Cerebrium

RunPod is a cloud platform for AI and machine learning workloads that rents GPU compute by the second. It offers Pods for persistent GPU instances, Serverless endpoints that autoscale inference from zero, and multi-node Clusters, plus a Hub of ready-to-deploy open-source models and templates.

Hạ tầng đám mây serverless cho khối lượng công việc AI và dữ liệu

Nebius is an AI-focused cloud platform that gives teams non-virtualized NVIDIA GPU clusters, managed MLOps tooling, and a serverless inference layer so they can move from experiment to production on one stack.

Đám mây AI do đội ngũ tạo ra PyTorch Lightning xây dựng

Together AI is the AI Native Cloud — a full-stack platform for running, fine-tuning and training open-source models. It spans serverless inference APIs, dedicated endpoints, GPU clusters, post-training and storage, all backed by in-house systems research.

GPU cloud giá rẻ với instance tính theo phút và sandbox tính theo giây cho khối lượng công việc AI.

Đám mây GPU phân tán điều phối các GPU tiêu dùng nhàn rỗi trên toàn cầu

Thuê GPU đám mây theo từng giây từ chợ toàn cầu

API suy luận serverless chi phí thấp cho hơn 200 mô hình

FluidStack builds and operates large-scale compute infrastructure for AI, including gigawatt-class data centers and GPU clusters used for training and inference. The company designs its own power, cooling and data center systems, onshores manufacturing and deploys solar generation to supply the power its clusters need. Rather than a self-serve cloud console, FluidStack works with AI labs and enterprises to provision large reserved clusters, with orchestration tooling for the ML frameworks and schedulers those teams already use.

Một cloud cho hơn 200 API mô hình, agent sandbox và sức mạnh GPU

General Compute is an inference cloud built around alternative AI silicon rather than standard GPU fleets. The company buys racks of accelerators, racks them in colocation data centres, and handles the cooling, power, and networking itself. On top of that hardware it runs a disaggregated inference stack that splits each request: prompt processing runs on NVIDIA GPUs for prefill, while token generation runs on faster decode chips such as Cerebras, SambaNova, Positron AI, and d-Matrix. Customers get bare metal access or a tokens-per-second SLA.