Question: I'm looking for a cloud provider that offers high-performance AI services with modern GPU-based infrastructure for multi-node training.

If you're looking for a cloud provider with high-performance AI services and modern GPU-based infrastructure for multi-node training, RunPod is worth a look. RunPod is a globally distributed GPU cloud that supports a range of GPU workloads and lets you instantly provision GPU pods. It also offers serverless ML inference, autoscaling, and job queuing for large-scale AI model development and training. With multiple pricing tiers and support for more than 50 preconfigured templates, RunPod offers flexibility and cost control.

Another good option is Anyscale. It's based on the open-source Ray framework and supports a broad range of AI models, including LLMs and custom generative AI models. Anyscale offers workload scheduling, heterogeneous node control, and GPU and CPU fractioning for efficient use of resources. It also offers native integrations with popular IDEs and a free tier with flexible pricing, so it's a good option for large-scale AI workloads.

If you're on a budget, Salad is worth a look. Salad is a cloud-based platform for running and managing AI/ML production models at scale. It has thousands of consumer GPUs around the world and offers features like on-demand elasticity, a global edge network, and multi-cloud support. Salad's pricing starts at $0.02 per hour for GTX 1650 GPUs, and it offers discounts for large-scale deployments, so it's a very cheap option for GPU-hungry workloads.

Last, if you're looking for a serverless GPU infrastructure, check out Cerebrium. It charges pay-per-use pricing and offers features like GPU variety, infrastructure as code, and real-time logging and monitoring. It's designed to scale automatically and offers tiered plans for different needs. That makes it a good option for engineers who want a flexible and cheap option for training and deploying machine learning models.