If GROQ technology would made it into the RTX 6000 Rubin Gpus.
My thinking was that DLSS 5 would require a different kind of chip and that this would change how graphics would be handled.
Yes i know that it will work with an rtx 5K gpu too but maybe different.
The impact if Groq is just too big to ignore.
Made with help of Gemini:
Groq (LPU) + Image Generation: The Turbo for Stable Diffusion & Mamba
While classic GPUs (Tensor Cores) act like “muscles” lifting heavy pixel loads, Groq’s LPU technology functions as the “nervous system” that dictates direction and speed.
1. For Mamba (State Space Models / Zigzag-Scan)
Mamba is the successor to Transformer models for imagery. Instead of processing the entire image at once (which consumes massive amounts of VRAM), Mamba “scans” the image in a continuous zigzag pattern.
The LPU Advantage: Since the LPU is a Stream Accelerator, it can handle this sequential scanning process without memory-induced latency.
Determinism: The LPU calculates the next pixel state at the exact moment the previous one is finished. This makes Mamba-based image generation on an LPU up to 10x faster than on a conventional GPU.
Result: 60 FPS real-time AI video or gaming graphics that are entirely “generated” rather than traditionally rendered.
2. For Stable Diffusion (Text-to-Image)
In this scenario, the LPU and Tensor Cores work as a hybrid team:
Text Conditioning (LPU): When you enter a prompt, the AI must understand what “a red car in the rain” means. The LPU processes this language stream instantly and sends the control commands to the graphics cores.
Sampling Loops (LPU): Stable Diffusion often requires 20–50 iterations (steps) to refine an image. The LPU handles the management of these loops, ensuring that data doesn’t “park” in slow VRAM between steps but stays within the LPU’s 150 TB/s SRAM.
Result: The “thinking second” before the image appears (TTFT – Time To First Token/Image) almost entirely disappears.
3. Why the combination in Rubin (RTX 60) is so powerful
With the LPX technology (Groq), NVIDIA is building a high-speed highway for data streams:
Tensor Cores (GPU): Paint the pixels (raw brute force).
LPU (Groq): Controls the scan path (Mamba) and the logic (Stable Diffusion).
The era of the “universal GPU” comes to an end with Blackwell. With Vera Rubin, the era of specialized accelerators begins, in which Groq technology (LPX) is considered the key factor for real-time interaction (decoding).
Groq is about 10 times more energy-efficient than an NVIDIA GPU when performing the same task.
