NVIDIA Gives Devs More Tools To Integrate RTX & AI Features – TensorRT for Unreal Engine Delivers 50% Boost, ComfyUI Made Easy On Any RTX GPU

Hassan Mujtaba
The GeForce RTX graphics card is displayed between large letters 'RTX' and 'AI' with green light beams in the background.

NVIDIA has expanded its RTX & AI feature set with more capabilities provided to developers for integration within their latest apps, including games.

NVIDIA Bets Big on Its "AI PC" Ecosystem With RTX GPUs, Provides Devs With New & Improved Tool Sets

The NVIDIA RTX and AI PC technologies are one of the industry's most advanced tool sets offered to developers. These tools make integration of the latest features and capabilities in apps & games easier than ever.

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Today, NVIDIA has announced more integrations that help developers create next-gen experiences. Last month, NVIDIA rolled out its DLSS 4.5 SDK, allowing developers to integrate the new DLSS 4.5 feature set, such as Dynamic Multi-Frame Generation, Multi-Frame Generation 6X, and 2nd Generation Transformer Model in games through Streamline.

We also have some exciting developer updates. Notably, game developers can now begin integrating NVIDIA DLSS 4.5 with Dynamic Multi Frame Generation, Multi Frame Generation 6X, and the second-generation transformer model for NVIDIA Super Resolution.

In addition to that, NVIDIA also has more tools that are being made available to developers, with the highlights listed below:

  • A new NVIDIA TensorRT for RTX plugin for Unreal Engine’s Neural Network Engine (NNE) is now available. The TensorRT for RTX plugin provides a runtime for Unreal Engine’s NNE, enabling efficient deployment of AI models directly within real-time applications. In practice, developers can see 1.5x performance improvements compared to DirectML-based approaches.
  • NVIDIA Kimodo, a research project, can now be used for easier motion generation. It can help reduce iteration time and expand the range of character movement in a project, while maintaining consistency with existing animation systems. Learn more about Kimodo
  • We’ve put together a guide to using ComfyUI to help produce pre-production assets. It walks creators through three production-ready workflows from the GenAI Creator Toolkit, adapted from the NVIDIA GTC 2026 Deep Learning Institute course “Create Generative AI Workflows for Design and Visualization in ComfyUI.” Each workflow is standalone, runs on any NVIDIA RTX GPU with 16 GB or more of VRAM, and works on both Windows and Linux. Read more here
  • Finally, you can check out more than a dozen new sessions from GDC and GTC. Some of the standout sessions can be found here.

First up is the new NVIDIA TensorRT for RTX plugin designed for Unreal Engine's NNE (Neural Network Engine). This is now available, allowing developers to harness TensorRT capabilities of the latest RTX GPU (Turing with compute capability 7.5 up to Blackwell with compute capability 10.0) family to easily deploy AI models within applications. With this, developers can get a nice 50% speed-up versus DirectML-based approaches. NVIDIA's TensorRT for RTX already offers a 2x performance boost on desktop PCs, and is supported across all RTX GPUs.

NVIDIA is also offering full ComfyUI support with a new capability allowing developers to produce pre-production assets. This capability is offered across all RTX GPUs with 16 GB or higher memory and can be utilized on both Windows and Linux platforms.

Besides this, NVIDIA is working towards powering future RTX and AI capabilities with advanced and cutting-edge features. The company is going big-time into Neural Rendering, which brings a 1,000,000x leap versus the current generation of GPUs, and is also readying new algorithms to drive Path Tracing by 3x.

At the same time, NVIDIA has Neural Texture Compressions being prepped to cut VRAM usage by 85% and also boost image quality within the same budget. Next-gen games such as Witcher IV and more are also deploying these advances to deliver a true visual feast that will define the future of gaming.

Hassan Mujtaba Photo

About the author: A Software Engineer by training and a PC enthusiast by passion, Hassan Mujtaba serves as Wccftech's Senior Editor for hardware section. With years of experience in the industry, he specializes in deep-dive technical analysis of next-generation CPU and GPU architectures, motherboards, and cooling solutions. His work involves not only breaking news on upcoming technologies but also extensive hands-on reviews and benchmarking.

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