Jarvis Labs
Cost-effective GPU cloud for ML practitioners
Last reviewed Mar 14, 2026
JarvisLabs offers managed Jupyter/VMs with per‑minute billing on H200/H100/A100; strong India presence and pause/resume.
Available GPUs
Hourly on-demand pricing. Click column headers to sort.
Prices last updated: July 7, 2026
GPU Model↑ | Memory↑ | GPUs | vCPUs | RAM | Price / hr↑ | Updated↑ | Source |
|---|---|---|---|---|---|---|---|
| A100 PCIE | 40GB | 1× | 16 | 112 GB | $0.890/hr | 7/7/2026 | |
| A100 SXM | 80GB | 1× | 16 | 112 GB | $1.49/hr | 7/7/2026 | |
| A30 | 24GB | 1× | 16 | 112 GB | $0.410/hr | 7/7/2026 | |
| H100 SXM | 80GB | 1× | 16 | 200 GB | $2.69/hr | 7/7/2026 | |
| H200 | 141GB | 1× | 28 | 368 GB | $3.80/hr | 7/7/2026 | |
| L4 | 24GB | 1× | 32 | 124 GB | $0.440/hr | 7/7/2026 | |
| RTX PRO 6000 | 96GB | 1× | 28 | 160 GB | $1.89/hr | 7/7/2026 |
Pros & Cons
Advantages
- Quick setup - get started in less than 5 minutes
- Per-minute billing for precise cost control
- Fast boot times (templates in 1.8s, VMs under 90s)
- Agent-native support for Claude Code, Cursor, and AI coding tools
- Easy instance lifecycle management (pause, resume, delete)
- Ability to switch GPU types when resuming instances
- Strong community endorsements from AI practitioners
- Comprehensive CLI and Python SDK
Limitations
- Primarily focused on India and EU regions
- Newer player compared to established cloud giants
- Limited enterprise-level features for large organizations
Key Features
Instant GPU Access
Get access to powerful GPUs instantly with zero setup complexity
Fast Boot Times
Boot templates in 1.8 seconds or VMs in under 90 seconds
Per-minute Billing
Pay-as-you-go with per-minute billing and no upfront commitments
CLI & Python SDK
Comprehensive command-line and Python SDK with agent integration for Claude Code, Cursor, and other AI coding agents
Multi-GPU Scaling
Scale up to 8 GPUs per instance for demanding workloads
Instance Management
Easy pause, resume, and delete functionality for cost optimization
Template Library
Wide range of pre-configured templates for PyTorch, TensorFlow, ComfyUI, and other ML frameworks
GPU Switching
Switch GPU types when resuming paused instances for optimal resource utilization
Compute Services
GPU Instances
On-demand GPU instances with various configuration options
- Pre-configured templates for popular ML frameworks
- Scalable GPU resources
- Instance pause and resume capabilities
- SSH access for full control
Templates
Pre-built environments for instant deployment
- Boot in 1.8 seconds
- Persistent storage across stop/start
- One-click API or notebook URL exposure
- Up to 8 GPUs per template
Virtual Machines
Full root access VMs for custom configurations
- Root SSH access from minute one
- Custom Docker/Kubernetes support
- Custom kernels and drivers
- Up to 8 GPUs per VM, multi-region
Pricing Options
| Option | Details |
|---|---|
| On-Demand Instances | Per-minute billing with no minimum commitments and instant provisioning |
| Spot Instances | Use spare capacity with significant discounts up to 56% off on-demand pricing |
| Monthly Commitments | Save up to 21% with 1-month commitments or up to 32% with 6-month commitments |
Availability & Support
Regions
GPU clusters deployed in India (Noida) and Europe with flexible regional instance management
Support
Documentation, tutorials, and getting started guides available
Getting Started
- 1
Create a New Account
Sign up for a new account on the Jarvis Labs platform
- 2
Recharge Your Wallet
Add funds to your account in the Recharge section
- 3
Choose and Launch a Template
Explore the wide range of templates, configure your desired setup, and click Launch
- 4
Manage Your Instances
Easily pause ⏸️, resume ▶️, and delete 🗑️ your instances with just a few clicks
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