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GPUwerkvsJarvis Labs

GPUwerk vs Jarvis Labs: Pricing, Specs, Strengths & Weaknesses

Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for GPUwerk and Jarvis Labs. Rates sourced from public APIs — verify current availability and billing terms before purchasing.

Overview

Attribute
GPUwerk
Jarvis Labs
Provider type
Specialist
Specialist
Founded
2020
Headquarters
Prague, Czech Republic (datacenter: Hradec Kralove, CZ)
San Francisco, CA
Billing model
Per-minute from prepaid credit; optional 1–24 month reservations
On-demand (per-second)
Min commitment
None (reservations optional)
None
Support tier
Standard
Community → Pro
Regions
2 regions
2 regions

Strengths & Best For

GPUwerk

GPUwerk is a specialist GPU cloud operated by PRINT IT! SE, based in Prague with datacenter infrastructure in Hradec Kralove, Czech Republic. The platform offers dedicated machine rentals with per-minute billing from prepaid credit, no egress fees, and optional 1–24 month reservations. Current catalog: DGX Spark (GB10) with 128 GB unified LPDDR5x memory, RTX 5090 32 GB, and a linked 2-node DGX Spark cluster (256 GB total across two nodes, not one pool) at $1.79/hr. EU data residency (Czech Republic).

Strengths
  • Dedicated machine per rental — no shared tenancy
  • Per-minute billing from prepaid credit
  • EU data residency (Czech Republic)
  • No egress fees
  • DGX Spark (GB10) with 128 GB unified LPDDR5x memory
Weaknesses
  • No workspace backup
  • Container access only — not host root
  • Stopped instances billed at 75% of on-demand rate
  • DGX Spark uses Arm64 architecture — container images must target linux/arm64
Best For
EU data residency (Czech Republic)DGX Spark workloads (Arm64, large unified memory)RTX 5090 inference in the EUDedicated machines with per-minute billing
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Jarvis Labs

Jarvis Labs is an ML-focused GPU cloud offering H100, A100, and RTX instances with per-second billing, pre-configured environments for PyTorch, TensorFlow, and other popular frameworks, and a simple interface designed for machine learning engineers. On-demand GPU rental with no minimum commitment makes it easy to spin up and tear down instances for training runs, fine-tuning, and AI inference experiments. A popular choice for ML engineers who want pre-built environments and granular per-second billing.

Strengths
  • Per-second billing — no minimum commitment
  • Pre-configured PyTorch/TensorFlow environments
  • Simple UI designed for ML engineers
  • Fast provisioning
Weaknesses
  • Small provider — limited GPU availability at scale
  • No enterprise SLAs
  • Limited regions and GPU SKU variety
Best For
ML engineers wanting pre-built environmentsNotebook-based training workflowsTeams wanting per-second billing on GPU instances
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Region Coverage

GPUwerk — 2 regions
CZEU
Jarvis Labs — 2 regions
USEU

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Provider pages

GPUwerk pricing and specs Jarvis Labs pricing and specs

Key differences

GPUwerk

EU specialist GPU cloud — DGX Spark and RTX 5090, per-minute billing, Czech Republic

Jarvis Labs

ML-focused GPU cloud with per-second billing and pre-configured environments

AttributeGPUwerkJarvis Labs
Provider typespecialistspecialist
Billing modelPer-minute from prepaid credit; optional 1–24 month reservationsOn-demand (per-second)
Min commitmentNone (reservations optional)None
Regions2 (CZ, EU)2 (US, EU)
Support tierStandardCommunity → Pro
Best forEU data residency (Czech Republic), DGX Spark workloads (Arm64, large unified memory)ML engineers wanting pre-built environments, Notebook-based training workflows
Founded / HQ · Prague, Czech Republic (datacenter: Hradec Kralove, CZ)2020 · San Francisco, CA