GPU Cloud Provider · Unavailable
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.
Founded
Unavailable
Countries
2
Data Centers
1
Team Size
11-50
Company Profile
Company TypeStartup
Provider TypeCloud Provider
FoundedUnavailable
HeadquartersUnavailable
FundingBootstrapped
Team Size11-50
Infrastructure
GPU FleetNVIDIA A100 80GB, NVIDIA A100 40GB, NVIDIA RTX 4090, NVIDIA RTX 3090, NVIDIA RTX A6000, NVIDIA V100
Network FabricInternet-based cloud infrastructure
ConnectivityHigh-speed internet connectivity (specific speeds not detailed)
StorageBlock storage up to 2TB, Persistent and ephemeral storage options
Bare MetalNo
AvailabilityGeneral Availability
StartupResearchHobbyistEnterprise
Compute & Deployment
On-DemandYes
Spot / InterruptibleNo
Reserved InstancesYes (pause and resume instances; monthly plans available)
Bare MetalNo
VM-BasedNo
Container-BasedYes (Docker-based environments with pre-built deep learning frameworks)
KubernetesNo
Serverless GPUNo
Spin-Up TimeUnder 2 minutes
TerraformNo
GPU Hardware
Latest GenH100 SXM, H100 PCIe, A100 SXM
Legacy SupportA100 PCIe, A6000, A5000, RTX 5000 Ada
Multi-GPU NodesYes (up to 8x per node)
Max GPUs/Node8
NVLinkYes (SXM nodes)
PCIe vs SXMBoth PCIe and SXM
Pricing Model
Per HourYes (primary billing unit)
Per MinuteNo
SubscriptionNo
Spot DiscountNo spot pricing
Public PricingYes
Hidden FeesNone disclosed
Pay-as-you-goYes
Credit SystemYes (prepaid credits)
Performance & Scaling
Multi-Node TrainingLimited (manual setup required, no managed multi-node orchestration)
Elastic ScalingNo
Auto ScalingNo
Perf IsolationPartial (dedicated GPU instances, but infrastructure details not fully disclosed)
Developer Experience
OnboardingDeploy in minutes via web UI; sign up and launch GPU instance quickly with minimal setup
FrameworksPyTorch, TensorFlow, CUDA libraries, Other popular AI and machine learning frameworks (generically supported)
SDK LanguagesPython
CLI ToolingBasic CLI for instance management and file transfer
JupyterNative JupyterLab integration available directly from dashboard
TemplatesPyTorch, TensorFlow, Fast.ai, Stable Diffusion, LLM Fine-tuning, JAX
DocumentationComprehensive docs with tutorials, quickstart guides, and framework-specific examples
API FeaturesCLI tools, SDK support, Python-based client library (JLclient)
Security & Compliance
SecurityRegular security updates,Compliance with industry-standard security protocols
ComplianceISO27001 (presumed based on industry practices)
Positive community reviews among AI researchers and studentsUsed by indie AI developers and researchers
Data Center Locations
Coverage
CountriesIndia, United States
CitiesNot disclosed
Asia-PacificNorth AmericaEurope
Compliance Regions
EU Data ResidencyNo EU presence
US Gov CloudNo
India RegionYes
Datacenter Locations
Key Strengths
Extremely simple and beginner-friendly interface
Competitive pricing for A100 and consumer GPU instances
Pre-configured deep learning environments ready out of the box
Research and indie developer focused platform
Known Limitations
Limited regional availability
No spot/preemptible instances
No reserved instance discounts
Small fleet compared to hyperscalers
Limited enterprise features and SLAs
No Windows support
Additional Information
Support Options
["Email support","Documentation","Community forums (presumed based on industry practices)"]
Community
Discord community and social media presence
Core Proposition
Affordable GPU cloud focused on deep learning practitioners with fast instance spinup and simple pricing.
Payment Methods
Credit Card
Last updated March 2026. Information subject to change.