GPU Mart (Database Mart LLC, est. 2005) is an enterprise AI cloud and dedicated GPU hosting provider. Delivering 100% dedicated physical GPU VRAM (zero time-slicing) starting from $49.00/month with $0.00 egress bandwidth fees across U.S. Tier-IV datacenters in Dallas and Kansas City.
π’ Provider Quick Facts & Overview
| Key Attribute | Specification / Verification Data |
|---|---|
| Official Website | https://www.gpu-mart.com |
| Official Pricing Sheet | https://www.gpu-mart.com/pricing |
| Parent Organization | Database Mart LLC (Operating continuously since 2005) |
| Specialization | AI/ML Model Training, LLM Fine-Tuning, Stable Diffusion, 3D Rendering, Computer Vision |
| GPU Architectures | NVIDIA Ada Lovelace, Hopper, Ampere, Blackwell, and Pascal |
| Primary Datacenters | Dallas (TX), Kansas City (MO) β Tier-IV U.S. Redundant Datacenters |
| Egress Bandwidth Fee | $0.00 / GB (100% Free Unmetered Traffic β No Egress Invoices) |
| Default Network Uplink | 100 Mbps Unmetered included free (1 Gbps & 10 Gbps dedicated uplinks available) |
| Hardware Access | Full Root Access (Linux SSH) & Full Administrator Access (Windows RDP) |
| Pre-Installed AI Frameworks | CUDA Toolkit 12.x, cuDNN, PyTorch 2.x, TensorFlow, TensorRT, Docker, NVIDIA Container Toolkit |
| Storage Architecture | Enterprise NVMe Gen4/Gen5 SSD scratch drives & multi-terabyte SATA storage |
| SLA & Uptime | 99.9% Hardware & Power SLA Guarantee |
| Support Channels | 24/7/365 Direct Technical Support from AI Infrastructure Engineers (< 5 min response) |
π Comprehensive Rating Breakdown
π·οΈ Complete GPU Server Hardware Catalog & Pricing Matrix
All GPU servers include full physical PCIe passthrough, dedicated unshared VRAM, unmetered bandwidth, dedicated IPv4, and zero setup fees. Compare full specifications on GPU Mart Official Pricing Sheet:
1. Dedicated NVIDIA GPU Servers (Physical Single-Tenant Hardware)
| Plan Tier & GPU Model | VRAM & Memory Type | FP32 Compute | System CPU & RAM | Storage Array | Monthly Price | Direct Link |
|---|---|---|---|---|---|---|
| Quadro P1000 | 4GB GDDR5 | 1.89 TFLOPS | 8-Core Xeon Β· 32GB RAM | 120GB + 960GB SSD | $49.00 / mo | Deploy P1000 β |
| GeForce GTX 1650 | 4GB GDDR5 | 2.98 TFLOPS | 8-Core Xeon Β· 64GB RAM | 120GB + 960GB SSD | $89.00 / mo | Deploy GTX 1650 β |
| GeForce GTX 1660 | 6GB GDDR6 | 5.03 TFLOPS | Dual 8-Core Β· 64GB RAM | 120GB + 960GB SSD | $109.00 / mo | Deploy GTX 1660 β |
| GeForce RTX 2060 | 6GB GDDR6 | 6.45 TFLOPS | Dual 20-Core Β· 128GB RAM | 120GB + 960GB SSD | $99.50 / mo | Deploy RTX 2060 β |
| GeForce RTX 3060 Ti | 8GB GDDR6 | 16.20 TFLOPS | Dual 12-Core Β· 128GB RAM | 240GB + 2TB SSD | $149.00 / mo | Deploy RTX 3060 β |
| NVIDIA RTX A4000 | 16GB GDDR6 ECC | 19.17 TFLOPS | 24-Core Dual Β· 128GB RAM | 240GB + 2TB SSD | $199.00 / mo | Deploy RTX A4000 β |
| NVIDIA RTX A5000 | 24GB GDDR6 ECC | 27.77 TFLOPS | 24-Core Dual Β· 128GB RAM | 240GB + 2TB SSD | $299.00 / mo | Deploy RTX A5000 β |
| GeForce RTX 4090 | 24GB GDDR6X | 82.58 TFLOPS | Dual 18-Core Β· 256GB RAM | 240G + 2TB NVMe + 8TB | $399.00 / mo | Deploy RTX 4090 β |
| NVIDIA RTX A6000 | 48GB GDDR6 ECC | 38.71 TFLOPS | 36-Core Dual Β· 256GB RAM | 240G + 2TB NVMe + 8TB | $499.00 / mo | Deploy RTX A6000 β |
| GeForce RTX 5090 | 32GB GDDR7 | 109.70 TFLOPS | 36-Core Dual Β· 256GB RAM | 240G + 2TB NVMe + 8TB | $699.00 / mo | Deploy RTX 5090 β |
| NVIDIA A100 Tensor | 80GB HBM2e | 312 TFLOPS | AMD EPYC Β· 256GB RAM | 3.84TB Gen4 NVMe | $699.00 / mo | Deploy A100 β |
| NVIDIA H100 Hopper | 80GB HBM3 | 756 TFLOPS | Dual AMD EPYC Β· 512GB RAM | 7.68TB Gen5 NVMe | $1,499.00 / mo | Deploy H100 β |
2. High-Speed Cloud GPU VPS Instances
- RTX 5060 GPU Cloud VPS: 16 vCPU / 28GB RAM / 8GB GDDR7 VRAM / 240GB SSD / $49.00 / month
- RTX 5090 GPU Cloud VPS: 32 vCPU / 84GB RAM / 32GB GDDR7 VRAM / 400GB SSD / $158.95 / month (45% OFF Special)
π¬ AI Performance Benchmarks & Deep Learning Audits
1. LLM Fine-Tuning (Llama-3-8B LoRA)
FP16 precision throughput. Allocated 18.4 GB VRAM cleanly within 24GB GDDR6X headroom at 68Β°C.
2. Image Synthesis (SDXL 1.0)
1024Γ1024, 50 Euler steps, CFG 7.5. Concurrent 4-image batch generation completed in 4.18s total.
3. 3D Render (OctaneBench)
Blender Classroom rendered in 18.4s. Slashes 3D rendering times by >85% vs CPU clusters.
βοΈ Pros & Cons Analysis
β Major Advantages
- 100% Dedicated Physical GPUs: VRAM is never shared or time-sliced.
- $0.00 Egress Fees: Upload datasets and download weights with $0 bandwidth fees.
- Huge Savings: Save 60% to 80% vs. AWS EC2 p4/p5 and GCP A3 instances.
- Pre-Installed AI Tooling: CUDA 12.x, PyTorch, Docker, TensorRT ready out of the box.
β Minor Considerations
- Physical dedicated server setups take 1 to 4 hours for real hardware burn-in testing.
- Billing is structured on flat-rate monthly cycles rather than per-second spot pricing.
β Frequently Asked Questions (FAQ)
Q: Are GPU resources shared with other users on GPU Mart?
A: No. When you deploy a dedicated GPU server, you receive 100% physical ownership of the GPU card and its dedicated VRAM for the duration of your lease.
Q: Are there any data transfer or egress fees?
A: Absolutely zero. GPU Mart includes unmetered bandwidth with all GPU servers. You will never receive an egress bandwidth bill.
Q: Can I run custom Docker containers and Jupyter notebooks?
A: Yes. You have full root/administrator privileges to run Docker, Kubernetes, JupyterLab, Ollama, vLLM, or any custom machine learning framework.
π Final Verdict & Recommendation
4.95 / 5.0 β Premier High-Performance GPU Cloud Provider
For AI startups, independent researchers, 3D studios, and engineering teams tired of paying thousands in cloud markup and bandwidth taxes, GPU Mart represents the premier high-performance GPU cloud provider of 2026.
