Solutions
Every workload has different memory, bandwidth and compute requirements. Explore the GPUs we recommend for your use case.
LLM and foundation model training
Training from scratch or continued pre-training demands high memory capacity and fast GPU-to-GPU interconnect. Shorten training times with NVLink-connected 8-GPU HGX servers and multi-node clusters.
- NVLink-connected 8-GPU HGX servers
- Multi-node distributed training (FSDP, DeepSpeed, Megatron-LM)
- Uninterrupted, dedicated resources for long training runs
Fine-tuning and model customization
Customize open-source models such as Llama, Qwen and Mistral with your enterprise data. Use a single GPU with LoRA and QLoRA, or multiple GPUs for full fine-tuning.
- Cost-efficient customization with LoRA / QLoRA
- Full fine-tuning, RLHF and DPO
- Your data stays on hardware reserved for you
Inference and model serving
Strike the right balance of memory and bandwidth for low latency and high throughput in production. Infrastructure compatible with serving stacks such as vLLM, TensorRT-LLM and SGLang.
- Low latency with high-bandwidth memory
- Cost-efficient serving with FP8 / FP4
- Horizontally scaled inference clusters
Image and video generation
Scale your generative content pipelines with Stable Diffusion, Flux and video generation models, and train brand and style models with LoRA.
- High-resolution image generation
- Video generation and editing models
- Brand and style training with LoRA
3D rendering and VFX
Cut delivery times with GPU render engines such as Blender, Octane, Redshift and V-Ray. Handle peak periods with monthly, project-based rentals.
- Fast ray tracing with RT Core GPUs
- Multi-GPU servers for render queues
- Monthly, project-based rentals
Scientific computing and HPC
GPU-accelerated compute for molecular dynamics, climate modeling, genomics and financial simulations.
- Data center GPUs with high FP64 performance
- CUDA-accelerated scientific software
- High memory capacity for large datasets
Let's plan the right GPU infrastructure for your project
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