Nvidia’s latest AI tool doesn’t live in the cloud—it’s installed right on your gaming PC. G-Assist is a new AI assistant tailored for PC gamers that runs locally on RTX 30-, 40-, or 50-series GPUs with at least 12GB of VRAM. It offers real-time insights and commands based on what’s happening in your game—no internet connection needed.
Instead of sending your screen data off to a remote server, G-Assist uses a local small language model built on a Llama-based Instruct architecture with 8 billion parameters. The model runs using TensorRT-LLM and Nvidia’s Tensor Cores.
It processes what’s visible on-screen through video capture and optical character recognition (OCR), responds to voice or text commands, and delivers performance diagnostics, hardware tuning suggestions, and gameplay information—all within the Nvidia App.
The assistant requires roughly 10GB of disk space and is compatible with a wide range of RTX hardware. Users can activate it with the Alt+G shortcut and interact via voice or typed prompts. Project G-Assist uses a third party Small Language Model designed to run locally and it is not intended to be a broad conversational AI.
From FPS Drops to Fan Curves
G-Assist’s capabilities are focused and practical. It can explain performance issues, such as frame rate dips, and suggest changes like enabling DLSS or switching graphics presets. It also visualizes expected performance improvements using charts, making the impact of settings adjustments easier to understand.
Beyond in-game help, the assistant reaches into system-level controls. It can launch benchmarks, tweak fan curves, adjust audio output, and control lighting on compatible peripherals from brands like Logitech, Corsair, MSI, and Nanoleaf. Users can even ask it to underclock the GPU to conserve power during lower-demand scenarios.
It’s also capable of answering questions about your PC’s hardware and Nvidia software stack, providing explanations or shortcuts to deeper diagnostics. These functions are accessible via the Nvidia App, where G-Assist integrates alongside new DLSS override tools, display scaling, and color calibration settings.
AI Tools That Stay on Your Rig
G-Assist’s local-only approach fits into Nvidia’s broader vision of AI-enhanced gaming that doesn’t rely on cloud infrastructure. The assistant benefits from recent additions to the RTX platform, such as DLSS 4’s Multi-Frame Generation—which produces multiple AI-generated frames for every rendered one, boosting smoothness in supported games—and DLSS Override, which allows players to manually apply DLSS updates in older titles.
Visual enhancements are supported by RTX Neural Shading, which integrates neural networks into DirectX shaders for improved lighting and texture rendering without ballooning VRAM usage. Nvidia notes, “By embedding small neural networks into shaders, developers can achieve more realistic visuals and optimize rendering efficiency in real-time.”
These enhancements are supported by the RTX 50-series GPUs introduced at CES 2025. Powered by the Blackwell architecture, the cards use GDDR7 memory and redesigned Tensor Cores that accelerate real-time AI features. But the performance comes at a cost—the RTX 5090 requires a 1,000-watt power supply, a detail that might give pause to anyone with space or power limitations.
Building on Familiar AI Ground
G-Assist isn’t Nvidia’s first foray into local AI assistants. Back in January, the company joined forces with Streamlabs and Inworld to unveil the Intelligent Streaming Assistant, a desktop AI tool that helps streamers manage scenes, handle chat interaction, and automate production workflows. It runs entirely on RTX hardware and uses Nvidia’s Avatar Cloud Engine (ACE) for low-latency avatar rendering and voice-driven reactions.
Streamlabs positioned the tool as a way to simplify creator workflows. The assistant was designed to step in as a technical director, co-host, and producer all at once.
Smart Companions Already in the Field
G-Assist builds on Nvidia’s recent efforts to embed local AI in gameplay itself. At CES 2025, the company showcased its ACE-powered NPCs, starting with “PUBG Ally,” an AI teammate in PUBG: Battlegrounds developed with Krafton.
The companion uses in-game context to coordinate flanks, share loot, and provide real-time tactical input.
Wemade Next’s MMORPG MIR5 takes the concept in another direction with Asterion, an AI-powered boss character that learns from previous encounters to evolve its strategy.
These implementations—like G-Assist—rely on Nvidia’s philosophy of edge AI, where the intelligence runs locally to reduce latency, improve responsiveness, and keep user data private.
A Different Path from Microsoft’s Xbox Copilot
G-Assist’s release comes just weeks after Microsoft announced Xbox Copilot, a cloud-based AI gaming assistant aimed at helping players improve, explore game features, and manage installations.
Set to launch via the Xbox mobile app in April, Copilot leans heavily on Microsoft’s cloud infrastructure and is designed for Xbox and mobile ecosystems—not the desktop PC.
In contrast, Nvidia’s approach is entirely local. No data leaves the device, and players maintain full control over what the assistant can access or do. That makes it more appealing to privacy-conscious users or those with limited internet connectivity. It also ensures low-latency responsiveness during gameplay, which cloud-dependent tools may not be able to match in real time.
Expanding Through Community and Customization
Nvidia has also opened G-Assist to community development. The assistant supports plugin creation through an official GitHub repository, allowing developers and enthusiasts to extend its capabilities beyond what’s shipped by default. This positions it as not just a product, but a platform that can grow with user feedback and developer creativity.
G-Assist supports both voice and text input, letting users interact however they prefer. It recognizes in-game and system-level context and can respond with overlays, charts, or system commands depending on the query. This flexibility ensures that it functions not just as a performance monitor or tutorial engine, but as an integrated part of the player’s desktop environment.
From April Fools’ Joke to Downloadable Reality
While G-Assist is now available as a real, functioning assistant, the idea originally began as a tongue-in-cheek gag. In 2017, Nvidia released a fake promo video for an “AI assistant” that would play your games for you—an April Fools’ joke at the time. That satirical concept has now become a downloadable utility that’s deeply integrated with the company’s RTX platform and GPU strategy.
And for players juggling high-end graphics settings, complex RPG systems, and an ever-growing list of peripherals, an AI assistant that lives on your PC—rather than in the cloud—might be just what they didn’t know they needed.
