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


  • 16GB RAM
  • Quad-Core Xeon E3-1270v3
        (4 Cores & 8 Threads
  • 120GB + 960GB SSD
  • 100Mbps-1Gbps





  • OS: Windows / Linux
    GPU: Nvidia Quadro K620

  • Microarchitecture: Maxwell
  • CUDA Cores: 384
  • GPU Memory: 2GB GDDR3
  • 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

  • 64GB RAM
  • Dual 10-Core Xeon E5-2660v2
        (20 Cores & 40 Threads
  • 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








  • Professional GPU VPS - A4000


  • 32GB RAM
  • 24 CPU Cores
  • 320GB SSD
  • 300Mbps Unmetered
         Bandwidth



  • Once per 2 Weeks Backup
    OS: Linux / Windows 10/ Windows 11
    GPU: GeForce RTX 3060 Ti

  • 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

  • 128GB RAM
  • Dual 12-Core E5-2697v2
         24 Cores & 48 Threads
  • 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

  • 128GB RAM
  • Dual 12-Core E5-2690v3
        (24 Cores & 48 Threads)
  • 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

  • 256GB RAM
  • Dual 18-Core E5-2697v4
        36 Cores & 72 Threads
  • 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: 24GB GDDR6X
  • FP32 Performance: 86.2 TFLOPS




  • Perfect for 3D rendering/modeling , CAD/ professional design, video editing, gaming, HPC, AI/deep learning.

    Enterprise GPU Dedicated Server - RTX A6000

  • 256GB RAM
  • Dual 18-Core E5-2697v4
        (36 Cores & 72 Threads
  • 240GB SSD + 2TB NVMe + 8TB
        SATA
  • 100Mbps-1Gbps



  • OS: Windows / Linux
    GPU: Nvidia Quadro RTX A6000

  • Microarchitecture: Ampere
  • CUDA Cores: 10,752/li>
  • Tensor Cores: 336
  • GPU Memory: 48GB GDDR6
  • FP32 Performance: 38.71
        TFLOPS





  • Optimally running AI, deep learning, data visualization, HPC, etc.

    Enterprise GPU Dedicated Server - A100

  • 256GB RAM
  • Dual 18-Core E5-2697v4
        (36 Cores & 72 Threads
  • 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

  • 256GB RAM
  • Dual 18-Core E5-2697v4
        (36 Cores & 72 Threads
  • 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.

    Multi-GPU Dedicated Server - 4xA100

  • 512GB RAM
  • Dual 22-Core E5-2699v4
        (44 Cores & 88 Threads
  • 240GB SSD + 4TB NVMe + 16TB
        SATA
  • 1Gbps


  • OS: Windows / Linux
    GPU: 4xNvidia A100

  • Microarchitecture: Ampere
  • CUDA Cores: 6912
  • Tensor Cores: 432
  • GPU Memory: 40GB HBM2
  • FP32 Performance: 19.5
        TFLOPS













  • Enterprise GPU Dedicated Server - A100(80GB)

  • 256GB RAM
  • Dual 18-Core E5-2697v4
        (36 Cores & 72 Threads
  • 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

  • 256GB RAM
  • Dual 18-Core E5-2697v4
        (36 Cores & 72 Threads
  • 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: 183
        TFLOPS















  • More GPU Hosting Plans

    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.

     NVIDIA GPU

    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.


    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.

    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

    Customization

    Customization

    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.


    Efficiency

    Efficiency

    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.

    Cost

    Cost

    As a self-hosted alternative to ChatGPT, Ollama is freely available, while ChatGPT may incur costs for certain versions or usage.


    Flexibility

    Flexibility

    Ollama allows for running multiple models in parallel, providing customization and integration, which can be useful for tasks like autogen and other applications.

    Security and Privacy

    Security 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.

    Simplicity and Accessibility

    Simplicity 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.


    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.


    DeepSeek
    Model Name Params Model Size Recommended GPU cards
    DeepSeek R1 7B 4.7GB GTX 1660 6GB or higher
    DeepSeek R1 8B 4.9GB GTX 1660 6GB or higher
    DeepSeek R1 14B 9.0GB RTX A4000 16GB or higher
    DeepSeek R1 32B 20GB RTX 4090, RTX A5000 24GB, A100 40GB
    DeepSeek R1 70B 43GB RTX A6000, A40 48GB
    DeepSeek R1 671B 404GB Not supported yet
    Deepseek-coder-v2 16B 8.9GB RTX A4000 16GB or higher
    Deepseek-coder-v2 236B 133GB 2xA100 80GB, 4xA100 40GB
    Llama
    Model Name Params Model Size Recommended GPU cards
    Llama 3.3 70B 43GB A6000 48GB, A40 48GB, or higher
    Llama 3.1 8B 4.9GB GTX 1660 6GB or higher
    Llama 3.1 70B 43GB A6000 48GB, A40 48GB, or higher
    Llama 3.1 405B 243GB 4xA100 80GB, or higher
    Gemma
    Model Name Params Model Size Recommended GPU cards
    Gemma 2 9B 5.4GB RTX 3060 Ti 8GB or higher
    Gemma 2 27B 16GB RTX 4090, A5000 or higher
    Qwen
    Model Name Params Model Size Recommended GPU cards
    Qwen2.5 7B 4.7GB GTX 1660 6GB or higher
    Qwen2.5 14B 9GB RTX A4000 16GB or higher
    Qwen2.5 32B 20GB RTX 4090 24GB, RTX A5000 24GB
    Qwen2.5 72B 47GB A100 80GB, H100
    Qwen2.5 Coder 14B 9.0GB RTX A4000 16GB or higher
    Qwen2.5 Coder 32B 20GB RTX 4090 24GB, RTX A5000 24GB or higher
    Phi
    Model Name Params Model Size Recommended GPU cards
    Phi-4 14B 9.1GB RTX A4000 16GB or higher
    Phi-3 14B 7.9GB RTX A4000 16GB or higher
    Mistral
    Model Name Params Model Size Recommended GPU cards
    Mistral 7B 4.1GB GTX 1660 6GB or higher
    Mixtral 8x7B 26GB A6000 48GB, A40 48GB, or higher
    Mixtral 8x22B 80GB 2xA6000, 2xA100 80GB, or higher


    How to Run LLMs Locally with Ollama AI

    Deploy Ollama on a bare-metal server with a dedicated or multi-GPU setup in just 10 minutes at GPU Mart. (Supports automatic deployment or manual installation.)

    Step 1


    Order a GPU Server

    Click Order Now, on the order page, select the pre-installed Ollama OS image for automatic setup. Alternatively, choose a standard OS and manually install Ollama after deployment.

    Step 2


    Install Ollama AI

    If you selected a standard OS, remotely log in to your GPU server and install the latest version of Ollama from the official website. Installation steps are the same as a local deployment.

    Step 3


    Download an LLM Model

    Choose and download a pre-trained LLM model compatible with Ollama. You can explore different models based on your needs:
    - Run Llama 3.1 8B with Ollama
    - Run Mistral using Ollama
    - Install and Run DeepSeek R1 Locally With Ollama

    Step 4


    Chat with the Model

    Start interacting with your model directly from the terminal or via Ollama's API for integration into applications.

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

    Get in touch

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