
NVIDIA Perplexity Portable Computer Now Available on Windows, Powered by NVIDIA RTX
Official announcement republished verbatim (not rewritten or translated); source linked on this page.(Original language:English)

As local models become more capable, AI agents can handle more work directly on a PC while keeping sensitive information on the device.
Portable Computer is a local version of the agent Perplexity Computer that plans and carries out multistep tasks. Accelerated by NVIDIA GPUs, it uses local models to analyze data, bring together information across files and handle recurring work. Sensitive information stays on device, and locally completed work doesn’t consume Perplexity Computer credits. Users can also orchestrate work up to cloud models for more advanced research and reasoning.
Today, Perplexity is adding Portable Computer in the Perplexity app for Windows on compatible NVIDIA GeForce RTX PCs and NVIDIA RTX PRO Workstations , bringing powerful agentic AI to more Windows PC users. The release builds on existing support for NVIDIA DGX Spark systems and RTX PCs running Linux .
Perplexity brings local and cloud AI together in one app, letting users work with sensitive files on their PCs and take advantage of Computer’s built-in tools such as the built-in browser and proprietary SPACE sandbox.
For tasks that call for more advanced reasoning, Portable Computer can also identify when a task needs cloud support, asking the user for permission before sending information off-device.
The app simplifies setup with a local model, such as Qwen 3.8 27B, that is post-trained to work with Perplexity Computer and optimized for NVIDIA RTX GPUs. Users can put the agent to work without having to research models or configure the complex software stack typically required to run local AI.
Connectors for Microsoft Outlook, OneDrive, Word, Google Drive, Gmail, Slack and GitHub extend that experience across the files and apps already part of users’ daily workflows.
For example, the agent can help with:
Portable Computer is available for NVIDIA GeForce RTX and RTX PRO GPUs with 24GB or more of VRAM. NVIDIA DGX Station support is expected to come soon.
Try Perplexity Portable Computer today.
🧠Z.ai’s GLM 5.3 Flash provides impressive performance and visual intelligence at low cost, optimized for DGX Station and dual DGX Spark systems.
🐋DeepSeek-v4.1 Flash significantly reduces key-value cache memory demands and operating costs for complex AI agent workloads, delivering remarkable intelligence per dollar.
⚡Qwen has released Qwen3.8-Flash-Next , an open-weight multimodal mixture-of-experts model, and an early preview of Qwen4, which can run locally on a single DGX Spark with NVFP4 and punches well above its weight.
👾GLM 5.3 is Z.ai’s 744-billion-parameter flagship model, tuned for agent sessions that run for hours on DGX Station and a cluster of four DGX Spark systems.
See notice regarding software product information.

Specifications
- Compatible GPUs
- NVIDIA GeForce RTX和RTX PRO GPU,24GB或更多VRAM
- Platform
- Windows
- Supported Features
- Microsoft Outlook、OneDrive、Word、Google Drive、Gmail、Slack和GitHub
- Model
- Qwen 3.8 27B
- Agent
- Perplexity
- Real-time Features
- 自動識別任務需要雲支援,並請求使用者許可後傳送資訊
Sources
Specs and launch info are cited from official sources; the analysis is our own original writing.
With local models becoming more capable, AI agents can now handle more tasks directly on a PC while keeping sensitive information on the device.
Portable Computer is a local version of the agent Perplexity Computer and is now available on compatible NVIDIA GeForce RTX PCs and NVIDIA RTX PRO Workstations.
It uses local models to analyze data, integrate information across files, and handle repetitive work, without consuming Perplexity Computer credits.
Pros
- Keeps sensitive information on the device
- Simplifies setup without requiring research into models or configuring a complex software stack
- Provides rich workflow integration, such as Microsoft Outlook, OneDrive, and more
Cons
- Currently supports specific GPU models only
- Cloud support functionality is expected soon but is not currently available
- Local models may require more VRAM
Discussion