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Gemma 3 Hosting, Host Gemma-3 with Ollama or vLLM
Google's latest model, Gemma 3, is open-source and highly efficient. It's the most powerful model that can run on a single GPU!
Choose Your Gemma-3 Hosting Plans
GPU Mart offers best budget GPU servers for Gemma 3 1b/4b/12b/27b. Cost-effective dedicated GPU servers are ideal for hosting your own Gemma-3 LLMs online.
Flash Sale to June 16
Professional GPU VPS - A4000
$ 99.00/mo
44% OFF Recurring (Was $179.00)
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Order Now- 32GB RAM
- 24 CPU Cores
- 320GB SSD
- 300Mbps Unmetered Bandwidth
- Once per 2 Weeks Backup
- OS: Linux / Windows 10/ Windows 11
- Dedicated GPU: Quadro RTX A4000
- CUDA Cores: 6,144
- Tensor Cores: 192
- GPU Memory: 16GB GDDR6
- FP32 Performance: 19.2 TFLOPS
- Available for Rendering, AI/Deep Learning, Data Science, CAD/CGI/DCC.
Half-Year Pay, Full-Year Deal
Advanced GPU Dedicated Server - A5000
$ 191.90/mo
45% OFF Recurring (Was $349.00)
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Order Now- 128GB RAM
- Dual 12-Core E5-2697v2
- 240GB SSD + 2TB SSD
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia Quadro RTX A5000
- Microarchitecture: Ampere
- CUDA Cores: 8192
- Tensor Cores: 256
- GPU Memory: 24GB GDDR6
- FP32 Performance: 27.8 TFLOPS
Enterprise GPU Dedicated Server - RTX A6000
$ 409.00/mo
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Order Now- 256GB RAM
- Dual 18-Core E5-2697v4
- 240GB SSD + 2TB NVMe + 8TB SATA
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- OS: Windows / Linux
- GPU: Nvidia Quadro RTX A6000
- Microarchitecture: Ampere
- CUDA Cores: 10,752
- Tensor Cores: 336
- GPU Memory: 48GB GDDR6
- FP32 Performance: 38.71 TFLOPS
Enterprise GPU Dedicated Server - RTX 4090
$ 409.00/mo
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Order Now- 256GB RAM
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- GPU: GeForce RTX 4090
- Microarchitecture: Ada Lovelace
- CUDA Cores: 16,384
- Tensor Cores: 512
- GPU Memory: 24 GB GDDR6X
- FP32 Performance: 82.6 TFLOPS
Enterprise GPU Dedicated Server - A100
$ 639.00/mo
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Order Now- 256GB RAM
- Dual 18-Core E5-2697v4
- 240GB SSD + 2TB NVMe + 8TB SATA
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia A100
- Microarchitecture: Ampere
- CUDA Cores: 6912
- Tensor Cores: 432
- GPU Memory: 40GB HBM2
- FP32 Performance: 19.5 TFLOPS
- Good alternativeto A800, H100, H800, L40. Support FP64 precision computation, large-scale inference/AI training/ML.etc
Multi-GPU Dedicated Server - 2xA100
$ 1099.00/mo
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Order Now- 256GB RAM
- Dual 18-Core E5-2697v4
- 240GB SSD + 2TB NVMe + 8TB SATA
- 1Gbps
- OS: Windows / Linux
- GPU: Nvidia A100
- Microarchitecture: Ampere
- CUDA Cores: 6912
- Tensor Cores: 432
- GPU Memory: 40GB HBM2
- FP32 Performance: 19.5 TFLOPS
- Free NVLink Included
- A Powerful Dual-GPU Solution for Demanding AI Workloads, Large-Scale Inference, ML Training.etc. A cost-effective alternative to A100 80GB and H100, delivering exceptional performance at a competitive price.
New Arrival
Enterprise GPU Dedicated Server - A100(80GB)
$ 1559.00/mo
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Order Now- 256GB RAM
- Dual 18-Core E5-2697v4
- 240GB SSD + 2TB NVMe + 8TB SATA
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia A100
- Microarchitecture: Ampere
- CUDA Cores: 6912
- Tensor Cores: 432
- GPU Memory: 80GB HBM2e
- FP32 Performance: 19.5 TFLOPS
Enterprise GPU Dedicated Server - H100
$ 2099.00/mo
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Order Now- 256GB RAM
- Dual 18-Core E5-2697v4
- 240GB SSD + 2TB NVMe + 8TB SATA
- 100Mbps-1Gbps
- OS: Windows / Linux
- GPU: Nvidia H100
- Microarchitecture: Hopper
- CUDA Cores: 14,592
- Tensor Cores: 456
- GPU Memory: 80GB HBM2e
- FP32 Performance: 183TFLOPS
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Gemma-3-27B Benchmark Performance
With just 27B parameters, Gemma-3 easily outperforms the 671B full-power DeepSeek V3, o3-mini, and Llama-405B, ranking second only to DeepSeek-R1.
Key Features of Gemma 3
The most powerful model that can run on a single GPU is here! Google's latest model, Gemma 3, is open-source and highly efficient.
Gemma 3 includes the following key features:
Image and Text Input: With multimodal capabilities, you can input both images and text to understand and analyze visual data.
128K Token Context: The input context has been expanded 16 times, enabling the analysis of more data and the solving of more complex problems.
Extensive Language Support: Supports over 140 languages, allowing you to operate in your preferred language or expand the linguistic capabilities of your AI applications.
Developer-Friendly Model Sizes: Choose the model size (1B, 4B, 12B, 27B) and precision level that best fit your task and computing resources.
How to Run Gemma-3 with Ollama or vLLM
VLLM is an optimized inference engine that delivers high-speed token generation and efficient memory management, making it ideal for large-scale AI applications. Ollama is a lightweight and user-friendly framework that simplifies running open-source LLMs on local machines. Make a selection based on your needs.
Install Ollama or vLLM
Run Gemma-3 with Ollama or vLLM
Chat with Gemma-3
Sample 1 - 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 | sh
Text only - 1B parameter model (32k context window)
ollama run gemma3:1b
Multimodal (Vision) - 4B parameter model (128k context window)
ollama run gemma3:4b
12B parameter model (128k context window)
ollama run gemma3:12b
27B parameter model (128k context window)
ollama run gemma3:27b
Screenshot: The image shows a terminal session running the Ollama framework with the Gemma 3:27B model on an NVIDIA RTX A5000 GPU.
Sample 2 - Run Gemma-3 with vLLM
By default, vLLM uses the model file on HuggingFace, using Tensor type BF16, which is 4 times the size of the 4-bit quantization in the Ollama library. So we need to use a GPU card with more memory.
# Prerequirements # A100 80GB or H100 GPU Dedicated Server uv pip install vllm vllm serve google/gemma-3-27b-it --max-model-len 131072
FAQs of Gemma-3 Hosting
Here are some Frequently Asked Questions about Google Gemma 3 LLMs.
What is Gemma 3?
Gemma is a lightweight, family of models from Google built on Gemini technology. The Gemma 3 models are multimodal—processing text and images—and feature a 128K context window with support for over 140 languages. Available in 1B, 4B, 12B, and 27B parameter sizes, they excel in tasks like question answering, summarization, and reasoning, while their compact design allows deployment on resource-limited devices.
Who can use Gemma?
Gemma is a class of generative artificial intelligence (AI) models that can be used for various generative tasks, including question answering, summarization, and reasoning. Gemma models provide open weights and allow responsible commercial use, enabling you to fine-tune and deploy them in your own projects and applications.
How can I deploy Gemma-3?
Gemma-3 can be deployed via Ollama, vLLM, or on-premise solutions.