Source: GPU Memory Essentials for AI Performance | NVIDIA Technical Blog
The NVIDIA blog highlights the critical role of GPU memory capacity in running advanced artificial intelligence (AI) models. Large AI models, such as Llama 2 with 7 billion parameters, require significant amounts of memory. For instance, processing at FP16 precision demands at least 28 GB of memory.
NVIDIA offers high-performance RTX GPUs, such as the RTX 6000 Ada Generation, featuring up to 48 GB of VRAM. These GPUs are designed to handle the largest AI models, enabling local development and execution of complex tasks. Additionally, they come equipped with specialized hardware, including Tensor Cores, which significantly accelerate computations required for AI workloads.
With NVIDIA’s powerful solutions, businesses and researchers can optimize the development and deployment of AI models directly on local devices, opening up new possibilities for advancements in artificial intelligence.
For more details, visit the official NVIDIA blog: developer.nvidia.com.
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