Packet.ai
Packet.ai is a GPU cloud platform built to give developers and AI teams fast access to high-performance computing without the complexity and inefficiencies of traditional cloud infrastructure. It provides on-demand GPU instances, including modern NVIDIA hardware, that can be launched in seconds and accessed through tools like SSH, Jupyter, or VS Code, enabling users to quickly start training models, running inference, or experimenting with AI workloads. It introduces a different approach to GPU usage by dynamically allocating resources based on real-time workload demands, rather than treating a GPU as a fixed unit, allowing multiple compatible workloads to share hardware efficiently while maintaining predictable performance. This results in higher utilization and eliminates the need to pay for idle capacity, focusing instead on the exact compute resources consumed. Packet.ai also offers an OpenAI-compatible API for language model inference, embeddings, and fine-tuning, etc.
Learn more
NVIDIA Confidential Computing
NVIDIA Confidential Computing secures data in use, protecting AI models and workloads as they execute, by leveraging hardware-based trusted execution environments built into NVIDIA Hopper and Blackwell architectures and supported platforms. It enables enterprises to deploy AI training and inference, whether on-premises, in the cloud, or at the edge, with no changes to model code, while ensuring the confidentiality and integrity of both data and models. Key features include zero-trust isolation of workloads from the host OS or hypervisor, device attestation to verify that only legitimate NVIDIA hardware is running the code, and full compatibility with shared or remote infrastructure for ISVs, enterprises, and multi-tenant environments. By safeguarding proprietary AI models, inputs, weights, and inference activities, NVIDIA Confidential Computing enables high-performance AI without compromising security or performance.
Learn more
Google Cloud GPUs
Speed up compute jobs like machine learning and HPC. A wide selection of GPUs to match a range of performance and price points. Flexible pricing and machine customizations to optimize your workload. High-performance GPUs on Google Cloud for machine learning, scientific computing, and 3D visualization. NVIDIA K80, P100, P4, T4, V100, and A100 GPUs provide a range of compute options to cover your workload for each cost and performance need. Optimally balance the processor, memory, high-performance disk, and up to 8 GPUs per instance for your individual workload. All with the per-second billing, so you only pay only for what you need while you are using it. Run GPU workloads on Google Cloud Platform where you have access to industry-leading storage, networking, and data analytics technologies. Compute Engine provides GPUs that you can add to your virtual machine instances. Learn what you can do with GPUs and what types of GPU hardware are available.
Learn more
Fluidstack
Fluidstack is an AI infrastructure platform designed to provide high-performance compute resources for advanced workloads. It offers dedicated GPU clusters that are fully isolated and optimized for large-scale AI training and inference. The platform includes Atlas OS, a bare-metal operating system built to enable fast provisioning and efficient orchestration of AI infrastructure. Fluidstack also provides Lighthouse, a monitoring and optimization tool that ensures reliability and performance across workloads. Its infrastructure is designed for speed, scalability, and secure operations, with single-tenant environments by default. The platform supports enterprises, AI labs, and governments that require high-performance computing capabilities. Fluidstack emphasizes rapid deployment, enabling teams to access GPU resources quickly when needed. Overall, it delivers a powerful and secure solution for running AI workloads at scale.
Learn more