Deploy & Scale Gemma AI Models on High-Performance GPU
Run, Fine-Tune & Serve Gemma LLMs with Dedicated Infrastructure and Ultra-Fast Inference Performance.
60GB RAM | 24 CPU Cores | 320GB SSD |
500Mbps Unmetered Bandwidth |
-
Windows / Linux |
Once per 2 Weeks Backup | OS -
Nvidia RTX Pro 4000 |
Dedicated GPU -
8,960 | Tensor Cores: 280 |
CUDA Cores -
24GB GDDR7 | FP32 Performance: 34 TFLOPS
GPU Memory
60GB RAM | 24 CPU Cores | 320GB SSD |
500Mbps Unmetered Bandwidth |
Once per 2 Weeks Backup |
-
Windows / Linux |
OS -
Nvidia RTX Pro 5000 |
Dedicated GPU -
14,080 | Tensor Cores: 440 |
CUDA Cores -
48GB GDDR7 |
GPU Memory -
66.94 TFLOPS
FP32 Performance
90GB RAM | 32 CPU Cores | 400GB SSD |
500Mbps Unmetered Bandwidth |
Once per 2 Weeks Backup |
-
Windows / Linux | Dedicated GPU: GeForce RTX 5090 |
OS -
21,760 | Tensor Cores: 680 |
CUDA Cores -
32GB GDDR7 | FP32 Performance: 109.7 TFLOPS
GPU Memory
Dual 12-Core E5-2697v2 |
240GB SSD + 2TB SSD |
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Nvidia Quadro RTX A5000 |
128GB RAM | GPU -
Windows / Linux |
100Mbps-1Gbps | OS -
Ampere | CUDA Cores: 8,192 |
Microarchitecture -
256 | GPU Memory: 24GB GDDR6 |
Tensor Cores -
27.8 TFLOPS
FP32 Performance
