
TensorDock – Easy & Affordable Cloud GPUs
TensorDock is a global GPU cloud marketplace offering affordable, on-demand access to a wide range of GPUs for AI, machine learning, rendering, and cloud gaming. It connects users with vetted, high-uptime hardware providers in 100+ locations, delivering enterprise-ready reliability and up to 80% low
TensorDock
"Easy & Affordable Cloud GPUs"
Typical plan: $108 / month

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Comparing 4 AI tools.
| Feature | ||||
|---|---|---|---|---|
Upvotes | 3 | 83 | 103 | 82 |
Avg. Rating | 4.0 | 4.0 | 4.0 | 4.0 |
Slogan | Easy & Affordable Cloud GPUs | Quality data. From real people. For faster breakthroughs. | The Data and AI Company | Build, train, and deploy custom ML and generative AI models on Google Cloud—no expertise required. |
Category | ||||
Pricing Model | Subscription Pay-per-Use Contact for Pricing | Pay-per-Use Contact for Pricing | Free Pay-per-Use Contact for Pricing Enterprise | Freemium Pay-per-Use Enterprise Contact for Pricing |
Monthly Pricing (USD) | $72 – $1,620 / month Min$72 / month Mid$108 / month Max$1,620 / month | N/A | N/A | N/A |
Pricing Details | Pay-per-use billed per second with GPU hourly rates from $0.10/hr to $2.25/hr. Monthly plans available for long-term use; contact required for subscription pricing. | No subscription fees. Researchers pay per study: at least $8/hour participant pay (recommended $12/hour)+platform fee (33.3% academic/non-profit, 42.8% corporate). Managed services are contact for pricing. No free or freemium tier. | Databricks pricing is primarily pay-per-use, metered in Databricks Units (DBUs), which vary by cloud provider, compute type, region, and product tier (Standard, Premium, Enterprise). Standard is being phased out for AWS/GCP. A free 14-day trial is offered. Significant discounts or custom pricing are available through direct sales and committed contracts ('Contact for Pricing', 'Enterprise'). No new subscription or freemium models identified as of 2025. | Free tier with $300 credits. Pay-per-use: AutoML model training from $3.465/node hour, deployment from $1.375/node hour, custom model training from $0.218/hour. Imagen from $0.0001/image. Gemini generative models from $1.25/million input tokens. Some advanced/enterprise features 'Contact for Pricing'. All amounts in USD. |
Platforms | ||||
Target Audience | Scientists, Software Developers, Entrepreneurs, AI Enthusiasts | Scientists, Students, Educators, AI Enthusiasts, Software Developers, Marketing Professionals, Product Managers, Entrepreneurs | Software Developers, Scientists, Business Executives, Entrepreneurs | Software Developers, Scientists, Entrepreneurs, Educators, Students, Business Executives, AI Enthusiasts, Product Managers |
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Make the Most of TensorDock
Use this page as a starting point to evaluate TensorDock alongside similar options. Our directory focuses on practical details that matter for adoption—capabilities, pricing signals, integrations, and real audiences—so you can shortlist with confidence and move from exploration to evaluation faster.
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Before adopting any tool, model your total cost at expected usage, verify integration coverage and API quality, and review privacy, security, and compliance. A short pilot on a real workflow will reveal reliability and fit quickly. Bookmark this site to track updates to TensorDock and the broader ecosystem over time.
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User Reviews
Based on 1 review
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All Reviews (1)
Elliot Warren
25 days ago
Reliable, affordable, and fast-marketplace quirks included
TensorDock stands out for how quickly I can spin up GPU instances-I've timed launches under 30 seconds several times, which is way faster than when I used AWS for similar tasks. The pricing is another highlight; being able to grab an RTX 4090 for about $0.35/hr is nuts compared to what I used to pay elsewhere. Actually, I started testing TensorDock for machine learning projects about a month ago, trying out their API and web dashboard. One thing that caught me off guard: sometimes, the host quality varies (think Airbnb for GPUs), so I had to switch regions when a job acted up. But the marketplace model means tons of choice, flexible scaling, and no annoying quotas. Documentation could use some love, and the UI isn't as slick as the big clouds. Still, for the price, performance, and flexibility, it's seriously worth considering if you're tired of cloud sticker shock.
How TensorDock Works
Usage-based pricing keeps TensorDock aligned with actual consumption. Finance teams pay only for the outcomes the organization really uses. Integrations with Plugin/Integration keep work connected.
Key Features & Capabilities
Device-agnostic access
Runs on Web App, CLI Tool, and API so teams stay productive on their preferred devices. Available across Web App, CLI Tool, and API for consistent adoption.
Developer-friendly API
Rate limits and authentication are clearly documented for smooth implementation. Automation handles the repetitive work so teams can focus on strategy.
Client libraries available
Developers get client libraries that smooth integration work.
Automation-first workflows
TensorDock coordinates processes across teams so automation handles repetitive tasks. Automation handles the repetitive work so teams can focus on strategy.
Built for regulated teams
Security tooling ensures deployments stay within policy while innovation continues. Security controls, permissions, and logging keep sensitive data protected.
Common Use Cases
ScientistsAccelerate development
Engineering keeps ownership of customization while leveraging managed AI capabilities. Automation handles the repetitive work so teams can focus on strategy.
ScientistsAutomate repeatable work
Bots, rules, and triggers ensure nothing gets stuck in manual queues. Automation handles the repetitive work so teams can focus on strategy.
ScientistsSecure deployments
Security teams monitor access, compliance, and audit trails inside TensorDock. Security controls, permissions, and logging keep sensitive data protected.
Pricing & Plans
Pay-per-use billed per second with GPU hourly rates from $0.10/hr to $2.25/hr. Monthly plans available for long-term use; contact required for subscription pricing.
Usage Model: API Calls, Pay-as-You-Go — ensuring you only pay for what you actually use.
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Frequently Asked Questions about TensorDock
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