Our models are trained with a single A100 (80GB) GPU. They can also be trained on multiple GPUs with smaller RAM by setting a smaller data_loader.train.batch_size per GPU. Training on multiple nodes ( ...
The config file examples/mistral-4-node-benchmark.yaml is pre-configured for a multi-node setup with 4 DGX nodes, each with 8 A100-80GB or H100-80GB GPUs. Note Fast-LLM scales from a single GPU to ...
Up until now, it required around 8 Nvidia A100/H100 Superchips, each one costing around $30K ... and the H100 Superchip starts at 80GB of VRAM. Companies are rushing to deploy AI agents, and Nvidia ...
TL;DR: NVIDIA is developing a new RTX Blackwell workstation GPU with 96GB of GDDR7 memory on a 512-bit bus, using 3GB modules. It is expected to be part of the RTX 8000 series, featuring the GB202 ...
The explosive growth of ChatGPT has triggered unprecedented demand for artificial intelligence (AI) computing power, leading ...
TL;DR: NVIDIA's rumored GeForce RTX 5090 Ti features a GB200-200 GPU with 24,576 CUDA cores, 32GB of GDDR7 memory, and an 800W TDP. It boasts a base clock of 2100MHz and a boost clock of 2514MHz.
Meanwhile, AMD may take more time to ramp up its GPU availability, giving Nvidia the chance to dominate the GPU market in early 2025. With CES 2025 mere days away, we already know that January is ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback