Ollama Hosting, Deploy Your own AI Chatbot with Ollama

Ollama is a self-hosted AI solution to run open-source large language models, such as Gemma, Llama, Mistral, and other LLMs locally or on your own infrastructure. GPUMart provides a list of the best budget GPU servers for Ollama to ensure you can get the most out of this great application.

Choose Your Ollama Hosting Plans

GPUMart offers best budget GPU servers for Ollama. Cost-effective Ollama hosting is ideal to deploy your own AI Chatbot. Note: You should have at least 8 GB of VRAM (GPU Memory) available to run the 7B models, 16 GB to run the 13B models, 32 GB to run the 33B models, 64 GB to run the 70B models.

Lite GPU Dedicated Server - K620

49.00/mo
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  • 16GB RAM
  • Quad-Core Xeon E3-1270v3
  • 120GB + 960GB SSD
  • 100Mbps-1Gbps
  • OS: Windows / Linux
  • GPU: Nvidia Quadro K620
  • Microarchitecture: Maxwell
  • CUDA Cores: 384
  • GPU Memory: 2GB DDR3
  • FP32 Performance: 0.863 TFLOPS
  • Ideal for lightweight Android emulators, small LLMs, graphic processing, and more. Powerful than GPU VPS.

Basic GPU Dedicated Server - GTX 1660

139.00/mo
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  • 64GB RAM
  • Dual 10-Core Xeon E5-2660v2
  • 120GB + 960GB SSD
  • 100Mbps-1Gbps
  • OS: Windows / Linux
  • GPU: Nvidia GeForce GTX 1660
  • Microarchitecture: Turing
  • CUDA Cores: 1408
  • GPU Memory: 6GB GDDR6
  • FP32 Performance: 5.0 TFLOPS
Flash Sale to Mar.26

Professional GPU VPS - A4000

102.00/mo
43% OFF Recurring (Was $179.00)
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  • 32GB RAM
  • 24 CPU Cores
  • 320GB SSD
  • 300Mbps Unmetered Bandwidth
  • Once per 2 Weeks Backup
  • OS: Linux / Windows 10
  • 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.

Advanced GPU Dedicated Server - A5000

349.00/mo
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  • 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

Advanced GPU Dedicated Server - V100

229.00/mo
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  • 128GB RAM
  • Dual 12-Core E5-2690v3
  • 240GB SSD + 2TB SSD
  • 100Mbps-1Gbps
  • OS: Windows / Linux
  • GPU: Nvidia V100
  • Microarchitecture: Volta
  • CUDA Cores: 5,120
  • Tensor Cores: 640
  • GPU Memory: 16GB HBM2
  • FP32 Performance: 14 TFLOPS
  • Cost-effective for AI, deep learning, data visualization, HPC, etc

Enterprise GPU Dedicated Server - RTX 4090

409.00/mo
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  • 256GB RAM
  • Dual 18-Core E5-2697v4
  • 240GB SSD + 2TB NVMe + 8TB SATA
  • 100Mbps-1Gbps
  • OS: Windows / Linux
  • GPU: GeForce RTX 4090
  • Microarchitecture: Ada Lovelace
  • CUDA Cores: 16,384
  • Tensor Cores: 512
  • GPU Memory: 24 GB GDDR6X
  • FP32 Performance: 82.6 TFLOPS
  • Perfect for 3D rendering/modeling , CAD/ professional design, video editing, gaming, HPC, AI/deep learning.
Flash Sale to Mar.26

Enterprise GPU Dedicated Server - RTX A6000

357.00/mo
34% OFF Recurring (Was $409.00)
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  • 256GB RAM
  • Dual 18-Core E5-2697v4
  • 240GB SSD + 2TB NVMe + 8TB SATA
  • 100Mbps-1Gbps
  • 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
  • Optimally running AI, deep learning, data visualization, HPC, etc.
Flash Sale to Mar.26

Enterprise GPU Dedicated Server - A100

469.00/mo
41% OFF Recurring (Was $799.00)
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  • 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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  • 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

Multi-GPU Dedicated Server - 4xA100

1899.00/mo
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  • 512GB RAM
  • Dual 22-Core E5-2699v4
  • 240GB SSD + 4TB NVMe + 16TB SATA
  • 1Gbps
  • OS: Windows / Linux
  • GPU: 4 x Nvidia A100
  • Microarchitecture: Ampere
  • CUDA Cores: 6912
  • Tensor Cores: 432
  • GPU Memory: 40GB HBM2
  • FP32 Performance: 19.5 TFLOPS
New Arrival

Enterprise GPU Dedicated Server - A100(80GB)

1559.00/mo
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  • 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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  • 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

Popular LLMs and GPU Recommendations

If you're running models on the Ollama platform, selecting the right NVIDIA GPU is crucial for performance and cost-effectiveness.
Model NameParamsModel SizeRecommended GPU cards
DeepSeek R17B4.7GBGTX 1660 6GB or higher
DeepSeek R18B4.9GBGTX 1660 6GB or higher
DeepSeek R114B9.0GBRTX A4000 16GB or higher
DeepSeek R132B20GBRTX 4090, RTX A5000 24GB, A100 40GB
DeepSeek R170B43GBRTX A6000, A40 48GB
DeepSeek R1671B404GBNot supported yet
Deepseek-coder-v216B8.9GBRTX A4000 16GB or higher
Deepseek-coder-v2236B133GB2xA100 80GB, 4xA100 40GB
Qwen2.57B4.7GBGTX 1660 6GB or higher
Qwen2.514B9GBRTX A4000 16GB or higher
Qwen2.532B20GBRTX 4090 24GB, RTX A5000 24GB
Qwen2.572B47GBA100 80GB, H100
Qwen 2.5 Coder14B9.0GBRTX A4000 16GB or higher
Qwen 2.5 Coder32B20GBRTX 4090 24GB, RTX A5000 24GB or higher
Gemma 29B5.4GBRTX 3060 Ti 8GB or higher
Gemma 227B16GBRTX 4090, A5000 or higher
Phi-414B9.1GBRTX A4000 16GB or higher
Phi-314B7.9GBRTX A4000 16GB or higher
Llama 3.370B43GBA6000 48GB, A40 48GB, or higher
Llama 3.18B4.9GBGTX 1660 6GB or higher
Llama 3.170B43GBA6000 48GB, A40 48GB, or higher
Llama 3.1405B243GB4xA100 80GB, or higher
Mistral7B4.1GBGTX 1660 6GB or higher
Mixtral8x7B26GBA6000 48GB, A40 48GB, or higher
Mixtral8x22B80GB2xA6000, 2xA100 80GB, or higher

The Upcoming GPU Plans

We are currently stocking GPU servers featuring L4, RTX 6000 Ada, and L40s. If you're interested, please fill out the form below. We will prioritize progress based on the number of reservations.

Advanced GPU Server - L4

498.00/mo
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  • 128GB RAM
  • Dual E5-2697v2
  • 240GB + 2TB SSD
  • 100Mbps-1Gbps
  • OS: Linux
  • GPU: Nvidia L4

Enterprise GPU Server - RTX 6000 Ada

770.00/mo
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  • 256GB RAM
  • Dual E5-2697v2
  • 240GB + 2TB SSD + 8TB SATA
  • 100Mbps-1Gbps
  • OS: Linux
  • GPU: Nvidia RTX 6000 Ada

Enterprise GPU Server - L40S

830.00/mo
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  • 256GB RAM
  • Dual E5-2697v2
  • 240GB + 2TB SSD + 8TB SATA
  • 100Mbps-1Gbps
  • OS: Linux
  • GPU: Nvidia L40S
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The GPU server I need *

6 Reasons to Choose our Ollama Hosting

GPUMart enables powerful GPU hosting features on raw bare metal hardware, served on-demand. No more inefficiency, noisy neighbors, or complex pricing calculators.
Intel Xeon CPU

NVIDIA GPU

Rich Nvidia graphics card types, up to 48GB VRAM, powerful CUDA performance. There are also multi-card servers for you to choose from.
SSD-Based Drives

SSD-Based Drives

You can never go wrong with our own top-notch dedicated GPU servers for Ollama, loaded with the latest Intel Xeon processors, terabytes of SSD disk space, and up to 256 GB of RAM per server.
Full Root/Admin Access

Full Root/Admin Access

With full root/admin access, you will be able to take full control of your dedicated GPU servers for Ollama very easily and quickly.
99.9% Uptime Guarantee

99.9% Uptime Guarantee

With enterprise-class data centers and infrastructure, we provide a 99.9% uptime guarantee for Ollama hosting service.
Dedicated IP

Dedicated IP

One of the premium features is the dedicated IP address. Even the cheapest GPU hosting plan is fully packed with dedicated IPv4 & IPv6 Internet protocols.
24/7/365 Technical Support

24/7/365 Technical Support

GPUMart provides round-the-clock technical support to help you resolve any issues related to Ollama hosting.

Advantages of Ollama over ChatGPT

Ollama is an open-source platform that allows users to run large language models locally. It offers several advantages over ChatGPT
check_circleCustomization
Ollama enables users to create and customize their own models, which is not possible with ChatGPT, which is a closed product accessible only through an API provided by OpenAI.
check_circleEfficiency
Ollama is designed to be more efficient and less resource-intensive than other models, which means it requires less computational power to run. This makes it more accessible to users who may not have access to high-performance computing resources.
check_circleCost
As a self-hosted alternative to ChatGPT, Ollama is freely available, while ChatGPT may incur costs for certain versions or usage.
check_circleFlexibility
Ollama allows for running multiple models in parallel, providing customization and integration, which can be useful for tasks like autogen and other applications.
check_circleSecurity and Privacy
All components necessary for OLlama to operate, including the LLMs, are installed within your designated server. This ensures that your data remains secure and private, with no sharing or collection of information outside of your hosting environment.
check_circleSimplicity and Accessibility
Ollama is renowned for its straightforward setup process, making it accessible even to those with limited technical expertise in machine learning. This ease of use opens up opportunities for a wider range of users to experiment with and leverage LLMs.

Key Features of Ollama

Ollama's ease of use, flexibility, and powerful LLMs make it accessible to a wide range of users.

Ease of Use

Ollama’s simple API makes it straightforward to load, run, and interact with LLMs. You can quickly get started with basic tasks without extensive coding knowledge.

Flexibility

Ollama offers a versatile platform for exploring various applications of LLMs. You can use it for text generation, language translation, creative writing, and more.

Powerful LLMs

Ollama includes pre-trained LLMs like Llama 2, renowned for its large size and capabilities. It also supports training custom LLMs tailored to your specific needs.

Community Support

Ollama actively participates in the LLM community, providing documentation, tutorials, and open-source code to facilitate collaboration and knowledge sharing.

How to Run LLMs Locally with Ollama AI

Deploy Ollama on bare-metal server with a dedicated GPU or Multi-GPU in 10 minutes. We will go through How to Install and Use Ollama AI on Linux step-by-step.
step1
Order and Login GPU Server
step2
Install Ollama AI
step3
Download a LLM Model
step4
Chat with the Model

FAQs of Ollama Hosting

The most commonly asked questions about Ollama hosting service below.

What is Ollama?

Ollama is a platform designed to run open-source large language models (LLMs) locally on your machine. It supports a variety of models, including Llama 2, Code Llama, and others, and it bundles model weights, configuration, and data into a single package, defined by a Modelfile. Ollama is an extensible platform that enables the creation, import, and use of custom or pre-existing language models for a variety of applications.

What Nvidia GPUs are good for running Ollama?

Ollama supports Nvidia GPUs with compute capability 5.0+. Check your compute compatibility to see if your card is supported: https://developer.nvidia.com/cuda-gpus.
Examples of minimum supported cards for each series: Quadro K620/P600, Tesla P100, GeForce GTX 1650, Nvidia V100, RTX 4000.

Where can I find the Ollama GitHub repository?

The Ollama GitHub repository is the hub for all things related to Ollama. You can find source code, documentation, and community discussions by searching for Ollama on GitHub or following this link (https://github.com/ollama/ollama).

How do I use the Ollama Docker image?

Using the Ollama Docker image (https://hub.docker.com/r/ollama/ollama) is a straightforward process. Once you've installed Docker, you can pull the Ollama image and run it using simple shell commands. Detailed steps can be found in Section 2 of this article.

Is Ollama compatible with Windows?

Yes, Ollama offers cross-platform support, including Windows 10 or later. You can download the Windows executable from Ollama download page (https://ollama.com/download/windows) or the GitHub repository and follow the installation instructions.

Can Ollama leverage GPU for better performance?

Yes, Ollama can utilize GPU acceleration to speed up model inference. This is particularly useful for computationally intensive tasks.

What is Ollama-UI and how does it enhance the user experience?

Ollama-UI is a graphical user interface that makes it even easier to manage your local language models. It offers a user-friendly way to run, stop, and manage models. Ollama has many good open source chat UIs, such as chatbot UI, Open WebUI, etc.

How does Ollama integrate with LangChain?

Ollama and LangChain can be used together to create powerful language model applications. LangChain provides the language models, while Ollama offers the platform to run them locally.