Model Architecture
Based on the Transformer architecture, it may be optimized and customized for specific domains to offer faster inference speeds and lower resource consumption.
DeepSeek R1 Hosting, Deploy DeepSeek R1 on GPUMart
DeepSeek-R1 is a powerful open-source AI model designed to address tasks requiring logical inference and mathematical problem-solving. Easily deploy DeepSeek R1 on our private AI servers and scale your LLM hosting with Ollama and top frameworks.
Choose Your DeepSeek R1 Hosting Plans
GPUMart offers the best budget DeepSeek GPU server solutions. Our cost-effective, dedicated hardware is ideal for secure LLM hosting and running your own DeepSeek-R1 models.
DeepSeek-R1 1.5B-8B
DeepSeek-R1 14B
DeepSeek-R1 32B
DeepSeek-R1 70B
Express GPU Dedicated Server - P1000
$Β 64.00/mo
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Order Now- 32GB RAM
- GPU: Nvidia Quadro P1000
- Eight-Core Xeon E5-2690ξ
- 120GB + 960GB SSD
- 100Mbps-1Gbpsξ
- OS: Windows / Linux
- Single GPU Specifications:
- Microarchitecture: Pascal
- CUDA Cores: 640
- GPU Memory: 4GB GDDR5
- FP32 Performance: 1.894 TFLOPSξ
Basic GPU Dedicated Server - T1000
$Β 99.00/mo
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Order Now- 64GB RAM
- GPU: Nvidia Quadro T1000
- Eight-Core Xeon E5-2690ξ
- 120GB + 960GB SSD
- 100Mbps-1Gbpsξ
- OS: Windows / Linux
- Single GPU Specifications:
- Microarchitecture: Turing
- CUDA Cores: 896
- GPU Memory: 8GB GDDR6
- FP32 Performance: 2.5 TFLOPSξ
Hot Sale
Basic GPU Dedicated Server - RTX 4060
$Β 89.50/mo
50% OFF Recurring (Was $179.00)
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Order Now- 64GB RAM
- GPU: Nvidia GeForce RTX 4060
- Eight-Core E5-2690ξ
- 120GB SSD + 960GB SSD
- 100Mbps-1Gbpsξ
- OS: Windows / Linux
- Single GPU Specifications:
- Microarchitecture: Ada Lovelace
- CUDA Cores: 3072
- Tensor Cores: 96
- GPU Memory: 8GB GDDR6
- FP32 Performance: 15.11 TFLOPSξ
Hot Sale
Advanced GPU Dedicated Server - RTX 3060 Ti
$Β 107.55/mo
55% OFF Recurring (Was $239.00)
1mo3mo12mo24mo
Order Now- 128GB RAM
- GPU: GeForce RTX 3060 Ti
- Dual 12-Core E5-2697v2ξ
- 240GB SSD + 2TB SSD
- 100Mbps-1Gbpsξ
- OS: Windows / Linux
- Single GPU Specifications:
- Microarchitecture: Ampere
- CUDA Cores: 4864
- Tensor Cores: 152
- GPU Memory: 8GB GDDR6
- FP32 Performance: 16.2 TFLOPSξ
More GPU Server Instance Pricingarrow_circle_right
Benchmarking DeepSeek-r1 14b on Ollama0.5.7
Deepseek-R1, 14b, 9GB, Q4
For more details and versions of Deepseek-R1 14B servers.
Deepseek-R1, 14b, 9GB, Q4
For more details and versions of Deepseek-R1 14B servers.
| GPU Servers | GPU VPS - A4000 | GPU Dedicated Server - P100 | GPU Dedicated Server - V100 |
| Downloading Speed(MB/s) | 36 | 11 | 11 |
| CPU Rate | 3% | 2.5% | 3% |
| RAM Rate | 17% | 6% | 5% |
| GPU UTL | 83% | G91% | 80% |
| Downloading Speed(MB/s) | 30.2 | 18.99 | 48.63 |
Benchmarking DeepSeek-r1 32b on Ollama0.5.7
Deepseek-R1:32b, 20GB, Q4
For more details and versions of Deepseek-R1:32b servers.
Deepseek-R1:32b, 20GB, Q4
For more details and versions of Deepseek-R1:32b servers.
| GPU Servers | GPU VPS - A5000 | GPU Dedicated Server - RTX 4090 | GPU Dedicated Server - A100 40GB | GPU Dedicated Server - A6000 |
| Downloading Speed(MB/s) | 113 | 113 | 113 | 113 |
| CPU Rate | 3% | 3% | 2% | 5% |
| RAM Rate | 6% | 3% | 4% | 4% |
| GPU UTL | 97% | 98% | 81% | 89% |
| Downloading Speed(MB/s) | 24.21% | 34.22% | 35.01% | 27.96% |
Benchmarking DeepSeek-r1 70b on Ollama0.5.7
Deepseek-R1, 70b, 43GB, Q4
Deepseek-R1, 70b, 43GB, Q4
DeepSeek-R1 vs. OpenAI O1: Benchmark Performance
DeepSeek-R1 competes directly with OpenAI o1 across several benchmarks, often matching or surpassing OpenAIβs o1 in complex LLM inference tasks.
Advantages of DeepSeek-V3 over OpenAI's GPT-4
Comparing DeepSeek-V3 with GPT-4 involves evaluating their strengths and weaknesses in various areas.
Performance
May excel in specific tasks, especially in scenarios requiring high accuracy and low latency.
Application Scenarios
Suitable for scenarios requiring high precision and efficient processing, such as finance, healthcare, legal fields, and real-time applications needing quick responses.
Customization and Flexibility
May offer more customization options, allowing users to tailor the model to specific needs.
Cost and Resource Consumption
Likely more optimized in terms of resource consumption and cost, making it suitable for scenarios requiring efficient use of computing resources.
Ecosystem and Integration
May have tighter integration with specific industries or platforms, offering more specialized solutions.
How to Run DeepSeek R1 LLMs with Ollama
Let's go through Get up and running with DeepSeek, Llama, Gemma, and other LLMs with Ollama step-by-step.
Order and Login GPU Server
Download and Install Ollama
Run DeepSeek R1 with Ollama
Chat with DeepSeek R1
Sample Command line
# install Ollama on Linux curl -fsSL https://ollama.com/install.sh | sh # on GPU VPS - A4000 16GB, you can run deepseek-r1 1.5b,7b,8b and 14b ollama run deepseek-r1:1.5b ollama run deepseek-r1 ollama run deepseek-r1:8b ollama run deepseek-r1:14b # on GPU dedicated server - A5000 24GB, RTX4090 24GB and A100 40GB, you can run deepseek-r1 32b ollama run deepseek-r1:32b # on GPU dedicated server - A6000 48GB and A100 80GB, you can run deepseek-r1 70b ollama run deepseek-r1:70b
6 Reasons to Choose our GPU Servers for DeepSeek R1 Hosting
DatabaseMart enables powerful LLM hosting features on raw bare metal hardware, served on-demand. Easily deploy DeepSeek R1 without inefficiency or noisy neighbors.
NVIDIA GPU
Rich Nvidia graphics card types on bare metal GPUs, up to 80GB VRAM, delivering powerful CUDA performance for your DeepSeek GPU server.
SSD-Based Drives
You can never go wrong with our top-notch private AI servers, loaded with Intel Xeon processors, terabytes of NVMe SSD space, and up to 256 GB RAM.
Full Root/Admin Access
With full root/admin access, you have complete control to deploy DeepSeek R1 and customize your AI environment securely and quickly.
99.9% Uptime Guarantee
Backed by enterprise-class data centers, we provide a 99.9% uptime guarantee to ensure low latency and continuous LLM hosting.
Dedicated IP
A premium feature for every plan. Even our most budget-friendly DeepSeek hosting plan includes dedicated IPv4 & IPv6 addresses for secure access.
24/7/365 Technical Support
We provide round-the-clock technical support to help you resolve any issues related to your AI infrastructure and DeepSeek hosting.
DeepSeek-R1 on Different LLM Frameworks & Tools
Install and Run DeepSeek-R1 Locally with Ollama
Ollama is a self-hosted AI solution to run open-source large language models, such as DeepSeek, Gemma, Llama, Mistral, and other LLMs locally or on your own infrastructure.
Install and Run DeepSeek-R1 Locally with vLLM v1 >
vLLM is an optimized framework designed for high-performance inference of Large Language Models (LLMs). It focuses on fast, cost-efficient, and scalable serving of LLMs.
Other Popular LLM Models
DBM has a variety of high-performance Nvidia GPU servers equipped with one or more RTX 4090 24GB, RTX A6000 48GB, A100 40/80GB, which are very suitable for LLMs inference. Choosing the Right GPU for Popular LLMs on Ollama
Qwen2.5 Hosting >
Qwen2.5 models are pretrained on Alibaba's latest large-scale dataset, encompassing up to 18 trillion tokens. The model supports up to 128K tokens and has multilingual support.
LLaMA 3.1 Hosting >
Llama 3.1 is the state-of-the-art, available in 8B, 70B and 405B parameter sizes. Metaβs smaller models are competitive with closed and open models that have a similar number of parameters.
Gemma 3 Hosting >
Googleβs Gemma 3 model is available in three sizes, 2B, 9B and 27B, featuring a brand new architecture designed for class leading performance and efficiency.
Phi-4/3/2 Hosting >
Phi is a family of lightweight 3B (Mini) and 14B (Medium) state-of-the-art open models by Microsoft.
GPU Card Benchmarks
DBM provides comprehensive benchmarks for a wide range of Nvidia GPUs, helping you choose the best hardware for your LLM inference needs.
Ollama GPU Benchmark: P1000 The Nvidia P1000 is an entry-level GPU, ideal for lightweight LLM tasks and small-scale deployments,like 1.5b
Ollama GPU Benchmark: T1000 The Nvidia T1000 offers a balance of performance and efficiency, suitable for mid-range LLM workloads, like 7b, 8b.
Ollama GPU Benchmark: GTX 1660 The GTX 1660 is a budget-friendly GPU suitable for entry-level LLM tasks and small-scale deployments.
Ollama GPU Benchmark: RTX 4060 The Nvidia RTX 4060 is a mid-range GPU, offering strong performance for LLM workloads in the 7b, 8b parameter range, balancing efficiency and capability.
Ollama GPU Benchmark: RTX 3060 Ti The RTX 3060 Ti delivers excellent performance for its price, making it a popular choice for LLM inference.
Ollama GPU Benchmark: RTX 2060 The RTX 2060 offers good performance for mid-range LLM workloads, providing a balance between cost and capability.
Ollama GPU Benchmark: A4000 The Nvidia A4000 is a powerful workstation GPU, capable of handling demanding LLM tasks with ease.
Ollama GPU Benchmark: V100 The V100 is a high-performance GPU designed for deep learning and large-scale LLM inference.
Ollama GPU Benchmark: A5000 The A5000 offers exceptional performance for AI workloads, including LLM training and inference.
Ollama GPU Benchmark: A6000 The Nvidia A6000 is a top-tier GPU, ideal for high-performance LLM tasks and large-scale deployments.
Ollama GPU Benchmark: RTX4090 The RTX4090 is a flagship GPU, offering unmatched performance for LLM inference and AI workloads.
Ollama GPU Benchmark: A40 The A40 is a versatile GPU, optimized for AI, rendering, and LLM inference tasks.
Ollama GPU Benchmark: A100 (40GB) The A100 (40GB) is a powerhouse GPU, designed for large-scale LLM training and inference.
Ollama GPU Benchmark: Dual A100 Dual A100 GPUs provide extreme performance, ideal for the most demanding LLM workloads.
Ollama GPU Benchmark: H100 The H100 is Nvidia's latest flagship GPU, offering cutting-edge performance for AI and LLM tasks.
FAQs of DeepSeek Hosting
Here are some Frequently Asked Questions about DeepSeek-R1.
What is DeepSeek-R1?
DeepSeek-R1 is a powerful open-source AI model in the DeepSeek family, optimized for specific tasks like real-time processing, low-latency applications, and resource-constrained environments. It achieves performance comparable to OpenAI-o1 across math, code, and reasoning tasks.
What are the key differences between DeepSeek-V3 and DeepSeek-R1?
DeepSeek-V3: Focuses on versatility and high performance across a wide range of tasks.
DeepSeek-R1: Optimized for speed and low resource consumption. It offers various parameter models making it ideal for real-time applications and environments with limited computational power.
DeepSeek-R1: Optimized for speed and low resource consumption. It offers various parameter models making it ideal for real-time applications and environments with limited computational power.
Who can use DeepSeek-V3 and DeepSeek-R1?
Both models are designed for businesses, developers, and researchers. They are suitable for anyone needing advanced NLP capabilities deployed securely on a private AI server.
How does DeepSeek-V3 compare to OpenAI's GPT models?
DeepSeek-V3 is designed for efficiency and precision in specific domains, while OpenAI's GPT models are more general-purpose. DeepSeek models often match or exceed performance in specialized LLM inference tasks.
How does DeepSeek-R1 handle low-resource environments?
DeepSeek-R1 is optimized for minimal resource consumption, making it suitable for deployment on edge devices, mobile applications, and environments prioritizing data privacy.
How can I deploy DeepSeek-R1?
You can easily deploy DeepSeek-R1 on our dedicated DeepSeek GPU servers with full root access. Both models can be deployed via APIs, cloud services, or on-premise solutions using top LLM frameworks.