NVIDIA Enters Full Production of "Vera Rubin" Platform: Integrating Groq 3 LPU for Unprecedented AI SpeedNVIDIA has officially announced that its next-generation Vera Rubin platform has entered full-scale production and is ready for customer delivery. This comprehensive AI infrastructure suite represents a massive leap in unified computing, featuring the Vera CPU, Rubin GPU, NVLink 6, ConnectX-8, BlueField-4 DPU, Spectrum-6 Ethernet, and the highly anticipated NVIDIA Groq 3 LPU.
The Groq 3 Breakthrough: Tackling the Transformer Bottleneck
The standout star of this platform is the Groq 3 (LP30 chip). Following NVIDIA’s strategic acquisition of Groq’s founding talent in late 2025, the company has successfully integrated LPU (Language Processing Unit) technology into its ecosystem.
The LP30 chip utilizes on-chip memory and a sophisticated software compiler to pre-program operations, enabling lightning-fast Decoding in Transformer architectures. To overcome the LP30’s limited 500MB on-chip memory, NVIDIA has engineered a powerhouse configuration: a single Rubin GPU paired with 55 Groq 3 LPU units via a high-speed C2C (Chip-to-Chip) link, creating a unified 4GB memory pool optimized for ultra-low latency inference.
The Roadmap: Moving Toward NVFP4 and Feynman
During the announcement, Jensen Huang addressed the current limitation of the LP30, which supports only FP8 data formats. He unveiled the upcoming LP35 chip, which will introduce support for the high-efficiency NVFP4 format under the Vera Rubin umbrella. Looking further ahead, NVIDIA teased the 2028 "Feynman" platform, which will upgrade to the LP40 chip, featuring native NVLink support for seamless multi-chip connectivity.
The inclusion of Groq is a direct declaration of war in the inference market. While GPUs have excelled at training, Groq excels at response speed. Pairing Rubin and Groq 3 will enable seamless real-time AI interaction, a key strength for future AI agents.
The push for NVFP4 (4-bit Floating Point) reinforces NVIDIA's ambition to set new industry standards. This data format allows large-scale models (LLMs) to run faster with less power and less memory usage, areas where competitors currently lag behind.
The memory wall is the biggest bottleneck in current AI solutions. Connecting numerous LPUs to a GPU via a C2C link demonstrates NVIDIA's shift from selling individual chips to a "system-on-a-rack," where a whole computer functions like a single chip.
The announcement of the Feynman Platform plan reassures shareholders and customers that NVIDIA has a clear roadmap to dominate the AI market for at least another 3-5 years, focusing on integration and increasingly faster inter-chip communication.
Apple Acquires MotionVFX Boosting Final Cut Pro with Professional Visual Effects.
Source: NVIDIA
NVIDIA Enters Full Production of "Vera Rubin" Platform: Integrating Groq 3 LPU for Unprecedented AI SpeedNVIDIA has officially announced that its next-generation Vera Rubin platform has entered full-scale production and is ready for customer delivery. This comprehensive AI infrastructure suite represents a massive leap in unified computing, featuring the Vera CPU, Rubin GPU, NVLink 6, ConnectX-8, BlueField-4 DPU, Spectrum-6 Ethernet, and the highly anticipated NVIDIA Groq 3 LPU.
The Groq 3 Breakthrough: Tackling the Transformer Bottleneck
The standout star of this platform is the Groq 3 (LP30 chip). Following NVIDIA’s strategic acquisition of Groq’s founding talent in late 2025, the company has successfully integrated LPU (Language Processing Unit) technology into its ecosystem.
The LP30 chip utilizes on-chip memory and a sophisticated software compiler to pre-program operations, enabling lightning-fast Decoding in Transformer architectures. To overcome the LP30’s limited 500MB on-chip memory, NVIDIA has engineered a powerhouse configuration: a single Rubin GPU paired with 55 Groq 3 LPU units via a high-speed C2C (Chip-to-Chip) link, creating a unified 4GB memory pool optimized for ultra-low latency inference.
The Roadmap: Moving Toward NVFP4 and Feynman
During the announcement, Jensen Huang addressed the current limitation of the LP30, which supports only FP8 data formats. He unveiled the upcoming LP35 chip, which will introduce support for the high-efficiency NVFP4 format under the Vera Rubin umbrella. Looking further ahead, NVIDIA teased the 2028 "Feynman" platform, which will upgrade to the LP40 chip, featuring native NVLink support for seamless multi-chip connectivity.
The inclusion of Groq is a direct declaration of war in the inference market. While GPUs have excelled at training, Groq excels at response speed. Pairing Rubin and Groq 3 will enable seamless real-time AI interaction, a key strength for future AI agents.
The push for NVFP4 (4-bit Floating Point) reinforces NVIDIA's ambition to set new industry standards. This data format allows large-scale models (LLMs) to run faster with less power and less memory usage, areas where competitors currently lag behind.
The memory wall is the biggest bottleneck in current AI solutions. Connecting numerous LPUs to a GPU via a C2C link demonstrates NVIDIA's shift from selling individual chips to a "system-on-a-rack," where a whole computer functions like a single chip.
The announcement of the Feynman Platform plan reassures shareholders and customers that NVIDIA has a clear roadmap to dominate the AI market for at least another 3-5 years, focusing on integration and increasingly faster inter-chip communication.
Apple Acquires MotionVFX Boosting Final Cut Pro with Professional Visual Effects.
Source: NVIDIA
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