RTX 4080 Super vs 5070: AI VRAM and Tensor Cores

Описание: The article https://www.bestgpusforai.com/gpu-comparis... offers a comprehensive technical evaluation comparing the NVIDIA *GeForce RTX 5070 (Blackwell)* and the *RTX 4080 Super (Ada Lovelace)**, focusing specifically on their application in various Artificial Intelligence workloads such as large language models and generative AI. The older **RTX 4080 Super* is shown to be more capable for current high-precision pipelines due to its higher *raw throughput**, superior memory bandwidth, and larger **16 GB of VRAM**. In contrast, the RTX 5070, built on the newer Blackwell architecture, introduces key specialized features like 5th-generation Tensor Cores with native **FP4 and FP6 quantization* support, and a dramatically increased L2 cache size. This focus on *architectural efficiency* allows the 5070 to run very large models within its smaller 12 GB memory limit by significantly reducing model size, provided the software stack is optimized for these new formats. Therefore, the choice between the GPUs centers on whether a user needs the proven flexibility of the 4080 Super or the forward-looking, highly efficient capabilities of the 5070.