Provider Comparison

Atlantic.net vs TensorDock

Atlantic.net and TensorDock offer distinct GPU cloud solutions for ML/AI workloads, catering to different priorities. Atlantic.net, a long-standing IaaS provider, focuses on enterprise-class bare-metal infrastructure with high-performance computing tailored for regulated industries. It excels in HIPAA-compliant hosting for healthcare, backed by SOC 2, GDPR compliance, and a 100% uptime SLA. Billing is per-hour on a rigid model without spot instances or managed MLOps tools like notebooks, making it suitable for teams prioritizing stability, raw GPU performance, and long-term deployments over cost optimization. TensorDock, a GPU marketplace recently stabilized by Voltage Park's acquisition, emphasizes extreme affordability through spot pricing and per-second billing. This model aggregates inventory for on-demand and interruptible instances, appealing to cost-sensitive users. However, it lacks the compliance certifications and guaranteed uptime of Atlantic.net, with potential variability in GPU availability. Atlantic.net's value proposition centers on reliability for production-critical workloads in compliant environments, while TensorDock prioritizes minimizing costs for bursty or experimental compute. ML engineers should weigh compliance needs, uptime guarantees, and billing flexibility: Atlantic.net for mission-critical stability, TensorDock for economical scaling on spot-tolerant tasks. Neither provides extensive managed services, requiring users to handle orchestration.

Visit Atlantic.net Visit TensorDock

Our Recommendation

Select Atlantic.net for regulated enterprises, especially healthcare (HIPAA needs), or teams requiring bare-metal performance, 100% uptime SLA, and compliance (SOC 2, GDPR). Ideal for mid-to-large teams (10+ engineers) running production inference or long-term training on stable clusters, where budgets accommodate per-hour on-demand pricing without spot risks. Avoid if needing managed MLOps or ultra-low costs. Choose TensorDock for budget-constrained startups, researchers, or small teams (1-10 engineers) focused on cost savings via spot instances and per-second billing. Best for interruptible workloads like experimentation or batch jobs, where GPU variety and marketplace flexibility outweigh compliance or uptime guarantees. Not suitable for real-time production or regulated data due to potential interruptions and lacking certifications.

Live Pricing

Compare real-time GPU offers from Atlantic.net and TensorDock

54 offers available

Provider	GPU Model	VRAM	Host Specs	Region	Price	Status
TensorDock	NVIDIA RTX A4000 16GB VRAM	16GB	0 vCPU 0GB RAM	Tallinn, Harjumaa	$0.08/GPU/hr	Available
TensorDock	NVIDIA RTX A4000 16GB VRAM	16GB	0 vCPU 0GB RAM	Tallinn, Harjumaa	$0.08/GPU/hr	Sold Out
TensorDock	NVIDIA RTX A4000 16GB VRAM	16GB	0 vCPU 0GB RAM	Detroit, Michigan	$0.08/GPU/hr	Sold Out
TensorDock	NVIDIA RTX A4000 16GB VRAM	16GB	0 vCPU 0GB RAM	Tallinn, Harjumaa	$0.10/GPU/hr	Sold Out
TensorDock	NVIDIA RTX A4000 16GB VRAM	16GB	0 vCPU 0GB RAM	Rzeszow, Subcarpathian	$0.10/GPU/hr	Sold Out

TensorDock

Tallinn, Harjumaa

Available

NVIDIA RTX A4000

16GB VRAM

0 vCPU

0GB RAM

1000 Mbps ↑

1000 Mbps ↓

$0.08/GPU/hr

TensorDock

Tallinn, Harjumaa

Sold Out

NVIDIA RTX A4000

16GB VRAM

0 vCPU

0GB RAM

$0.08/GPU/hr

TensorDock

Detroit, Michigan

Sold Out

NVIDIA RTX A4000

16GB VRAM

0 vCPU

0GB RAM

$0.08/GPU/hr

TensorDock

Tallinn, Harjumaa

Sold Out

NVIDIA RTX A4000

16GB VRAM

0 vCPU

0GB RAM

$0.10/GPU/hr

TensorDock

Rzeszow, Subcarpathian

Sold Out

NVIDIA RTX A4000

16GB VRAM

0 vCPU

0GB RAM

$0.10/GPU/hr

View all 54 offers

Atlantic.net(Est. 1994)

A veteran in the infrastructure-as-a-service market focusing on enterprise-class infrastructure with a pivot into high-performance computing for regulated industries.

Best For

Healthcare organizations requiring HIPAA-compliant GPU hostingEnterprises seeking raw performance of bare metal with long-term stability

Unique Features

100% uptime SLA
Bare-metal delivery model

Limitations

Lack of managed MLOps tools like notebooks and endpoints
Rigid pricing model without spot markets

TensorDock(Est. 2021)

A GPU marketplace offering extremely low spot prices, stabilized by acquisition by Voltage Park.

Best For

Extremely low spot prices

Unique Features

Marketplace model
Stabilized inventory post-acquisition

Feature Comparison

Access Methods

Feature	Atlantic.net	TensorDock
SSH
Jupyter Notebooks
Web Terminal
API
Kubernetes
Containers

Billing Options

Feature	Atlantic.net	TensorDock
Billing Increment	per-hour	per-second
Spot Instances
Reserved Instances
Prepaid Credits

Compliance

Certification	Atlantic.net	TensorDock
SOC 2
HIPAA
GDPR
ISO 27001

Support

Feature	Atlantic.net	TensorDock
SLA
Enterprise Support
Discord Community

Pricing Analysis

Pricing Overview

Atlantic.net employs per-hour on-demand billing with a rigid model, lacking spot markets, reserved instances, or per-second granularity. This ensures predictable costs for sustained usage but penalizes short bursts or idle time, as minimum charges apply hourly. No discounts for commitment beyond standard enterprise negotiations. TensorDock uses per-second billing with spot instances at significantly lower rates (often 50-80% cheaper than on-demand), alongside standard on-demand options via its marketplace model. Spot pricing introduces savings for interruptible workloads but risks interruptions during high demand. Post-acquisition stabilization improves inventory reliability. Implications: TensorDock favors variable, short-duration jobs (e.g., <1 hour experiments), minimizing waste; Atlantic.net suits steady, long-running tasks (>hours) needing cost predictability without eviction risks.

Value Assessment

For small experiments or fine-tuning (<1 hour), TensorDock delivers superior value via per-second spot pricing, enabling 3-5x savings over Atlantic.net's hourly minimums. Large training runs (days-long) favor TensorDock if spot-tolerant with checkpointing, leveraging low rates for high-volume GPU hours; otherwise, Atlantic.net's stability justifies premium for uninterrupted progress. Production inference splits: batch inference suits TensorDock's spots for cost efficiency; real-time inference prefers Atlantic.net's uptime SLA to avoid latency spikes. Overall, TensorDock maximizes value for budgets < $10k/month on non-critical workloads; Atlantic.net for >$50k/month enterprise spends prioritizing reliability over 30-70% spot discounts.

Use Case Comparison

LLM Training

Atlantic.net recommended

Atlantic.net

Atlantic.net's bare-metal GPUs and 100% uptime SLA ensure uninterrupted, high-performance multi-GPU training for large models, ideal for regulated data. Raw HPC focus supports efficient scaling without virtualization overhead, though per-hour billing increases costs for long runs without spot flexibility.

TensorDock

TensorDock's spot marketplace offers low-cost GPUs for training, with per-second billing suiting variable durations. Stabilized inventory reduces eviction risks, but interruptions demand robust checkpointing; lacks bare-metal consistency for optimal inter-GPU bandwidth.

Batch Inference

TensorDock recommended

Atlantic.net

Atlantic.net provides stable bare-metal for reliable batch processing, with compliance for sensitive data. Uptime SLA minimizes retries, but rigid hourly pricing inflates costs for sporadic, interruptible jobs without managed orchestration.

TensorDock

TensorDock excels with ultra-cheap spot instances and per-second billing, perfect for scalable, cost-optimized batches. Marketplace variety allows quick GPU access; interruptions manageable via queuing, yielding high value for non-urgent inference.

Real-time Inference

Atlantic.net recommended

Atlantic.net

Atlantic.net's 100% SLA and bare-metal delivery guarantee low-latency, consistent performance for production endpoints. Compliance suits enterprise deployments; lacks managed endpoints but supports custom Kubernetes for scaling.

TensorDock

TensorDock's spot model risks interruptions unsuitable for real-time SLAs, though on-demand options exist at low rates. Per-second billing aids variable traffic, but no uptime guarantees or compliance limit production reliability.

Fine-tuning & Experimentation

TensorDock recommended

Atlantic.net

Atlantic.net offers stable bare-metal for iterative fine-tuning, with enterprise reliability. Hourly billing less efficient for short experiments; no notebooks mean self-managed environments, better for structured teams than rapid prototyping.

TensorDock

TensorDock's per-second spot pricing optimizes short, bursty experiments, enabling more iterations at low cost. Marketplace flexibility provides diverse GPUs quickly; ideal for solo researchers despite potential availability variability.

Technical Comparison

Infrastructure

Atlantic.net delivers bare-metal GPUs for direct hardware access, emphasizing enterprise networking (low-latency, high-bandwidth), persistent storage, and Kubernetes compatibility without virtualization overhead. Tailored for HPC in regulated setups, with robust compliance tooling. TensorDock's marketplace model virtualizes GPUs across providers, offering flexible spot/on-demand instances with per-second scaling. Storage and networking vary by listing; Kubernetes support likely via user configs. Less emphasis on bare-metal uniformity, post-acquisition improvements noted but details limited.

Performance

Atlantic.net provides consistent bare-metal performance with excellent multi-GPU scaling (e.g., NVLink-equivalent via direct interconnects) and high GPU availability for stable workloads; ideal for bandwidth-intensive training. TensorDock offers competitive perf at low cost, with diverse NVIDIA GPUs (A100/H100 availability via marketplace), but spot evictions and virtualization may impact scaling efficiency. Limited public benchmarks; stabilization aids reliability, yet bare-metal purity favors Atlantic.net for peak throughput.

Frequently Asked Questions

Which provider offers spot instances for cost savings?▾

TensorDock offers spot/preemptible instances, which can significantly reduce costs (typically 50-80% off on-demand prices) for interruptible workloads like batch processing and training with checkpoints. Atlantic.net does not currently offer spot instances, so all usage is billed at on-demand rates. If cost optimization through spot instances is important for your workflow, TensorDock would be the better choice.

What is the minimum billing increment for each provider?▾

Atlantic.net bills per-hour, while TensorDock bills per-second. Per-second billing from TensorDock offers better cost efficiency for short experiments and iterative development, as you only pay for exactly what you use.

Which provider has better compliance certifications for enterprise use?▾

Atlantic.net holds SOC 2, HIPAA, GDPR certifications. TensorDock holds no publicly listed certifications. For organizations with strict compliance requirements, Atlantic.net offers more comprehensive coverage.

Which provider offers better development tools like Jupyter notebooks?▾

TensorDock offers built-in Jupyter notebook support for interactive development, while Atlantic.net requires you to set up your own notebook environment. If quick iteration and experimentation are priorities, TensorDock's integrated notebooks provide a smoother experience. Additionally, TensorDock offers web-based terminal access for quick debugging.

Which provider has better Kubernetes support for orchestration?▾

Neither provider offers native Kubernetes support. You would need to manage your own Kubernetes cluster or use alternative orchestration methods for containerized workloads.

What is each provider best suited for?▾

Atlantic.net is best suited for Healthcare organizations requiring HIPAA-compliant GPU hosting; Enterprises seeking raw performance of bare metal with long-term stability. TensorDock excels at Extremely low spot prices. Understanding these specializations helps you choose the provider that aligns with your primary use case, though both can handle a variety of GPU computing needs.

Which provider offers reserved instances for long-term savings?▾

Atlantic.net offers reserved instance pricing for long-term commitments, while TensorDock does not currently offer this option. Reserved instances are ideal for predictable, steady-state workloads like always-on inference services. For variable workloads, on-demand or spot instances may offer better flexibility.

Which provider offers better enterprise support?▾

Atlantic.net offers dedicated enterprise support options, while TensorDock may have more limited support tiers. Regarding SLAs: Atlantic.net offers SLA guarantees (100% uptime); TensorDock has no published SLA.

Which provider has better API and automation support?▾

Atlantic.net provides a comprehensive API for programmatic control, while TensorDock may require more manual management. If automation is a priority, Atlantic.net's API support will streamline your infrastructure-as-code workflows.

Which provider has better container and Docker support?▾

Both Atlantic.net and TensorDock support containerized workloads, allowing you to deploy Docker images with your ML frameworks, dependencies, and models pre-configured. This ensures reproducibility and simplifies deployment across development, staging, and production environments.

What unique features differentiate these providers?▾

Atlantic.net's standout features include: 100% uptime SLA; Bare-metal delivery model. TensorDock's standout features include: Marketplace model; Stabilized inventory post-acquisition. These differentiators may be decisive factors depending on your specific technical requirements and workflow preferences.

How do I get started with each provider?▾

To get started with Atlantic.net, visit their website at https://cloud.atlantic.net/r/t3hjjhja?utm_source=gpuperhour&utm_medium=referral to create an account and explore available GPU options. For TensorDock, visit https://tensordock.com?utm_source=gpuperhour&utm_medium=referral to sign up. Both providers typically offer some form of free credits or trial period for new users. We recommend starting with a small experiment to evaluate the platform's ease of use, instance launch times, and overall fit for your workflow before committing to larger workloads.