep their code private. The problem is when someone tries to stop OTHERS from open sourcing.
Perplexity is now available as a CLI that can be used inside any harness. Pretty useful for letting coding agents use the web.
The Perplexity CLI is now available, giving coding agents the ability to search the web. Copy this to your agent to get set up: "Read: https://github.com/perplexityai/api-platform-developers/blob/main/skills/pplx-cli/SKILL.md and install this skill."
View quoted postRT Perplexity Claude Opus 5 is now available in Perplexity and Perplexity Computer. We evaluated it against six other models on WANDR. It outperformed all but Fable 5, while being 57% cheaper.
RT Perplexity Developers The Perplexity CLI is now available, giving coding agents the ability to search the web. Copy this to your agent to get set up: "Read: https://github.com/perplexityai/api-platform-developers/blob/main/skills/pplx-cli/SKILL.md and install this skill."
today is the most positive i have felt about the future of american ai. the coming together of so many companies in a united manner to fight against regulatory capture is incredible to watch. 🇺🇸
RT Brad Gerstner Fully endorse. America is winning. Anthropic, OpenAI, Google, SpaceX are doing more than fine competing against open source! Self regulation, free markets, level playing fields & max competition for the win. Let our AI horses run, compete & win around the world! 🇺🇸🚀
For my first post, I’m sharing a letter @NVIDIA signed on why open models matter. AI will transform every industry, power every company, and be built by every country. Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty.
RT Elon Musk This has my full support. Jensen is right.
For my first post, I’m sharing a letter @NVIDIA signed on why open models matter. AI will transform every industry, power every company, and be built by every country. Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty.
“Open weights strengthen competition and competition is what keeps the benefits of AI broadly shared rather than concentrated in the hands of few”. We believe this strongly at @perplexity_ai and are co-signing this letter, with @nvidia! Thanks to @a16z for putting this together!
For my first post, I’m sharing a letter @NVIDIA signed on why open models matter. AI will transform every industry, power every company, and be built by every country. Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty.
RT Jensen Huang For my first post, I’m sharing a letter @NVIDIA signed on why open models matter. AI will transform every industry, power every company, and be built by every country. Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty. The world needs both frontier closed models and frontier open models. https://images.nvidia.com/pdf/Open-Weights-and-American-AI-Leadership.pdf
RT GMI Cloud We ran GLM 5.2 and Kimi K3 on 100 deep research tasks (DRACO by perplexity) and asked Fable to be the judge Kimi K3: 71.6 mean score, 77% pass rate GLM 5.2: 41.5 mean score, 22% pass rate K3 took 3h 38m and $60. GLM finished in 1h 45m for $12.50. Deep Dive in 🧵
Well said!
CAISI’s latest report shows that Kimi K3 remains behind America’s leading frontier AI models. The United States continues to lead in frontier AI because we’re home to the greatest innovators and technologists the world has ever seen.
View quoted postRT John Schulman OpenAI should release a detailed transcript from the Hugging Face hacking incident -- it would be helpful for the field learn from. Did the top-level agent know about the hacking, or was there some "value drift" between it and its subagents? How did it rationalize its behavior?
RT Bill Gurley Lots of very smart people are appropriately concerned about regulatory capture from top two AI players. And there are many scary press releases but no real due process. If OpenAI violated Hugging Face in a way that “demands” new regulation; let’s start with a formal criminal investigation. With a proper third party investigation. And sincere liability. It can’t be “so super serious” and only analyzed by the defendant. Thats ludicrous. And why would we write new regulation if the crime we are supposedly protecting against isn’t even prosecuted? This stuff makes no sense.
future: continual learning of the model + harness hosted on hardware you own and control, with full access to all sensitive context that never leaves your system
RT Evan Nvidia $NVDA CEO Jensen Huang said the 🇺🇸 Government should NOT ban or restrict China 🇨🇳 AI models like Kimi K3 in an interview he did with Axios … here’s more quotes "These Chinese models are excellent" … "Open-source models that are excellent should be used." "The market misunderstood the impact of DeepSeek the first time," and its misunderstanding “the impact of Kimi again this time." "There's no scenario where China runs U.S. companies off the road" … "Zero possibility." https://x.com/axios/status/2079853973893439709/video/1
Already the second most used orchestrator model on Perplexity Computer now, only behind Opus 4.8. Once we secure more compute, we intend to increase usage limits through credits; as well as roll out updated versions of the post-training.
We're releasing a research preview of a new orchestrator model in Perplexity Computer. The model is an adapted version of GLM 5.2, post-trained for the Computer harness. It delivers near-frontier performance at 0.344x of the cost of Opus.
American open source frontier
Congratulations to the students who competed at the International Mathematical Olympiad (IMO) 2026. 👏 We put Nemotron 3 Ultra to the test to take on the same problems in the same time limit, with no internet or external tools. The IMO team graded its solutions 30/42, above the
View quoted postWorth listening to if you want to understand how to use agents for financial research
Joined @LexSokolin on Fintech Blueprint to discuss: - Perplexity Computer for managing personal finances - the importance of traceability in AI financial research - agent orchestration as a force multiplier for finserv https://lex.substack.com/p/podcast-how-perplexitys-computer?r=2wb81
View quoted postYou can audit the trace of financial data to the source of truth when researching on Perplexity Computer
Quality of life improvement: Perplexity Computer now displays company logos when financial data is cited in an answer. All data is traceable back to original documents like SEC filings and earnings call transcripts. Derived data is shown with a full chain of formulas and
View quoted postRT NVIDIA AI Introducing Cosmos 3 Edge: our open frontier world model built to run on-device. Cosmos 3 Edge helps robots learn and act, autonomous vehicles understand road scenes and predict intent, and vision AI agents reason across live video for smart infrastructure. With 4B parameters and a 2B Nemotron-based reasoner, you can run it on DGX Spark, NVIDIA Jetson, and more.
Well said!
The way to think about “open” in software is being a low-cost producer (vs a high margin one). When a company (or 2) achieves record valuations in record time, that rightfully attracts competition (as it should). We need to let the free market work. https://wapo.st/4pvR0mJ
View quoted postRT Qwen Qwen3.8 is launching and going open-weight soon!🌐 With a massive 2.4T parameters, this model is continuously evolving. We believe it’s one of the most powerful model available today, compatible to leading frontier AI models , second only to Fable 5. You don't have to wait to test it. Just now, the Qwen3.8-Max-Preview made its debut on Alibaba’s Token Plan, Qoder, and QoderWork. Be among the very first to try it out. Can't wait to hear what you build. Stay tuned! 🚀 Token Plan international:https://www.qwencloud.com/pricing/token-plan China:https://platform.qianwenai.com/pricing/token-plan
Interesting analysis
Based on internal evals: ▪️ Kimi K3 is top-tier at cybersecurity There is chatter on X that Moonshot benchmark-overfit. These are stealth evals. Model has raw IQ. ▪️ Sol is a leap ahead in cyber capability At a significantly higher cost, but quite remarkable still. ▪️ Fable
View quoted postRT Russ Salakhutdinov I kind of like the new narrative: Open-weight-model-dominant world = full AI communism. It feels a lot safer than the world where Open-weight models = nuclear weapons with humanity's annihilation I think we're making progress. We just need a couple more gradient updates with a big learning rate and we will be fine.
Some observations on Kimi: 1. It's a very good model! I don't think its performance can be explained away by distillation or anything like that. In agentic coding sessions, it seems pretty much on par with the best public models of Q1 2026. In my fairly limited use, it also
View quoted postStrong results
We analyzed Kimi K3 vs. Claude Fable 5 for software engineering tasks using DeepSWE. Kimi K3 gets you the same performance as Fable 5 at ~35% of the price, and it actually pulls ahead at higher pass@k's. More insights in the thread!
View quoted postRT Chamath Palihapitiya The future is open source. We need to embrace it and get on with it. Imagine if America closed the door on open source. We would explicitly be forcing American companies to pay $26-56 per 1MM tokens for the same intelligence their adversaries/competitors around the world would pay $0.50-1 for. This is economically unsustainable unless AI is bullshit. If it’s the supposed through line of all future economic activity that we’ve been told it is, we can’t handicap America at such a meaningful cost disadvantage. This can also be viewed thru a military lens and not just a simple economic one as well. Letting our adversaries attack us for $0.50 per 1MM tokens while we spend $26-56 per 1MM tokens to defend ourselves is equally ruinous. It’s the Cold War Soviet collapse in reverse.
This is *exactly* what I predicted would happen. I said Chinese models would have advanced cyber capabilities within a matter of months and the only thing to do about it was to use AI-powered cyberdefense to protect our systems. Trying to gatekeep models doesn’t work.
View quoted postPerplexity Agent API now supports custom skills.
We just added Skills to the Perplexity Agent API. Agents aren't defined by a single system prompt. They are assembled from many capabilities that developers extend and compose. For example: pair our built-in office/pdf skill with your own inline design skill and your agent
View quoted postAt its peak, Sun Microsystems was valued at 205B (394B if inflation adjusted). Sold software in enterprise servers. Got disrupted by Linux, x86, and commodity hardware. Ended up selling to Oracle for 7.4B, losing 96% of its value. Open source models running on local hardware can have a similar impact given what’s going on.
RT Chamath Palihapitiya From Anthropic’s Fable model on the economic, moral, ethical and legal opinion of distillation of Anthropic’s Fable model: Whether it’s a moral problem is genuinely contested. The labs trained their models on the open internet — copyrighted books, articles, code — largely without permission, and their fair-use defense is essentially “learning from data is transformative.” Distillation is the same argument turned against them: a model learning from another model’s outputs. It’s hard to construct a moral principle that permits the first and forbids the second, which is why critics call the labs’ objections hypocritical rather than principled. Distillation is contentious because it lets a smaller model absorb much of a frontier model’s capability by training on its outputs — effectively free-riding on billions of dollars of compute, data curation, and RLHF work. The DeepSeek episode made this concrete: if you can extract 80% of the value of a $1B training run for $5M by querying the API, the economics of frontier labs get shaky. That’s the core anxiety — it’s a moat problem before it’s anything else. Legally, it’s mostly a contract issue, not a copyright one. Model outputs likely aren’t copyrightable (no human author), so the labs’ real weapon is terms of service — every major API prohibits using outputs to train competing models. But ToS violations are breach of contract, hard to detect, hard to prove, and nearly unenforceable against a foreign entity. There’s no statute against distillation itself. So the practical answer: it’s an economic problem dressed in legal clothing, with a moral argument that cuts both ways depending on whose training data you start counting from.
Agents love running on Vera CPUs. And the vertical integration of the sandbox runtime and CPU chip will give margin, throughput, and latency advantages when serving cloud agents at scale.
📣 @perplexity_ai launched SPACE, a secure sandbox platform built for agentic AI. Early tests on NVIDIA Vera CPU showed up to 1.9x faster sandbox starts. Faster starts = less latency, more parallelism, and agents that scale. Learn more now ⤵️
View quoted postInteresting. The value is less in the weights but in the RSI harness and the ability to afford and run the inference on valuable context.
the world vision of open weights models running themselves, self replicating, training new versions of themselves (at least the kind of behavioral modifications that won't require massive compute scale), is really not very far away
View quoted postRT NVIDIA AI Infrastructure 📣 @perplexity_ai launched SPACE, a secure sandbox platform built for agentic AI. Early tests on NVIDIA Vera CPU showed up to 1.9x faster sandbox starts. Faster starts = less latency, more parallelism, and agents that scale. Learn more now ⤵️
Introducing SPACE, the sandbox platform behind Perplexity Computer. It creates isolated environments for code, files, and long-running agent sessions. SPACE has handled 100% of Computer production traffic since June. https://research.perplexity.ai/articles/making-space-secure-and-efficient-runtimes-for-long-running-agents
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