内容历史
We built a replacement for AWS DynamoDB, a key-value database for fast web content fetches. This was done with two engineers and hundreds of persistent Computer agents over two months. Migrating to our in-house database will save us up to a hundred million dollars yearly.
We’re publishing research on how we built CobbleDB, our key-value database that serves web content for Perplexity search. Two engineers and a team of hundreds of proactive, always-on AI agents built the core infrastructure in two months.
RT Perplexity Perplexity Computer will now come pre-installed on HP ZBook Ultra G3a. . Use Computer to run complex multi-step work from a simple interface. Computer agents are grounded in accurate deep research and connected to hundreds of tools, now including Autodesk.
Computer is turning into a workspace of humans and AIs.
You can now tag coworkers in Computer sessions. Use @ to mention and share a session with someone. Available now on the web for all Computer users.
Perplexity Computer makes you money.
Where are agentic traders coming from? Here's the breakdown of where agentic trading volume came from last week: Perplexity - 26.8% Claude - 19.3% Grok - 15.3% ChatGPT - 1.1% Claude Code - 0.7% CLI/Other - 36.8%
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Another leaderboard win for Nemotron 🏆 Nemotron 3 Embed 8B ranks #1 for combined nDCG@10 on the Q2D-Web benchmark, tested across 190M web documents and nearly 70K agent-reformulated queries in 10 languages. Shoutout to @perplexity_ai for putting it together.
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Perplexity has joined the Rust Foundation. We believe in supporting the people who build reliable open-source software. By joining the Rust Foundation, our goal is to improve how people and agents build with Rust.
Wow!
🚀 Introducing DeepSeek-V4.1-Flash: smarter, faster, more efficient. 🔹 Introducing the smallest model in our new architecture family, with native visual understanding. 🔹 Designed for greater capability, faster inference, higher throughput, and scaling to larger models. 1/6
Monumental accomplishment!
We’re sharing a solution to the Navier-Stokes Millennium Prize Problem, one of the deepest problems at the frontier of mathematics. The proof was produced by a group of agents, using an OpenAI next-generation model significantly more capable than GPT-6 Astra. The problem
A deep dive into how Perplexity serves search results at scale: embeddings for ranking, GPU-based model inference, request batching, running inference servers, and handling latency/throughput trade-offs.
Every answer in Perplexity starts with embedding and ranking models picking the most relevant results for the query. Today we published research on how we built SoTA serving infrastructure behind those models. Read the research: https://www.perplexity.ai/hub/blog/fast-embeddings-on-gpus
Congrats to @OpenAI on building the industry's frontier model: GPT-6 Astra. It's far ahead of every other model on wide and deep research tasks, while also being more cost-effective. We'll be bringing this model up on Perplexity Computer for all Pro and Max users soon!
We evaluated GPT-6 Astra on WANDR. It scored 0.682 at $11.98 per task, the highest score of any model we tested. GPT-6-Astra scored 13.5% higher than Fable 5.1 at 6.1% lower cost, and 27.0% higher than Opus 5 at 3.3% higher cost.
RT Perplexity Developers 42 models are now available through the Perplexity Agent API, including the open-weight GLM 5.3 from @Zai_org. Switch models by changing one field in your request. Add fallbacks to keep your agent running if a model becomes unavailable. https://pplx.ai/agent-api-glm
Private, Personal, Powerful AI.
Best-in-class PII Detection...running entirely on your device 🤯 https://www.perplexity.ai/hub/blog/pii-trace-detecting-personal-data-before-it-leaves-the-device
Live demo of Portable Computer (aka a fully local runtime of Perplexity Computer) on DGX Spark
Want to see @perplexity_ai Portable Computer running locally on NVIDIA DGX Spark? 👀 Tune in tomorrow, 9/2 at 12:30 p.m. PDT, to see live demos showcasing private file analysis, connected tools and more.
Agentic trading, market analysis, and monitoring on Perplexity Computer with Coinbase
Coinbase for Agents is now live on Perplexity Computer. Let your Computer trade, analyze markets, and execute workflows. One of 20+ financial connectors. No APIs. No MCP setup. Just click connect. @perplexity_ai Computer works for you. Now it works with Coinbase.
Fable is the frontier model by a good margin right now. Enjoy it on Perplexity Computer as an orchestrator for high-stakes tasks. Computer still uses GPT 5.6 (Terra) models as cost-efficient subagents while taking advantage of Fable's frontier planning capabilities.
Congrats Tim on an incredible journey at Apple. Few people have ever shipped at that scale without letting the bar for excellence slip. You've raised the standard for all of us to aspire to; thanks for everything.
Sending lots of love to the Apple community on my last day as CEO. My title changes tomorrow, but the love I have for the Apple community never will. Thank you for being a constant source of inspiration. My gratitude is endless, and I’m excited for the next chapter!
View quoted postRT 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.
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.
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 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.
Dense 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. 🧵
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 👑
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.
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 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.
A 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.
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.
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 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
