Virtual-machine management
Choose instance capacity and region, configure SSH access, and manage virtual servers through the dashboard.
Huddle01 Cloud
Paid
Manage cloud workloads and access multiple AI models through one platform.
¿Qué es Huddle01 Cloud?
Huddle01 Cloud is a developer platform for deploying virtual machines, container workloads, Kubernetes clusters, and GPU jobs. Its console provides workspaces for managing resources, usage, and billing; APIs support programmatic infrastructure access.
The platform also provides AI Inference, an OpenAI-compatible service that routes requests to supported model providers. Developers can change the model identifier within the same integration and receive generated output and usage metadata. This is a distinct service from renting a GPU to run your own workload.
¿Qué puede hacer Huddle01 Cloud?
Managed containers and Kubernetes
Deploy Docker images with configuration or create Kubernetes clusters with selected master and worker nodes and automatic worker scaling.
GPU deployment
Select available GPU offers, images, storage, and region through the console or API, then connect through SSH. Preconfigured CUDA images support training workloads.
Unified model inference
Use one Huddle01 API key and OpenAI-compatible endpoint for supported models from providers including OpenAI, Anthropic, Google, and DeepSeek.
Networking and workload visibility
Use private networking, firewall rules, load balancing, resource metrics, and usage dashboards to operate deployed services.
Casos de uso
“Host application backends”
Deploy virtual servers near users and add container orchestration or load balancing as the application grows.
“Develop model-powered applications”
Build chat, summarization, or coding workflows and compare supported models through the same inference integration.
“Run GPU experiments”
Rent available GPU capacity for training or computation with usage-based billing and a defined minimum charge.
Preguntas frecuentes
What does a basic VM cost?
Anton-2, with 2 vCPUs and 4 GB RAM, is listed at US$0.031 per hour. Block storage is charged separately at US$0.0000834 per GB per hour. Kubernetes master and worker nodes use VM rates; the master node is billable despite no additional control-plane surcharge. General VM and Kubernetes resource charges accrue with use and are invoiced at the end of the calendar month; GPU credits use a separate prepaid balance.
What are the GPU payment conditions?
GPU deployment requires at least US$20 in prepaid GPU credits. Each deployment has a ten-minute minimum charge, then per-second billing. Prices and availability depend on the live offer and configuration. A zero balance triggers a 30-minute top-up grace period before suspension.
How is inference charged?
Inference uses model-specific input and output token rates. It requires a Huddle01 API key and supported model identifier; renting GPU hardware is not required for this managed inference workflow.
What remains my responsibility?
Customers remain responsible for guest operating-system patches, application security, credentials, and external application-data backups. Managed infrastructure does not replace those tasks.
Datos rápidos
- Type
- Cloud platform with managed AI inference
- Users
- Developers and application teams
- Access
- Console, APIs, and SSH for deployed servers
- Payment model
- Metered resource and inference charges; prepaid GPU credits
Análisis de tráfico de Huddle01 Cloud
Los datos de tráfico son solo como referencia.
- Valoración del dominio
- 64
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