Text Generation
Pre-installed Gemma3-27B LLM Hosting
Advanced Dedicated GPU Server - RTX A5000
- GPU Model: RTX A5000
- CPU: 24-Core Dual E5-2697v2
- Memory: 128GB RAM
- Disk: 240GB SSD+2TB SSD
- Bandwidth: 100Mbps Unmetered
- GPU Memory: 24 GB GDDR6
- IP: 1 Dedicated IPv4
- Location: USA
Advanced GPU VPS - RTX Pro 4000
- GPU Model: RTX Pro 4000
- CPU: 24 CPU Cores
- Memory: 56GB RAM
- Disk: 320GB SSD
- Bandwidth: 500Mbps Unmetered
- GPU Memory: 24 GB GDDR7
- IP: 1 Dedicated IPv4
- Location: USA
- Backup: Once per 2 Weeks
Enterprise Dedicated GPU Server - RTX 4090
- GPU Model: RTX 4090
- CPU: 36-Core Dual E5-2697v4
- Memory: 256GB RAM
- Disk: 240GB SSD+2TB NVMe+8TB SATA
- Bandwidth: 100Mbps Unmetered
- GPU Memory: 24 GB GDDR6X
- IP: 1 Dedicated IPv4
- Location: USA
Advanced GPU VPS - RTX Pro 5000
- GPU Model: RTX Pro 5000
- CPU: 24 CPU Cores
- Memory: 56GB RAM
- Disk: 320GB SSD
- Bandwidth: 500Mbps Unmetered
- GPU Memory: 48 GB GDDR7
- IP: 1 Dedicated IPv4
- Location: USA
- Backup: Once per 2 Weeks
Advanced GPU VPS - RTX 5090
- GPU Model: RTX 5090
- CPU: 32 CPU Cores
- Memory: 84GB RAM
- Disk: 400GB SSD
- Bandwidth: 500Mbps Unmetered
- GPU Memory: 32 GB GDDR7
- IP: 1 Dedicated IPv4
- Location: USA
- Backup: Once per 2 Weeks
Enterprise Dedicated GPU Server - A100
- GPU Model: A100
- CPU: 36-Core Dual E5-2697v4
- Memory: 256GB RAM
- Disk: 240GB SSD+2TB NVMe+8TB SATA
- Bandwidth: 100Mbps Unmetered
- GPU Memory: 40 GB HBM2
- IP: 1 Dedicated IPv4
- Location: USA
Rent other GPU Servers for Gemma-3 Hosting
Basic Dedicated GPU Server - GTX 1650
- GPU Model: GTX 1650
- CPU: 8-Core Xeon E5-2667v3
- Memory: 64GB RAM
- Disk: 120GB SSD + 960GB SSD
- Bandwidth: 100Mbps Unmetered
- GPU Memory: 4 GB GDDR5
- IP: 1 Dedicated IPv4
- Location: USA
Advanced Dedicated GPU Server - RTX 3060 Ti
- GPU Model: RTX 3060 Ti
- CPU: 24-Core Dual E5-2697v2
- Memory: 128GB RAM
- Disk: 240GB SSD+2TB SSD
- Bandwidth: 100Mbps Unmetered
- GPU Memory: 8 GB GDDR6
- IP: 1 Dedicated IPv4
- Location: USA
Professional GPU VPS - RTX A4000
- GPU Model: RTX A4000
- CPU: 24 CPU Cores
- Memory: 28GB RAM
- Disk: 320GB SSD
- Bandwidth: 300Mbps Unmetered
- GPU Memory: 16 GB GDDR6
- IP: 1 Dedicated IPv4
- Location: USA
- Backup: Once per 2 Weeks
Enterprise Dedicated GPU Server - RTX A6000
- GPU Model: RTX A6000
- CPU: 36-Core Dual E5-2697v4
- Memory: 256GB RAM
- Disk: 240GB SSD+2TB NVMe+8TB SATA
- Bandwidth: 100Mbps Unmetered
- GPU Memory: 48 GB GDDR6
- IP: 1 Dedicated IPv4
- Location: USA
Gemma-3-27B Benchmark Performance
What is Google Gemma 3 Good For?
Chatbots and Conversational AI
Text Summarization
Language Learning Tools
Natural Language Processing (NLP) Research
Knowledge Exploration
How to Run Gemma 3 LLMs with Ollama
Sample - Run Gemma-3 with Ollama Command line
This model requires Ollama 0.6 or later.
# install Ollama on Linux
curl -fsSL https://ollama.com/install.sh | shText only - 1B parameter model (32k context window)
ollama run gemma3:1bMultimodal (Vision) - 4B parameter model (128k context window)
ollama run gemma3:4b 12B parameter model (128k context window)
ollama run gemma3:12b27B parameter model (128k context window)
ollama run gemma3:27bNote: Here is a table summarizing the key parameters of Google's Gemma 3 models, along with their approximate VRAM requirements when running 4-bit quantized versions (Q4_0) using Ollama:
| Model Size | Parameters | Download Size | VRAM Required (4-bit QAT) | Notes |
|---|---|---|---|---|
| 1B | 1 Billion | ~1 GB | 1~ GB | Suitable for low-end GPUs like GTX 1650 4GB. |
| 4B | 4 Billion | ~4 GB | 4~ GB | Runs efficiently on GPUs with 4–8GB VRAM. |
| 12B | 12 Billion | ~8.9 GB | 12~ GB | Optimal performance on GPUs with ≥16GB VRAM. |
| 27B | 27 Billion | ~18 GB | 24~ GB | Requires GPUs with ≥24GB VRAM |
