Lenovo is expanding the possibilities of local AI computing with the new Lenovo Yoga Pro 9n (15”, 11) and Lenovo Yoga 9n 2-in-1 (16”, 11), powered by NVIDIA RTX Spark. Designed for creators and developers, the new laptops combine NVIDIA's AI and RTX technologies with substantial unified memory to support demanding AI development, content creation, software development and 3D rendering directly on the device.
As AI becomes an increasingly important part of creative and professional workflows, running models locally offers users greater control over their data, reduced dependence on cloud computing and the flexibility to experiment with AI tools without sending every request to an external service. With NVIDIA RTX Spark, Lenovo is bringing advanced local computing capabilities to premium portable devices, making it easier for creators and developers to work with sophisticated AI models alongside their existing applications.
Local AI Computing
Traditional AI workflows often depend on cloud-based infrastructure or powerful desktop workstations. These approaches can provide substantial computing resources, but they may introduce additional costs, network dependencies and data-handling considerations. The technology is beneficial for those who work with confidential data, including lawyers, doctors, journalists and researchers.
NVIDIA RTX Spark combines NVIDIA AI and RTX technologies with the CUDA software stack to support increasingly sophisticated AI workloads locally. By bringing AI acceleration and graphics capabilities together in a portable computing platform, it allows users to explore AI-assisted workflows alongside conventional creative and development applications.
A key capability of the new Lenovo Yoga laptops is their unified memory architecture. The Yoga Pro 9n supports up to 128GB of unified memory, while the Yoga 9n 2-in-1 offers up to 64GB, both running at 9400 MT/s. This substantial memory capacity gives users more room to work with demanding applications, large datasets and memory-intensive AI models.
For AI workloads, available memory can be as important as raw processing performance. Larger models and more complex workflows require space for model parameters, intermediate computations and other working data. A system with greater memory capacity can accommodate workloads that might otherwise require a more constrained model configuration or a different computing environment.
The combination of NVIDIA's AI technologies, RTX acceleration and the CUDA ecosystem also provides developers with a familiar foundation for building and experimenting with accelerated applications.
Multi-step workflows
One of the platform's distinguishing capabilities is its support for coordinating multiple specialised AI agents to automate complex tasks across applications. These devices are prepared for the agentic AI era, that are far more capable than generative AI.
Instead of using AI only for isolated operations, such as generating an image, removing an object from a photograph or suggesting a chunk of code, users can explore workflows in which multiple AI capabilities contribute to a larger task.
For example, a creative project could involve generating visual assets, refining images, preparing content and moving between editing applications. A software development workflow could involve analysing code, assisting with implementation and supporting testing. By coordinating specialised AI agents, more of these activities can potentially be connected into a broader process.
Local execution gives users the opportunity to develop and test these workflows on their own systems, with greater control over their working environment and data. The precise level of automation and application integration will depend on the models, software and tools being used.
For developers, this creates opportunities to experiment with agent-based applications and local AI pipelines. For creators, it offers a way to incorporate more sophisticated AI-assisted processes into existing production workflows.
Lenovo Yoga Pro 9n
The Lenovo Yoga Pro 9n (15”, 11) is designed for users who prioritise computing performance and memory capacity in a portable system.
Powered by NVIDIA RTX Spark and equipped with up to 128GB of unified memory, the laptop supports local AI development, software development, content creation and 3D rendering. Its NVIDIA RTX capabilities also extend to gaming, allowing users to combine professional creative workloads and entertainment on a single device.
The laptop pairs its computing capabilities with a PureSight Pro OLED display designed for colour-sensitive creative work. Lenovo X Power thermal architecture supports sustained performance within its slim chassis, while creator-focused connectivity accommodates professional peripherals and external displays.
For users working with AI models, editing high-resolution video, rendering complex scenes or developing software, the Yoga Pro 9n brings these workloads together in a single portable platform. Its combination of substantial unified memory and accelerated computing is intended for creators and developers who need greater local computing capability without moving to a conventional desktop workstation.
Lenovo Yoga 9n 2-in-1
The Lenovo Yoga 9n 2-in-1 (16”, 11) brings NVIDIA RTX Spark to a convertible design intended for users who need both local computing performance and flexibility in how they work.
With up to 64GB of unified memory, the laptop supports demanding creative workloads and local AI applications. Its 360-degree hinge allows it to switch between laptop, tablet, tent, stand and canvas modes, adapting to different stages of a project.
A distinctive feature is its dual-surface pen experience. Users can write or draw directly on the PureSight Pro OLED display or the haptic Force Pad, using the Yoga Pen Gen 2 for sketching, annotation, illustration and detailed editing.
The NVIDIA RTX platform also accelerates compatible creative applications, including Adobe Premiere Pro and ComfyUI, as well as local AI models such as FLUX and LTX. This gives creators a platform for combining conventional production tools with AI-assisted image and video workflows.
The Yoga 9n 2-in-1 is designed for users who want to move between developing an idea, editing content and presenting their work without switching between separate devices.
What This Means for Users
Running compatible AI workloads locally can reduce the need to transfer sensitive documents, creative assets or proprietary code to cloud services. Users retain greater control over where their data is processed, subject to the applications and services they choose.
Once the required models and software are installed, compatible workloads can run without a continuous internet connection. This can be useful when travelling, working remotely or operating in environments with limited connectivity.
Unified memory allows users to accommodate larger models and more complex working datasets than systems with more limited memory capacity. Actual model compatibility and performance depend on model size, quantisation, software support and the workload.
NVIDIA's accelerated computing technologies support a range of AI, graphics and content-creation applications. Users can incorporate compatible AI tools into established workflows rather than relying exclusively on separate cloud-based services.
Developers can explore local model inference, AI-assisted coding and agent-based applications on their own systems. This can make iterative development and testing more convenient, particularly when workloads involve sensitive data or frequent experimentation.
The Yoga Pro 9n combines AI development and professional creative capabilities with RTX gaming. The Yoga 9n 2-in-1 adds convertible versatility and pen input for users whose work involves sketching, editing, annotation and collaboration.
These benefits depend on the applications, models and configurations being used. Local execution does not automatically eliminate internet requirements, and some large models or particularly demanding workloads may still benefit from cloud or workstation-class resources.
Advancing the Future of Personal Computing
The introduction of NVIDIA RTX Spark-powered Yoga laptops reflects a broader shift towards personal computers capable of handling increasingly sophisticated AI workloads locally.
As AI applications evolve from individual prompts and isolated operations towards more complex, multi-step processes, computing platforms need to accommodate both demanding models and the workflows built around them. Memory capacity, accelerated computing, software compatibility and the ability to integrate AI into existing applications will all influence how effectively users can take advantage of these developments.
With the Yoga Pro 9n and Yoga 9n 2-in-1, Lenovo is bringing these capabilities to two distinct audiences: creators and developers seeking a performance-focused portable system, and users who want advanced local computing alongside flexible, pen-first interaction.
Together, the devices extend the role of the laptop from a tool for running applications to a platform for developing, testing and incorporating AI into everyday creative and professional work.
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