JarvisLabs.ai
Verified ProviderTier 3 Datacenter 4.8 / 5.0 (215 reviews)Researcher-First GPU Cloud with 1-Click JupyterLab & Auto-Pause Storage
JarvisLabs.ai is the premier GPU cloud built by AI researchers for AI researchers. Featuring 1-click web JupyterLab and VS Code, per-minute billing, and automated instance pausing that drops storage cost to just $0.0001/GB/hr while keeping all conda environments, checkpoints, and weights intact.
JarvisLabs.ai GPU Catalog & Real-Time Hourly Pricing (4 Tiers)
| GPU Model (Click for Specs) | VRAM | Interconnect | vCPU / System RAM | Spot Hourly | On-Demand Hourly | Actions |
|---|---|---|---|---|---|---|
| NVIDIA GeForce RTX 4090 | 24 GB | PCIe 4.0 x16 | 8 vCPUs / 32GB | $0.42/hr-14% | $0.49/hr | |
| NVIDIA RTX A6000 48GB | 48 GB | PCIe 4.0 x16 | 12 vCPUs / 60GB | $0.50/hr-15% | $0.59/hr | |
| NVIDIA A100 SXM4 80GB | 80 GB | NVLink (Fast) | 16 vCPUs / 120GB | $1.49/hr-12% | $1.69/hr | |
| NVIDIA H100 SXM5 80GB | 80 GB | NVLink (Fast) | 24 vCPUs / 180GB | $2.69/hr-10% | $2.99/hr |
JarvisLabs.ai Monthly Cost & Stopped Storage Estimator
Simulate your real-world monthly bill including active GPU compute and stopped persistent volume storage overhead.
When you click Stop Instance on JarvisLabs.ai, your GPU compute charge stops, but the 200GB disk volume continues billing 24/7 ($20.00/mo) until you terminate the volume. Always backup checkpoints to HuggingFace or S3 before terminating.
Hourly run-rate: $0.42/hr compute + $0.0274/hr disk
Equivalent cloud capacity on AWS would cost approx. $245/mo for 6h daily runtime.
- •Targeted primarily at individual researchers and mid-size teams rather than massive multi-million dollar training clusters.
- •Data transfer between different regions requires manual rsync or cloud bucket sync.
- ✓Features one of the most intuitive web-based control planes with built-in 1-click JupyterLab, VS Code, and FastHTML.
- ✓Pause/Resume functionality works cleanly: environment, Python packages, and weights remain intact upon resume.
- ✓Very competitive pricing on single RTX 4090 ($0.49/hr) and RTX A6000 ($0.59/hr) with seamless storage persistence.
Full-Lifecycle TCO & Hidden Cost EstimatorReal Invoicing
Calculate actual project costs including stopped storage fees and network egress penalties.
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1-Click Docker & SSH Recipes for JarvisLabs.ai
Tested terminal commands for immediate deployment on NVIDIA GeForce RTX 4090 instances.
# 1. SSH into your JarvisLabs.ai instance: # ssh root@<instance_ip> -p <ssh_port> # 2. Launch ComfyUI with FLUX.1 & SDXL model cache: docker run -d --gpus all --name comfyui \ --restart unless-stopped \ -p 8188:8188 \ -v /workspace/ComfyUI/models:/root/ComfyUI/models \ -v /workspace/ComfyUI/output:/root/ComfyUI/output \ yanwk/comfyui-boot:cu124 # Access ComfyUI in your browser at: http://<instance_ip>:8188
JarvisLabs.ai Architecture, Gotchas & Engineering Verdict
JarvisLabs.ai maintains dedicated enterprise Tier 3/4 colocation facilities with redundant UPS power, multi-gigabit fiber backbones, and formal uptime SLAs.
- ✓Extremely competitive hourly spot rates with up to 60% savings.
- ✓Direct root SSH and Docker container flexibility.
- ✓Instant credit card onboarding with transparent billing.
- !Stopped Storage Fee: Persistent disk volumes accrue billing 24/7 ($0.07/GB/month ($0.0001/GB/hr)) until deleted.
- !Bandwidth Variance: Verify host download speeds before pulling 50GB+ model checkpoints.
Developer Reviews & Telemetry Audit
Aggregated from 215 verified AI engineers deploying vLLM, ComfyUI, and production API workloads.
“JarvisLabs was built by researchers for researchers. The auto-pause feature stops the GPU compute when my Jupyter notebook is idle but keeps my environment and dataset cached for just $0.0001/GB/hr. RTX 4090 at $0.49/hr is unmatched.”
“Booting a fresh RTX A6000 takes under 30 seconds. VS Code server in the browser connects immediately with SSH keys preloaded. The per-minute billing means I only pay for the exact training epochs I run.”