GPU Cloud Provider · India
Jarvislabs
Jarvislabs specializes in providing on-demand GPU cloud services for AI and machine learning workloads, offering a range of NVIDIA GPUs with per-minute billing and no long-term commitments. The provider emphasizes quick setup and flexibility, catering to researchers and startups with scalable GPU options.
Founded
2020
Countries
2
Data Centers
2
Team Size
11-50
Company Profile
Company TypeStartup
Provider TypeCloud Provider
Founded2020
HeadquartersIndia
FundingBootstrapped
Team Size11-50
Infrastructure
GPU FleetNVIDIA H100 SXM, NVIDIA A100 80GB, NVIDIA A100 40GB, NVIDIA RTX 6000 Ada, NVIDIA RTX A6000, NVIDIA RTX 3090
Network FabricInfiniBand specified for multi-GPU connectivity
ConnectivityDetails not specified
StorageNo specific storage types mentioned
Bare MetalNo
AvailabilityGA (General Availability)
StartupResearchEnterpriseHobbyist
Compute & Deployment
On-DemandYes
Spot / InterruptibleNo
Reserved InstancesYes (weekly and monthly plans available)
Bare MetalNo
VM-BasedNo
Container-BasedYes (Docker-based instances)
KubernetesNo
Serverless GPUNo
Spin-Up TimeUnder 2 minutes
TerraformNo
GPU Hardware
Latest GenH100 SXM, H100 PCIe
Legacy SupportA100, A6000, RTX 5000 Ada, RTX 6000 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, not a primary advertised feature)
Elastic ScalingNo
Auto ScalingNo
NVSwitchYes (on SXM H100 nodes)
Perf IsolationYes (dedicated bare metal instances)
Noisy NeighborYes (bare metal, no sharing)
Developer Experience
OnboardingDeploy in minutes via web UI; account verification required before first launch
FrameworksNo specific frameworks mentioned
SDK LanguagesPython
CLI ToolingBasic CLI for instance management; SSH access supported
JupyterNative JupyterLab integration available on all instances
TemplatesPyTorch, TensorFlow, Fast.ai, RAPIDS, Hugging Face Transformers, Stable Diffusion, LLM Fine-tuning
DocumentationBasic to moderate documentation with framework-specific getting-started guides
API FeaturesNo specific API features mentioned
Security & Compliance
SecurityNo specific details
ComplianceNo specific certifications mentioned
Established customer base in AI/ML research communityPublicly listed GPU pricing with transparencyActive product updates and GPU fleet expansion
Data Center Locations
Coverage
CountriesIndia, United States
CitiesChennai, Dallas TX
Multi-Region FailoverNo
Asia-PacificNorth AmericaEurope
Compliance Regions
EU Data ResidencyNo EU presence
US Gov CloudNo
India RegionYes (Chennai)
Datacenter Locations
Key Strengths
Competitive H100 and A100 pricing targeting researchers and small teams
Simple web UI with fast instance launch and prebuilt ML frameworks
Jupyter-first workflow with native JupyterLab integration
No long-term commitments required
India-based provider with pricing attractive to global research community
Known Limitations
Limited geographic regions compared to major providers
No spot/preemptible instance pricing
No SLA or uptime guarantees published
Smaller GPU fleet with potential availability constraints
Limited enterprise features such as VPC, private networking, or SSO
No Windows support
Minimal community presence and ecosystem compared to larger providers
Additional Information
Support Options
["Email support"]
Community
Limited; primarily Discord and email support
Core Proposition
Affordable GPU cloud with fast spin-up times, tailored for ML/AI workloads with pre-configured deep learning environments and pause-resume billing.
Payment Methods
Credit CardPayPal
Last updated March 2026. Information subject to change.