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    Unsloth Hosting: GPU server for Fine-Tuning

    Are you looking for Unsloth hosting on a GPU server for efficient fine-tuning and training of your own language models? Here you will find plans with suitable compute power and sufficient VRAM for LoRA, QLoRA and other training methods.

    4 from 4 Offers* Last Updated: 11/11/2026

    Back to the GPU Servers comparison

    AP1-10 GPU

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    97% Recommendation

    Server location

    Diamond
    • NVIDIA® T4 GPU GPU
    • 16 GB (v)GPU Memory
    • 128 GB RAM
    GPU Server
    DDoS protection
    1 GPU
    16 GB (v)GPU RAM
    1 TB NVMe SSD
    AMD EPYC™ 7302P
    DDoS Protection
    Firewall
    Hourly Billing

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    £703.08

    Average price per month

    £649.00/Month plus setup £649.00

    Price details
    Monthly price £649.00
    Setup fee £649.00
    Contract term n/a
    Avg. price/month £703.08
    Cost 12 months £8,437.00
    Cost 24 months £16,225.00
    AP2-10 GPU

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    97% Recommendation

    Server location

    Diamond
    • NVIDIA® A10 GPU GPU
    • 24 GB (v)GPU Memory
    • 128 GB RAM
    GPU Server
    DDoS protection
    1 GPU
    24 GB (v)GPU RAM
    960 GB NVMe SSD
    AMD EPYC™ 7313P
    DDoS Protection
    Firewall
    Hourly Billing

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    £893.75

    Average price per month

    £825.00/Month plus setup £825.00

    Price details
    Monthly price £825.00
    Setup fee £825.00
    Contract term n/a
    Avg. price/month £893.75
    Cost 12 months £10,725.00
    Cost 24 months £20,625.00
    IP3-10 GPU

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    97% Recommendation

    Server location

    Diamond
    • INTEL® Flex 170 GPU
    • 16 GB (v)GPU Memory
    • 256 GB RAM
    GPU Server
    DDoS protection
    1 GPU
    16 GB (v)GPU RAM
    2 TB NVMe SSD
    Intel Xeon Gold 5412U
    DDoS Protection
    Firewall
    Hourly Billing

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    £941.42

    Average price per month

    £869.00/Month plus setup £869.00

    Price details
    Monthly price £869.00
    Setup fee £869.00
    Contract term n/a
    Avg. price/month £941.42
    Cost 12 months £11,297.00
    Cost 24 months £21,725.00

    Tip: Choose up to 3 offers and compare them with each other.

    IP4-60 GPU

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    97% Recommendation

    Server location

    Diamond
    • NVIDIA® RTX PRO 6000 Blackwell GPU
    • 96 GB (v)GPU Memory
    • 256 GB RAM
    GPU Server
    DDoS protection
    1 GPU
    96 GB (v)GPU RAM
    3.200 GB NVMe SSD
    Intel Xeon 6517P
    DDoS Protection
    Firewall
    Hourly Billing

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    £2,979.17

    Average price per month

    £2,750.00/Month plus setup £2,750.00

    Price details
    Monthly price £2,750.00
    Setup fee £2,750.00
    Contract term n/a
    Avg. price/month £2,979.17
    Cost 12 months £35,750.00
    Cost 24 months £68,750.00

    * At hosttest, only a selection of providers can be found. Offers marked with an asterisk have additional conditions on the offer detail page. More information about our ranking and sorting details.

    * All prices on this page are net prices and are subject to the applicable VAT.

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    Unsloth GPU Server for efficient LLM fine-tuning

    Unsloth is focused on memory- and compute-efficient training and fine-tuning of language models. A powerful GPU server makes it possible to process your own datasets and customise models without having to acquire the entire infrastructure yourself.

    How much GPU power is required?

    Hardware requirements depend on model size, context length, batch size and training method. QLoRA usually requires less VRAM than LoRA with higher accuracy. Sufficient RAM, fast NVMe storage and a compatible software environment are also important so that datasets and checkpoints can be processed efficiently.

    Typical use cases

    • Fine-tuning with your own domain and company data
    • LoRA and QLoRA training
    • Customisation of chat, code and reasoning models
    • Experiments with different models and datasets
    • Export and subsequent production serving

    Plan training and serving separately

    An Unsloth GPU Server is primarily interesting for training and fine-tuning. For later deployment of the adapted model, a vLLM GPU Server, a SGLang GPU Server or a general LLM GPU Server may be appropriate.