Jarvis Labs
Cost-effective GPU cloud for ML practitioners
Last reviewed Mar 14, 2026
JarvisLabs offers GPU templates, root-access VMs, multi-node clusters and model inference (APIs, managed endpoints, serverless) with per‑minute billing on H200/H100/RTX Pro 6000/A100/L4; strong India presence and pause/resume.
Available GPUs
Hourly on-demand pricing. Click column headers to sort.
Prices last updated: October 4, 2026
Jarvis Labs pricing by GPU
Configurations, price rank, and alternatives for one GPU at a time.
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
- Large clusters, reserved capacity and committed pricing go through sales rather than self-service
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
Network Isolation
Private VPC networking on chosen IP ranges, security groups for inbound/outbound firewall rules, and reserved public IPs that persist across pause and resume
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
GPU Clusters
Multi-node clusters for distributed training
- Instant Clusters launched from the dashboard
- Reserved clusters of 128 to 1,024+ GPUs on InfiniBand
- H200 SXM InfiniBand nodes
Inference
Model serving options from hosted APIs to bring-your-own stacks
- Model APIs: hosted open models through an OpenAI-compatible API, billed per token
- Managed Endpoints: deploy a catalog model with GPU configuration and serving image maintained by Jarvislabs
- Serverless: deploy your own model on vLLM, SGLang or Ollama, scaling to zero and billed per worker-minute
CPU VMs
General-purpose on-demand CPU VMs at a 1:4 vCPU-to-RAM ratio, from 2 to 32 vCPUs, in the India (Noida) region
Shared Filesystems
Network storage that mounts on any number of instances so datasets and checkpoints outlive a single machine
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 | Small discounts for 1-month, 3-month, 6-month and 1-year commitments, up to 9% off on-demand with a 1-year term |
| Volume and Reserved Capacity | Custom quotes through sales for 25+ GPUs, reserved capacity and H200 InfiniBand clusters |
| Model API Token Pricing | Hosted open models billed per input and output token, with rates set per model |
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
Frequently Asked Questions
What GPU types does Jarvis Labs offer?
Jarvis Labs offers various GPU types including A100 PCIE, A100 SXM, H100 SXM, H200, A30, L4, RTX PRO 6000. Check the pricing table above for current availability and pricing.
How do I get started with Jarvis Labs?
Create a New Account, Recharge Your Wallet, Choose and Launch a Template, Manage Your Instances
What are Jarvis Labs's main advantages?
Jarvis Labs's main advantages include: 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.
What are Jarvis Labs's limitations?
Jarvis Labs's main limitations include: Primarily focused on India and EU regions, Newer player compared to established cloud giants, Large clusters, reserved capacity and committed pricing go through sales rather than self-service.
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