LLaMA 3.1 Hosting, Host Your
LLaMA LLM with Ollama

Llama 3.1 is the state-of-the-art, available in 8B, 70B and 405B parameter sizes. Meta’s smaller models are competitive with closed and open models that have a similar number of parameters. You can deploy your own Llama 3.1 with Ollama.

  • Windows or Linux OS
  • Full Root/Admin Access
  • Support RDP/SSH Access
  • Free 24/7/365 Expert Online Support
  • Servers Delivered within 20 to 40 Minutes

Choose Your LLaMA 3.1 Hosting Plans

GPUMart offers best budget GPU servers for LLaMA 3.1. Cost-effective hosting of LLaMA 3.1 cloud is ideal for hosting your own LLMs online.

Professional GPU VPS - A4000


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



    • Once per 2 Weeks Backup
    OS: Windows / Linux 10/
         Windows11
    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 - A4000

  • 128GB RAM
  • Dual 12-Core E5-2697v2
        (24 Cores & 48 Threads
  • 240GB SSD + 2TB SSD
  • 100Mbps-1Gbps




    • OS: Windows / Linux
    GPU: Nvidia Quadro RTX A4000

  • Microarchitecture: Ampere
  • CUDA Cores: 6144
  • Tensor Cores: 192
  • GPU Memory: 16GB GDDR6
  • FP32 Performance: 19.2 TFLOPS


    • Good choice for hosting AI image generator, BIM, 3D rendering, CAD, deep learning, etc.

    Advanced GPU Dedicated Server - V100

  • 128GB RAM
  • Dual 12-Core E5-2690v3
        (24 Cores & 48 Threads
  • 240GB SSD + 2TB SSD
  • 100Mbps-1Gbps





    • OS: Linux / Windows
    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 A6000

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



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

  • Microarchitecture: Ampere
  • CUDA Cores: 10,752
  • Tensor Cores: 336
  • GPU Memory: 48GB GDDR6X
  • FP32 Performance: 38.71
         TFLOPS


    • Optimally running 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: GeFirce RTX 4090

  • Microarchitecture: Ada Lovelace
  • CUDA Cores: 16,384
  • Tensor Cores: 512
  • GPU Memory: 24GB GDDR6X
  • FP32 Performance: 82.6
        TFLOPS


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

    Multi-GPU Dedicated Server - 3xV100

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


    • OS: Windows / Linux
    GPU: 3xNvidia V100

  • Microarchitecture: Volta
  • CUDA Cores: 5,120
  • Tensor Cores: 640
  • GPU Memory: 16GB HBM2
  • FP32 Performance: 14 TFLOPS





    • Expertise in deep learning and AI workloads with more tensor cores

    Enterprise GPU Dedicated Server - A40

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


    • OS: Windows / Linux
    GPU: Nvidia A40

  • Microarchitecture: Ampere
  • CUDA Cores: 10,752/li>
  • Tensor Cores: 336
  • GPU Memory: 48GB GDDR6
  • FP32 Performance: 38.48
        TFLOPS



    • Ideal for hosting AI image generator, deep learning, HPC, 3D Rendering, VR/AR etc.

    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: 4 x Nvidia A100

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









    • More GPU Hosting Plans

    6 Reasons to Choose our GPU Servers for LLaMA 3.1 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 40GB 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 LLaMA 3.1, loaded with the latest Intel Xeon processors, terabytes of SSD disk space, and 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 LLaMA3 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 Llama3.1 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 LLaMA 3.1 hosting.


    What Can You Use Hosted Llama 3.1 For?

    Hosted LLaMA 3.1 offers a powerful and flexible tool for various applications, particularly for organizations and developers who want to leverage advanced AI capabilities without the need for extensive infrastructure.

    Text Generation

    Text Generation

    Generate high-quality, coherent text for various purposes, such as content creation, blogging, and automated writing.


    Summarization

    Summarization

    Summarize large documents, articles, or any other text data, providing concise and accurate summaries.

    Translation

    Translation

    Translate text between different languages, leveraging the model's multilingual capabilities.


    Chatbots

    Chatbots

    Develop advanced chatbots that can engage in human-like conversations, providing customer support, answering queries, or even conducting interviews.

    Programming Assistance

    Programming Assistance

    Use the model to generate code snippets, assist in debugging, or even help with understanding complex codebases.

    Creative Writing

    Creative Writing

    Assist in generating creative content, such as stories, poems, scripts, or even marketing copy.

    Question Answering

    Question Answering

    Implement advanced Q&A systems that can answer detailed and complex questions based on extensive text sources.

    Global Customer Support

    Global Customer Support

    Offer multilingual customer support by deploying LLaMA 3.1 in different languages, ensuring consistent service across regions.

    Advantages of Llama 3.1 over ChatGPT

    Comparing LLaMA 3.1 with ChatGPT involves evaluating their strengths and weaknesses in various areas.

    Purpose and Training

    LLaMA 3.1 is designed primarily for research and academic purposes. They excel in specific tasks such as reasoning, coding, and handling multilingual inputs. Meta’s focus with LLaMA has been on pushing the boundaries of open-source AI models, providing the research community with powerful tools.

    Performance

    With its large parameter size (up to 405 billion parameters), LLaMA 3.1 is highly capable in tasks requiring deep understanding and generation of complex text. It's competitive with other top-tier models like GPT-4 in specific technical tasks, especially in multilingual and long-context scenarios.


    Commercial Use

    While LLaMA 3.1 can be used for commercial purposes with the appropriate license, it’s primarily aimed at research and academic use. It may require significant customization and fine-tuning for specific commercial applications.

    Accessibility

    As an open-source model (with restrictions), LLaMA 3.1 is accessible to researchers and developers who can customize it for their needs. However, it may require more technical expertise to deploy effectively.

    How to Run Llama 3.1 with Ollama

    We will go through How to Run Llama 3.1 8B with Ollama step-by-step.



    Order and Login GPU Server



    Download and Install Ollama



    Run Llama 3.1 with Ollama



    Chat with Meta Llama 3.1


    FAQs of LLaMA 3.1 Hosting

    The most commonly asked questions about GPUMart Llama 3.1 cloud hosting service below.

    What is Llama 3.1?
    Llama 3.1 is a new state-of-the-art model from Meta available in 8B, 70B and 405B parameter sizes. Specifically, the "8B" denotes that this model has 8 billion parameters, which are the variables the model uses to make predictions.
    LLaMA 3.1, like its predecessors, is not entirely free for commercial use. While Meta has made the LLaMA models available for research and academic purposes, they have specific licensing restrictions regarding commercial use.
    To use LLaMA 3.1 for commercial purposes, organizations typically need to obtain a special license from Meta. The commercial license is not freely available, and interested parties usually need to negotiate terms directly with Meta.
    Llama3.1 8B balances performance and computational efficiency, making it suitable for a range of applications such as text generation, question answering, language translation, and code generation. Despite having fewer parameters compared to larger models like Llama 3.1 70B, it delivers impressive results in various natural language processing tasks. Additionally, Meta’s smaller models are competitive with closed and open models that have a similar number of parameters.
    LLaMA 3.1 might be better suited for research, technical tasks, and applications requiring a highly customizable and powerful open-source model. ChatGPT (GPT-4) is likely better for general-purpose use, especially in conversational contexts, and is more accessible for commercial deployment with less need for extensive customization.
    Ollama is an open source large language modeling service tool that helps users quickly run large models locally. With a simple install command, users can run open source large language models such as qwen locally with a single command. Ollama greatly simplifies the process of deploying and managing LLMs in Docker containers, enabling users to quickly run large language models locally!
    Llamma 3.1 8B is best for prototyping, lightweight applications, or use cases where computational resources are limited. Suitable for systems with lower VRAM (e.g., 16-24 GB).
    70B is best for more complex applications requiring better language understanding, reasoning, and accuracy. Requires significant VRAM, ideally 48 GB or more.
    405B for advanced AI research, specialized tasks, or scenarios where the highest accuracy and detail are crucial (e.g., medical diagnostics, scientific research). Requires advanced hardware such as NVIDIA A100 with large VRAM capacities (160 GB or more).
    There is a simple conversion method: different dtypes, each 1 billion parameters require memory as follows:
    - float32 4G
    - fp16/bf16 2G
    - int8 1G
    - int4 0.5G
    Then, if the 8B model uses int8 precision, it will require 1G*8 = 8G of video memory. An RTX 4000 VPS can do it. For LLaMA 3.1 70B, it is best to use a GPU with at least 48 GB of VRAM, such as the RTX A6000 Server.

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