NVIDIA GPU
Rich Nvidia graphics card types, up to 8x48GB VRAM, powerful CUDA performance. There are also multi-card servers for you to choose from.
Qwen2.5 Hosting, Host Your Qwen-2.5 with Ollama
Qwen 2.5 is designed to be a versatile tool, capable of handling a wide range of tasks across various industries. Find the most optimal way to host your own Qwen LLM on our cheap GPU servers.
Choose Your Qwen2.5 Hosting Plans
DatabaseMart offers best budget GPU servers for Qwen2.5. Cost-effective dedicated GPU servers are ideal for hosting your own LLMs online.
Professional GPU VPS - RTX Pro 2000
$ 95.20/mo
20% OFF (Was $119.00)
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Order Now- GPU Model: RTX Pro 2000
- CPU: 16 CPU Cores
- Memory: 28GB RAM
- Disk: 240GB SSD
- Bandwidth: 300Mbps Unmetered
- IP: 1 Dedicated IPv4
- Location: USA
- Backup: Once per 2 Weeks
Professional GPU VPS - RTX A4000
$ 119.00/mo
20% OFF (Was $149.00)
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Order Now- GPU Model: RTX A4000
- CPU: 24 CPU Cores
- Memory: 28GB RAM
- Disk: 320GB SSD
- Bandwidth: 300Mbps Unmetered
- IP: 1 Dedicated IPv4
- Location: USA
- Backup: Once per 2 Weeks
Advanced Dedicated GPU Server - RTX A5000
$ 269.00/mo
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Order Now- GPU Model: RTX A5000
- CPU: 24-Core Dual E5-2697v2
- Memory: 128GB RAM
- Disk: 240GB SSD+2TB SSD
- Bandwidth: 100Mbps Unmetered
- IP: 1 Dedicated IPv4
- Location: USA
Advanced GPU VPS - RTX 5090
$ 399.00/mo
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Order Now- GPU Model: RTX 5090
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- Backup: Once per 2 Weeks
Advanced GPU VPS - RTX Pro 4000
$ 159.00/mo
20% OFF (Was $199.00)
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Order Now- GPU Model: RTX Pro 4000
- CPU: 24 CPU Cores
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- Backup: Once per 2 Weeks
Enterprise Dedicated GPU Server - RTX A6000
$ 329.40/mo
40% OFF (Was $549.00)
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Order Now- GPU Model: RTX A6000
- CPU: 36-Core Dual E5-2697v4
- Memory: 256GB RAM
- Disk: 240GB SSD+2TB NVMe+8TB SATA
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Enterprise Dedicated GPU Server - RTX 4090
$ 307.44/mo
44% OFF (Was $549.00)
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Order Now- GPU Model: RTX 4090
- CPU: 36-Core Dual E5-2697v4
- Memory: 256GB RAM
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Enterprise Dedicated GPU Server - A100
$ 359.55/mo
55% OFF (Was $799.00)
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Order Now- GPU Model: A100
- CPU: 36-Core Dual E5-2697v4
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Enterprise Multi-GPU Dedicated Server - 2xRTX 5090
$ 859.00/mo
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- CPU: 44-core Dual E5-2699v4
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Enterprise Dedicated GPU Server - A100(80GB)
$ 1559.00/mo
8% OFF (Was $1699.00)
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Order Now- GPU Model: A100(80GB)
- CPU: 36-Core Dual E5-2697v4
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- IP: 1 Dedicated IPv4
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Enterprise GPU VPS - RTX Pro 6000
$ 479.00/mo
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Order Now- GPU Model: RTX Pro 6000
- CPU: 32 CPU Cores
- Memory: 84GB RAM
- Disk: 400GB SSD
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- IP: 1 Dedicated IPv4
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- Backup: Once per 2 Weeks
Enterprise Multi-GPU Dedicated Server - 4xRTX A6000
$ 1199.00/mo
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Order Now- GPU Model: 4 x RTX A6000
- CPU: 44-core Dual E5-2699v4
- Memory: 512GB RAM
- Disk: 240GB SSD+4TB NVMe+16TB SATA
- Bandwidth: 1000Mbps Unmetered
- NVLink: 2xNVLink
- IP: 1 Dedicated IPv4
- Location: USA
More GPU Server Instance Pricingarrow_circle_right
6 Reasons to Choose our GPU Servers for Qwen2.5 Hosting
DatabaseMart enables powerful GPU hosting features on raw bare metal hardware, served on-demand. No more inefficiency, noisy neighbors, or complex pricing calculators.
SSD-Based Drives
You can never go wrong with our own top-notch dedicated GPU servers, loaded with the latest Intel Xeon processors, terabytes of SSD disk space, and 256 GB of RAM per server.
Full Root/Admin Access
With full root/admin access, you will be able to take full control of your dedicated GPU servers very easily and quickly.
99.9% Uptime Guarantee
With enterprise-class data centers and infrastructure, we provide a 99.9% uptime guarantee for LLM hosting service.
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
We provides round-the-clock technical support to help you resolve any issues related to DeepSeek hosting.
Qwen 2.5 — Is it better than GPT-4o?
Qwen 2.5 competes directly with OpenAI o1 across several benchmarks, often matching or surpassing OpenAI’s GPT-4o.
Key Features and Capabilities of Qwen 2.5
Understanding the core strengths of a tool is the first step toward maximizing its potential.
Expanded Model Range
Offers a variety of models to suit different applications, with sizes ranging from 0.5 to 72 billion parameters.
Larger Training Dataset
It possesses significantly more knowledge and has greatly enhanced capabilities in coding and mathematics, due to specialized expert models in these domains.
Extended Context Window
Capable of processing and generating content across multiple formats. It supports long contexts of up to 128K tokens and can generate up to 8K tokens.
Superior Coding Abilities
Demonstrates improved coding skills, making it a valuable tool for developers. Enhanced capabilities in mathematical reasoning tasks.
Multilingual Support
It offers multilingual support for over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, Arabic, and more.
Better Efficiency and Speed
Utilizes a Mixture of Experts (MoE) architecture, employing 64 specialized expert networks activated dynamically, enhancing efficiency and reducing computational costs by approximately 30% compared to monolithic architectures.
How to Run Qwen 2.5 LLMs with Ollama
Let's go through Get up and running with Qwen, DeepSeek, Llama, Gemma, and other LLMs with Ollama step-by-step.
Order and Login GPU Server
Download and Install Ollama
Run Qwen 2.5 with Ollama
Chat with Qwen 2.5
Sample Command line
# install Ollama on Linux
curl -fsSL https://ollama.com/install.sh | sh
# on GPU VPS - A4000 16GB, you can run Qwen 1.5b,3b,7b and 14b
ollama run qwen2.5:3b
ollama run qwen2.5:7b
ollama run qwen2.5:14b
# on GPU dedicated server - A5000 24GB, RTX4090 24GB and A100 40GB, you can run Qwen2.5 32b
ollama run qwen2.5:32b
# on GPU dedicated server - A100 80GB and H100, you can run Qwen2.5 70b
ollama run qwen2.5:72bFAQs of Qwen2.5 Hosting
Here are some Frequently Asked Questions (FAQs) related to hosting and deploying the Qwen 2.5 model.
What is Qwen2.5?
Qwen2.5 models are pretrained on Alibaba's latest large-scale dataset, encompassing up to 18 trillion tokens. The model is a series of advanced AI models developed by Alibaba, including large language models (LLMs), multimodal models, and specialized models for coding (Qwen2.5-Coder) and mathematics (Qwen2.5-Math). It supports up to 128K context length and 29+ languages, making it versatile for various applications.
What are the system requirements for hosting Qwen 2.5?
GPU Memory: At least 14.74 GiB for smaller models like Qwen2.5-7B. Larger models (e.g., 72B) may require multiple GPUs or 60GB+ VRAM configurations.
CPU and RAM: Minimum 8 CPU cores and 32GB RAM for smaller models.
Quantization: For resource-constrained environments, consider using quantized versions (e.g., Q4_K_M) to reduce memory usage.
CPU and RAM: Minimum 8 CPU cores and 32GB RAM for smaller models.
Quantization: For resource-constrained environments, consider using quantized versions (e.g., Q4_K_M) to reduce memory usage.
Can Qwen 2.5 be deployed locally?
Yes, Qwen 2.5 can be deployed locally using tools like Ollama or Docker.
What frameworks support Qwen 2.5 deployment?
Qwen 2.5 is compatible with multiple frameworks, including: 1. Transformers: For general-purpose inference. 2. vLLM: For high-throughput, low-latency inference. 3. Ollama: For local deployment and API integration. 4. ModelScope: For easy model downloading and fine-tuning.
How do I interact with Qwen 2.5 after deployment?
Use Open WebUI for a graphical interface to interact with the model. Alternatively, use API endpoints (e.g., /api/generate or /api/chat) for programmatic access.
Can Qwen 2.5 be fine-tuned for specific tasks?
Yes, Qwen 2.5 supports fine-tuning using frameworks like Axolotl, Llama-Factory, and ms-swift. Fine-tuning can be done on both local and cloud environments.