Bare Metal Gpu Servers

Massed Compute delivers on‑demand GPU/CPU resources via API and desktop interface, supporting NVIDIA A100/H100/L40/A6000 GPUs and custom clusters. Bare‑metal servers provide direct physical access, while an Inventory API streamlines instance management in a Tier III data‑center with expert support.

Trooper.AI provides private EU-hosted bare-metal GPU servers for model training, fine-tuning, and inference, with one-click AI environment templates, full root SSH and NVMe storage, tested CUDA on Ubuntu 22.04, scalable hardware and pause/upgrade controls.

Fluidstack offers dedicated GPU clusters on bare‑metal Atlas OS, delivering rapid provisioning and full resource control. Continuous monitoring via Lighthouse ensures isolated, compliant infrastructure (GDPR, SOC 2, ISO 27001) with a 15‑minute support SLA for AI labs, enterprises, and government use

Vast.ai supplies on‑demand GPU instances, including NVIDIA RTX, H100, and Blackwell models, deployable in seconds. Developers can programmatically provision resources via CLI, SDK or API, and scale workloads with autoscaling, serverless inference, and dedicated InfiniBand clusters.

Cloud GPU rental platform offering on-demand VMs and bare-metal servers with A100/H100/RTX4090 and other GPUs, configurable vRAM/vCPU, persistent volumes, spot instances, and API-driven provisioning for training, inference, rendering, and HPC workloads.

GPU Mart provides dedicated GPU server hosting and VPS solutions optimized for demanding AI workloads, including LLM inference, image generation, and 3D rendering, offering guaranteed resources and transparent pricing.

Runpod supplies on‑demand GPUs in 31 regions, offering single‑node pods, multi‑node clusters, and serverless workloads. It delivers low‑latency inference, efficient fine‑tuning, instant scaling, S3‑compatible storage, real‑time logs, and sub‑200 ms cold starts.

Tensordock provides cloud GPU services for AI workloads, featuring on-demand Nvidia H100, A100, and RTX 4090 GPUs. It supports rapid deployment, extensive documentation, and efficient management of virtual environments for diverse applications.

GPUX is a serverless inference platform that delivers 1‑second cold starts and GPU‑accelerated execution for models like Stable Diffusion XL, ESRGAN, and Whisper. It supports P2P and read‑write volume access for rapid, scalable deployment on NVIDIA RTX 4090 GPUs.

Thunder Compute is a cloud-based platform that provides easy access to network-attached GPUs for AI and machine learning projects. It enables swift model deployment, efficient scaling, and minimizes idle GPU costs through streamlined infrastructure management.

Juice virtualizes local GPUs over IP, intercepting CUDA, Vulkan, DirectX 12 calls so Python, Blender, Unreal Engine run on remote GPUs with minimal changes. It supports all NVIDIA cards, SLURM integration, and TLS 1.3 secure tunnels.

fal.ai offers a unified API for generating images, videos, audio, and 3D models from a library of over 1,000 production‑ready assets. It provides serverless GPU inference, private deployment options, NVIDIA‑cluster fine‑tuning, SOC 2 compliance, and enterprise‑grade support.

Vocareum delivers labs with IDEs, notebooks, and GPU/CPU clusters in isolated containers or accounts. It offers tutoring, code grading, and a unified gateway to AWS, Azure, GCP, Databricks, and foundation models. LMS integration and SOC 2 compliance enable scalable training.

Float16.cloud delivers AI‑as‑a‑Service, platform, and infrastructure through instant, ready‑to‑use models accessed via a dashboard or API. It offers dedicated GPUs, 1‑second cold starts, Jupyter notebooks, credit‑based quotas, and dynamic scheduling for training, inference, and batch processing.

ClearML AI Infrastructure Platform unifies GPU management, model development, and generative‑AI deployment across on‑prem, cloud, and hybrid setups, offering secure multi‑tenant provisioning, priority scheduling, fractional GPU allocation, integrated IDE, CI/CD, and streamlined workflows for data sc

Scale your AI projects affordably with Salad's GPU Cloud service. Access over 10,000 GPUs for generative AI tasks like generating 9 million+ images in just 24 hours at a starting price of $0.02/hr. Salad offers fully managed services like the Salad Container Engine, Salad Gateway Service, and Virtua

BrainHost VPS offers a KVM-based virtual private server hosting solution with NVMe storage and a user-friendly Virtfusion panel. It supports low-latency access, scaling options, automated backups, and one-click OS reinstalls, catering to various hosting needs.

Cirrascale offers a private AI cloud that supports training and inference on AMD, Cerebras, NVIDIA, and Qualcomm accelerators. It provides zero DevOps, no data‑transfer fees, high‑bandwidth networking, and configurable multi‑GPU servers, streamlining workflows and accelerating deployment.

Denvr is a sovereign AI cloud and private platform on Canadian/US infrastructure, providing on-demand and reserved GPU compute (NVIDIA H200/H100/A100, Intel Gaudi2), scalable InfiniBand clusters, OpenAI-compatible inference endpoints, NVMe storage, secure networking, and developer APIs.

AI Horde is a community‑powered platform that harnesses volunteer CPU/GPU resources to generate images, text, and utilities via an open REST API. Users can access it through web apps, earn kudos for queue priority, and view real‑time throughput stats.

Compact edge platform featuring the Hailo‑8 accelerator for up to 83 TOPs. Supports USB, PCIe, Ethernet, and GPIO; runs Linux ≥ 6.18 with drivers, enabling rapid AI deployment for real‑time inference in automotive, security, and industrial inspection.

Dedalus Labs offers persistent full Linux VMs with VM-level kernel, memory and filesystem isolation, fast boot under 250 ms, preserved state across sessions, and CLI/API/SSH access for reproducible development, long-running agents, CI, and model workloads.

UbiOps offers a unified interface to deploy AI models on local, hybrid, or multi‑cloud environments. It provides version control, API management, resource prioritization, automated scaling, GPU provisioning, and Kubernetes orchestration, aiding cost, security, and compliance for production workloads

NVIDIA AI Workbench unifies building, training, and deploying AI models on NVIDIA GPUs. It integrates Jupyter, preconfigured libraries, Docker, automatic GPU allocation, multi‑node scaling, and real‑time monitoring, supporting TensorFlow, PyTorch, and Hugging Face.

Ministral WebGPU optimizes machine learning applications by utilizing enhanced graphics processing power. It supports various app files, enabling efficient collaboration and development, with an intuitive interface suitable for both beginners and experienced practitioners.

Render simplifies deployment and scaling of web apps, APIs, background workers, and static sites. It supports Docker, build‑packs, native runtimes, GitHub CI/CD, automatic scaling, zero‑downtime updates, SSL, custom domains, environment variables, and CDN‑backed database add‑ons.

General Compute is an OpenAI-compatible inference API using custom ASIC accelerators to deliver high throughput (e.g., 950 tokens/sec) and dramatically lower power consumption (≈17 kW vs. 120 kW per rack), enabling developers to switch providers by simply changing the base URL and API key. It suppor

Inferless is a serverless platform for deploying machine learning models seamlessly. It offers automatic load balancing, custom runtime environments, and automated CI/CD workflows, minimizing infrastructure management while scaling efficiently from single to millions of requests.

VibeClaw.dev is a browser-based OpenClaw runtime for running AI coding agents in sandboxed, in-browser Node.js containers. It features a complete virtual filesystem, multi-agent orchestration, and flexible model support from local WebGPU LLMs to cloud APIs, all exportable for private, reproducible w

TAHO is an AI/HPC infrastructure layer that accelerates model serving, training and batch workloads, cutting inference latency and cold starts, improving GPU utilization and parallelism via PeerMesh to boost throughput and reduce compute costs across cloud and on‑prem.