Marketplace GPU cloud with industry-leading pricing. No waitlists, quotas, or price gouging. Pay-per-second billing starting from $5 deposit. 100+ locations across 20+ countries. 30,000+ GPUs available including 45 different models. 99.99% uptime standard.
| Name | tensordock |
| Total Instances | 10 |
| Minimum Price | $0.12/hr |
| Maximum VRAM | 80 GB |
| Available GPU Models |
Marketplace GPU cloud with industry-leading pricing. No waitlists, quotas, or price gouging. Pay-per-second billing starting from $5 deposit. 100+ locations across 20+ countries. 30,000+ GPUs available including 45 different models. 99.99% uptime standard.
Ready to rent GPUs from tensordock? Sign up now to explore available instances and start your AI workloads.
Visit Provider Website →North America, Europe, Asia, Oceania, United States, Canada, Germany, United Kingdom, France, Netherlands, Singapore, Japan, Australia
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Pay-per-second GPU cloud with no waitlists
| Accelerator | Price/Hour | VRAM | Type | Action |
|---|---|---|---|---|
| H100 | $2.27 | 80 GB | GPU | View GPU → |
| A800 80GB | $1.81 | 80 GB | GPU | View GPU → |
| A800 80GB | $1.51 | 80 GB | GPU | View GPU → |
| Tesla V100 | $0.18 | 16 GB | GPU | View GPU → |
| L40S | $0.96 | 48 GB | GPU | View GPU → |
| RTX 4090 | $0.36 | 24 GB | GPU | View GPU → |
| RTX 3090 | $0.21 | 24 GB | GPU | View GPU → |
| RTX 6000 Ada | $0.77 | 48 GB | GPU | View GPU → |
| A6000 | $0.47 | 48 GB | GPU | View GPU → |
| RTX A4000 | $0.12 | 16 GB | GPU | View GPU → |
Explore GPU specifications and compare pricing for tensordock
Explore alternative GPU cloud providers and compare pricing
Check CUDA compute capability and AI feature support for different GPUs
View Reference →GPUvec currently tracks 10 tensordock instance configurations across 9 GPU models. The lowest observed rate in the dataset is $0.12/hour; the final price can vary by region, GPU count, host configuration, and billing terms.
The recorded catalog includes A6000, A800 80GB, H100, L40S, RTX 3090. GPUvec has location data for 13 regions: North America, Europe, Asia, Oceania, United States.
When evaluating tensordock, compare memory capacity, accelerator generation, hourly rate, regional availability, billing granularity, storage, and network requirements. Framework support also depends on the selected image and driver stack, so verify CUDA and container versions before migration.
Use GPUvec's provider directory and GPU comparison tool to compare tensordock with alternatives on the same accelerator model. A like-for-like comparison avoids misleading conclusions caused by different GPU counts, CPUs, RAM allocations, or commitment terms.
Learn more about GPUs from these authoritative sources:
Official CUDA programming guide
NVIDIA GPU Specifications →Official NVIDIA GPU specs
TechPowerUp GPU Database →Comprehensive GPU specifications
CUDA Compute Capability Guide →GPU compute capability reference
Visit tensordock's website to create an account and start using their GPU instances.
Visit tensordock →Get detailed information about tensordock's GPU cloud offerings, including available GPU models like RTX 4090, H100, A100, and L40S instances. Compare pricing structures, regional availability, and unique features that distinguish tensordock from other providers. Whether you need per-second billing, reserved instances, or spot pricing, understanding each provider's model helps you optimize your GPU spending.
Review the pricing structure for tensordock's GPU instances and compare hourly rates across different GPU models. GPUvec provides transparent pricing data so you can evaluate whether tensordock offers competitive rates for your AI training, inference, or rendering workloads compared to alternatives like RunPod, Vast.ai, or Lambda Labs.
See how tensordock stacks up against other GPU cloud providers in terms of pricing, GPU availability, geographic coverage, and unique features. Our detailed comparison helps you choose the best provider for your specific needs, whether you prioritize the lowest price per hour for RTX 4090 instances or the most reliable H100 availability for production workloads.