Fractional Gpu Allocation

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

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

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.

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.

IX RWA lets investors buy fractional ownership in real-world AI infrastructure, data centers, real estate, and renewable energy, providing proportional income from AI workloads and energy production with blockchain-secured records and low minimums.

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.

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.

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

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.

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.

Fracternal links fractional executives to companies using AI‑generated profiles and leadership assessments. Executives gain tailored visibility, flexibility, income diversification, and skill growth. Employers access niche expertise, scale staff flexibly, reduce hiring risk, and stay competitive.

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.

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.

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