Local AI: 775 tok/s, DiffusionGemma (BF16) on Nvidia RTX 6000 Pro (twitter.com)

A significant advancement in local AI performance was announced with the successful deployment of the DiffusionGemma model (full BF16) on an Nvidia RTX 6000 Pro, achieving an impressive speed of 775 tokens per second. This high throughput was made possible using vLLM, a fork developed by Red Hat, showcasing the model’s potential for rapid processing in short context scenarios. However, the performance does face limitations, as the time to first token (TTFT) dramatically increases to 22 seconds when scaling to 100,000 tokens. This development is crucial for the AI/ML community as it highlights advancements in local AI model efficiency, making it more feasible to implement powerful AI capabilities in real-time applications. The ability to rapidly process tokens offers potential applications in various sectors, from natural language processing to interactive AI systems. While the model excels at short contexts, understanding its limitations at larger scales is essential for developers aiming to leverage these AI technologies effectively.