Jarvis Labs

Jarvislabs.ai is a powerful GPU cloud platform designed to offer instant access to a wide range of GPUs and customizable environments for training machine learning models, developing AI applications, and conducting research. It provides a user-friendly platform with enterprise-grade infrastructure, a pay-as-you-go pricing model, and requires no setup.

Jarvis Labs

Provider Profile

Founded

Unavailable

Headquarters

Unavailable

Pricing Model

Pay-as-you-go with minute-level billing, with prices depending on the instance type and configuration.

Provider Console

Technical Specification

Target Audience
  • Researchers
  • AI developers
  • startups
  • and organizations requiring flexible
  • powerful GPU resources for AI projects
GPU Clusters & Offerings
  • H200 SXM (141GB VRAM, 200GB RAM, 16 vCPUs)
  • H100 SXM (80GB VRAM, 200GB RAM, 16 vCPUs)
  • RTX5000 (16GB VRAM, 32GB RAM, 7 vCPUs)
  • A5000 (24GB VRAM, 64GB RAM, 32 vCPUs)
  • A6000 (48GB VRAM, 32GB RAM, 7 vCPUs)
  • RTX6000 Ada (48GB VRAM, 128GB RAM, 32 vCPUs)
  • A100 (40GB VRAM, 32GB RAM, 7 vCPUs)
Network Fabric
Internet-based cloud infrastructure
Connectivity Bandwidth
High-speed internet connectivity (specific speeds not detailed)
Storage Architecture
  • Block storage up to 2TB
  • Persistent and ephemeral storage options
Compute Framework Compatibility
  • PyTorch
  • TensorFlow
  • CUDA libraries
  • Other popular AI and machine learning frameworks (generically supported)
Resource Orchestration
Docker support within VMs
Security Infrastructure
  • Regular security updates
  • Compliance with industry-standard security protocols
Developer Interface & APIs
  • CLI tools
  • SDK support
  • Python-based client library (JLclient)
Support Operations
  • Email support
  • Documentation
  • Community forums (presumed based on industry practices)
Resource Availability
General Availability
Datacenter Locations
Regulatory Compliance
ISO27001 (presumed based on industry practices)
Key Platform Features
  • Flexible instance types with adjustable GPU and storage options
  • Minute-level billing to prevent cost wastage
  • Managed workbench instances for simplified setup
  • Regional flexibility for seamless operations
  • Support for a variety of popular AI frameworks and tools
  • API for programmatic control and integration

Last Audit: February 2026