Prices updated 2026-06-23 — sourced from live provider data

Jarvis Labs A6000 Pricing Options

All available A6000 instance types on Jarvis Labs, sorted by lowest hourly rate.

Region Instance Type Price/hr GPUs vCPUs RAM
us A6000_x1 On-Demand $1.9900/hr Cheapest 1× GPU 8 vCPU 60 GB
us A6000_x2 On-Demand $3.9800/hr 2× GPU 16 vCPU 120 GB

About Jarvis Labs A6000 Cloud Pricing

Jarvis Labs provides affordable GPU cloud instances tailored for ML practitioners, with pre-configured environments and JupyterLab access. They focus on making GPU compute accessible for individual researchers and small teams.

Why Choose Jarvis Labs for A6000

  • Pre-configured ML environments with popular frameworks
  • JupyterLab interface for interactive development
  • Competitive pricing for smaller GPU instances
  • Persistent storage across sessions

Best suited for: Individual ML researchers, students, and small teams who want an affordable, ready-to-use GPU development environment.

A6000 Technical Overview

ArchitectureAmpere (Professional)
Memory48 GB GDDR6
Best ForProfessional visualization, medium-scale training, and workloads needing 48 GB VRAM

The A6000 provides 48 GB of VRAM — more than the A100-40GB — at a lower price point. It lacks the HBM bandwidth of A100 but excels at workloads that are memory-capacity-bound rather than bandwidth-bound.

Pricing Analysis

Jarvis Labs's cheapest A6000 option starts at $1.9900/hr, which is 22% above the market average of $1.6320/hr. Jarvis Labs currently offers on-demand pricing only for A6000. This means no commitment required, but you won't access the deeper discounts available from reserved or spot pricing.

Note: Jarvis Labs is well-suited for prototyping and experimentation, though production-scale training may require a provider with more infrastructure depth.

Market context: A6000 occupies a niche between consumer GPUs and enterprise A100s. It's cost-effective when you need more than 24 GB VRAM but don't need HBM bandwidth.

Top Alternatives to Jarvis Labs for A6000

Side-by-side cost comparison vs the cheapest Jarvis Labs A6000 rate ($1.9900/hr).

Provider Price/hr Type vs Jarvis Labs
RunPod $0.3300/hr On-Demand -83% cheaper vs Jarvis Labs
Vast.ai $0.4022/hr Spot -80% cheaper vs Jarvis Labs
TensorDock $0.7000/hr Spot -65% cheaper vs Jarvis Labs
Lambda Labs $1.0900/hr On-Demand -45% cheaper vs Jarvis Labs
CoreWeave $1.7500/hr On-Demand -12% cheaper vs Jarvis Labs

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Frequently Asked Questions

How much does Jarvis Labs A6000 cost per hour in 2026? +
Jarvis Labs A6000 starts at $1.9900/hr (on-demand). The market average for A6000 across all providers is $1.6320/hr. Jarvis Labs offers 2 A6000 configurations ranging from $1.9900 to $3.9800/hr. Use the GPU cost calculator to estimate total cost based on your hours and workload type.
What are the cheapest alternatives to Jarvis Labs for A6000? +
There are 6 providers offering A6000 cheaper than Jarvis Labs: RunPod at $0.3300/hr, Vast.ai at $0.4022/hr, TensorDock at $0.7000/hr, and 3 more. See the full comparison table for all A6000 providers.
Does Jarvis Labs offer reserved or spot A6000 pricing? +
Jarvis Labs offers 1 pricing type for A6000: on-demand. With on-demand only, you pay per hour with no commitment. While you won't get reserved or spot discounts, this provides maximum flexibility for unpredictable workloads.
What workloads is Jarvis Labs A6000 best suited for? +
The A6000 (Ampere (Professional) architecture, 48 GB GDDR6) is best suited for Professional visualization, medium-scale training, and workloads needing 48 GB VRAM. Jarvis Labs is a developer focused provider — Individual ML researchers, students, and small teams who want an affordable, ready-to-use GPU development environment.
How much does it cost to run A6000 on Jarvis Labs for a month? +
At Jarvis Labs's cheapest A6000 rate of $1.9900/hr: running 24/7 costs ~$47.76/day or ~$1452.70/month per GPU. For training jobs, costs scale linearly — a 100-hour training run would cost ~$199.00. Multi-GPU configurations multiply accordingly. Use the cost calculator for precise estimates with your specific parameters.
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