NVIDIA introduces New Broadcast AI Features for GeForce RTX 50 Series GPUs


January 30, 2025 by our News Team

NVIDIA introduces the powerful and game-changing GeForce RTX 5090 and RTX 5080 GPUs, equipped with advanced technology to enhance creative performance and productivity for various industries.

  • Significantly faster generative AI content creation
  • Increased memory and bandwidth for smoother performance and quicker rendering times
  • Improved video quality and faster export times for video editors and livestreamers


Introducing the Geforce RTX 5090 and RTX 5080 GPUs

The tech world is buzzing with excitement as nVidia rolls out its latest powerhouses: the GeForce RTX 5090 and RTX 5080 GPUs. Built on the NVIDIA Blackwell architecture, these GPUs are designed to supercharge generative AI content creation and elevate creative performance to new heights.

What makes these GPUs stand out? For starters, they come equipped with fifth-generation Tensor Cores that support FP4 precision. This means you can run generative AI models with significantly less VRAM—under 10 GB for Black Forest Labs’ FLUX models, compared to the hefty 23 GB needed for FP16. Imagine generating stunning images in just over five seconds with the RTX 5090, a remarkable leap from the 15 seconds it would take on FP16 with the RTX 4090. That’s a game changer for anyone in the creative space!

Power and Performance

Let’s talk numbers. The GeForce RTX 5090 boasts a whopping 32 GB of ultra-fast GDDR7 memory and a staggering 1,792 GB/sec of total memory bandwidth—an impressive 77% increase over its predecessor, the RTX 4090. This means smoother performance and quicker rendering times, which is music to the ears of creators everywhere. The RTX 5080, while slightly less powerful, still packs a punch with 16 GB of GDDR7 memory and 960 GB/sec of bandwidth, a solid 34% increase over the RTX 4080.

But that’s not all. The new GPUs come with ninth-generation encoders and sixth-generation decoders that support 4:2:2, enhancing encoding quality for HEVC and AV1 formats. Export times are cut by a third, so you can spend less time waiting and more time creating.

NVIDIA Broadcast App Gets an Upgrade

As if the new GPUs weren’t enough, NVIDIA has also released an updated version of its Broadcast app. This latest iteration introduces two exciting beta AI effects: Studio Voice and Virtual Key Light. Studio Voice transforms your microphone input to sound like a high-end studio mic, while Virtual Key Light ensures your lighting is always on point, mimicking the effects of a physical key light. Perfect for podcasters and streamers, these features require a GeForce RTX 4080 or higher—so you’ll want to make sure you’re equipped!

The app update also enhances existing features, making voice quality even better with Background Noise Removal and adding natural eye movements with Eye Contact. Plus, the revamped user interface allows for more simultaneous effects and includes handy tools like a GPU utilization meter.

Boosting Creative Workflows

For video editors, the GeForce RTX 50 Series GPUs are a dream come true. With support for 4:2:2 hardware, you can decode a single video source at up to 8K at 75 frames per second, or handle multiple 4K sources like a pro. The RTX 5090’s three encoders and two decoders mean you can export videos 40% faster than the RTX 4090 and an astounding 4x faster than the RTX 3090.

Livestreamers aren’t left out either. The ninth-generation NVENC technology improves video quality by 5% for HEVC and AV1 encoding, meaning your streams on platforms like Twitch and YouTube will look sharper than ever.

3D artists will appreciate the RTX 5090’s 32 GB of memory, which allows for seamless work on massive projects across various platforms. With the new DLSS 4 technology making its way into popular 3D applications like D5 Render, animators can look forward to smoother frame rates and enhanced performance.

Get Ready for the Future

The GeForce RTX 50 Series isn’t just about raw power; it’s about enhancing creativity and productivity across the board. Developers eager to integrate these new features can access NVIDIA’s SDKs to make the most of this technology.

So, whether you’re a video editor, a 3D artist, or a livestreamer, the new GeForce RTX 5090 and 5080 GPUs are here to elevate your creative game. Stay tuned for more updates on performance, app compatibility, and the exciting world of emerging AI technologies. The future of content creation is looking brighter than ever!

NVIDIA introduces New Broadcast AI Features for GeForce RTX 50 Series GPUs

NVIDIA introduces New Broadcast AI Features for GeForce RTX 50 Series GPUs

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Background Information


About nVidia:

NVIDIA has firmly established itself as a leader in the realm of client computing, continuously pushing the boundaries of innovation in graphics and AI technologies. With a deep commitment to enhancing user experiences, NVIDIA's client computing business focuses on delivering solutions that power everything from gaming and creative workloads to enterprise applications. for its GeForce graphics cards, the company has redefined high-performance gaming, setting industry standards for realistic visuals, fluid frame rates, and immersive experiences. Complementing its gaming expertise, NVIDIA's Quadro and NVIDIA RTX graphics cards cater to professionals in design, content creation, and scientific fields, enabling real-time ray tracing and AI-driven workflows that elevate productivity and creativity to unprecedented heights. By seamlessly integrating graphics, AI, and software, NVIDIA continues to shape the landscape of client computing, fostering innovation and immersive interactions in a rapidly evolving digital world.

nVidia website  nVidia LinkedIn
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Technology Explained


Blackwell: Blackwell is an AI computing architecture designed to supercharge tasks like training large language models. These powerful GPUs boast features like a next-gen Transformer Engine and support for lower-precision calculations, enabling them to handle complex AI workloads significantly faster and more efficiently than before. While aimed at data centers, the innovations within Blackwell are expected to influence consumer graphics cards as well

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DLSS: DLSS (Deep Learning Super Sampling) is an advanced AI-powered technology developed by NVIDIA that enhances real-time graphics rendering in video games and applications. DLSS utilizes deep learning algorithms to upscale lower-resolution images in real-time, resulting in higher-quality visuals while maintaining optimal performance. By harnessing the power of AI and deep neural networks, DLSS effectively boosts frame rates and image quality, enabling gamers to experience smoother gameplay and more immersive graphics without sacrificing computational efficiency. This technology has gained widespread recognition for its ability to deliver impressive visual fidelity and improved performance simultaneously, revolutionizing the way modern computer graphics are processed and displayed.

DLSS website
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GDDR7: GDDR7 (Graphics Double Data Rate 7) is the seventh generation of graphics double data rate (GDDR) memory. It is a type of dynamic random-access memory (DRAM) that is specifically designed for use in graphics cards. GDDR7 memory offers a number of advantages over previous generations of GDDR memory. GDDR7 is a significant improvement over previous generations of GDDR memory. It offers faster speeds up to 32 gigabits per second (Gbps) per pin, lower power consumption, and improved error correction. This makes it ideal for use in high-performance graphics cards and other applications that require high bandwidth and low latency.

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Geforce: Geforce is a line of graphics processing units (GPUs) developed by Nvidia. It is the most popular GPU used in the computer industry today. Geforce GPUs are used in gaming PCs, workstations, and high-end laptops. They are also used in virtual reality systems, artificial intelligence, and deep learning applications. Geforce GPUs are designed to deliver high performance and power efficiency, making them ideal for gaming and other demanding applications. They are also capable of rendering high-resolution graphics and providing smooth, realistic visuals. Geforce GPUs are used in a variety of applications, from gaming to professional workstations, and are the preferred choice for many computer users.

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GPU: GPU stands for Graphics Processing Unit and is a specialized type of processor designed to handle graphics-intensive tasks. It is used in the computer industry to render images, videos, and 3D graphics. GPUs are used in gaming consoles, PCs, and mobile devices to provide a smooth and immersive gaming experience. They are also used in the medical field to create 3D models of organs and tissues, and in the automotive industry to create virtual prototypes of cars. GPUs are also used in the field of artificial intelligence to process large amounts of data and create complex models. GPUs are becoming increasingly important in the computer industry as they are able to process large amounts of data quickly and efficiently.

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Tensor Cores: Tensor Cores are a type of specialized hardware designed to accelerate deep learning and AI applications. They are used in the computer industry to speed up the training of deep learning models and to enable faster inference. Tensor Cores are capable of performing matrix operations at a much faster rate than traditional CPUs, allowing for faster training and inference of deep learning models. This technology is used in a variety of applications, including image recognition, natural language processing, and autonomous driving. Tensor Cores are also used in the gaming industry to improve the performance of games and to enable more realistic graphics.

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VRAM: VRAM (Video Random Access Memory) is a type of computer memory used in graphics cards to store image data. It is a high-speed memory that is used to store the image data that is sent to the monitor. It is used in the computer industry to improve the performance of graphics cards and to provide faster access to the image data. VRAM is also used in gaming consoles to provide a more immersive gaming experience. It is also used in virtual reality applications to provide a more realistic experience. VRAM is an important component of the computer industry and is used in many applications.

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