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Open-Source · Self-Hosted · 100% Private

Deploy DeepSeek R1
on Your Own GPU Server

The most affordable DeepSeek R1 hosting on the market. Self-host DeepSeek R1 — 1.5B to 671B parameters — on a dedicated private AI server. Full root access, zero rate limits, unlimited LLM hosting. 10–100× cheaper than OpenAI API at scale.

R1 1.5B · 7B · 8B · 14B · 32B · 70B · 671B — all sizes supported

Compatible with Ollama, vLLM, llama.cpp — your framework, your rules

View Server Plans GPU Requirements Guide

GPUMart at a Glance

$64/m

7+ Years GPU Hosting

20min

Avg. Deploy Time

99.9%

Uptime SLA

100×

Cheaper vs API at Scale

Deploy DeepSeek R1 on your private AI server in 4 steps Order DeepSeek hosting → Install Ollama → Pull model → Chat with your AI

NVIDIA GPU · 4 GB – 384 GB VRAM

Full Root / Admin Access

24/7/365 Expert Support

NVMe SSD · Up to 256 GB RAM

GPU Requirements

DeepSeek R1 GPU Requirements: What VRAM Do You Need?

Understanding DeepSeek R1 GPU requirements is essential before you run DeepSeek R1 locally. VRAM is the single bottleneck — match your target model size to the right DeepSeek GPU server tier below.

4 – 8 GB VRAM

Entry Level

R1 1.5BR1 7B Q4

Recommended GPUs

Quadro P1000 (4 GB)
GeForce RTX 4060 (8 GB)
Quadro T1000 (8 GB)

$53

/mo from

DeepSeek R1 Cost: Self-Host vs OpenAI API

DeepSeek R1 cost drops dramatically when you self host DeepSeek on your own GPU server instead of paying per token. At 10 M tokens/month, the gap is already striking — and R1 matches o1 on every major benchmark.

OpenAI API (GPT-4o)

Using Closed API

Input tokens (5 M / month)$12.50

Output tokens (5 M / month)$37.50

Rate limits & queue latencyAlways present

Data privacy / compliance riskHigh

Model control / fine-tuningNone

$50+ /mo

for just 10 M tokens · scales unpredictably

Save 70–90%

Self-Hosted DeepSeek R1

Your Own GPU Server

Input tokens (unlimited)$0 extra

Output tokens (unlimited)$0 extra

Rate limitsNone

Data stays on your server100% Private

Fine-tuning & model controlFull Access

From $64 /mo

flat rate · unlimited inference · 24/7

DeepSeek R1 delivers comparable or better reasoning performance than OpenAI o1

DeepSeek R1 is designed for advanced reasoning tasks and performs on par with or better than o1 across major benchmarks. When deployed on dedicated GPU servers, it offers similar capabilities with lower long-term cost, full data privacy, and no API rate limits.

79.8%

AIME 2024
(o1: 79.2%)

97.3%

MATH-500
(o1: 96.4%)

65.9%

LiveCodeBench
(o1: 63.4%)

MIT

License
(o1: Closed)

Why Dedicated GPU

Why Choose a Dedicated DeepSeek GPU Server?
Not the API.

A private AI server with a dedicated GPU gives you control that no API can match — flat cost, unlimited throughput, and data that never leaves your infrastructure.

Complete Data Privacy

Prompts and responses never leave your server. Essential for finance, healthcare, and legal use-cases where data sovereignty is non-negotiable.

No Rate Limits, Ever

Run at full GPU speed with zero artificial throttling — perfect for batch inference, high-concurrency applications, and overnight jobs.

Predictable Flat Cost

One monthly price whether you run 1 M or 1 B tokens. Eliminate API billing surprises and forecast your AI infrastructure costs exactly.

Full Model Control

Fine-tune, quantize, swap versions, or run modified weights. Full root access means you own every layer of your AI stack.

Lower Latency

Direct bare-metal inference eliminates network round-trips to third-party API endpoints — critical for real-time chat and coding assistants.

Framework Freedom

Install Ollama, vLLM, or llama.cpp. Swap runtimes freely. No lock-in to any single inference stack or model provider.

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 Dedicated GPU Server - P1000

$ 40.70/mo

45% OFF (Was $74.00)

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GPU Model: P1000
CPU: 8-Core Xeon E5-2690
Memory: 32GB RAM
Disk: 120GB SSD + 960GB SSD
Bandwidth: 100Mbps Unmetered

IP: 1 Dedicated IPv4
Location: USA

Basic Dedicated GPU Server - T1000

$ 99.00/mo

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GPU Model: T1000
CPU: 8-Core Xeon E5-2690
Memory: 64GB RAM
Disk: 120GB SSD + 960GB SSD
Bandwidth: 100Mbps Unmetered

IP: 1 Dedicated IPv4
Location: USA

Basic Dedicated GPU Server - RTX 4060

$ 89.50/mo

50% OFF (Was $179.00)

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GPU Model: RTX 4060
CPU: 8-Core Xeon E5-2690
Memory: 64GB RAM
Disk: 120GB SSD + 960GB SSD
Bandwidth: 100Mbps Unmetered

IP: 1 Dedicated IPv4
Location: USA

Advanced Dedicated GPU Server - RTX 3060 Ti

$ 107.55/mo

55% OFF (Was $239.00)

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GPU Model: RTX 3060 Ti
CPU: 24-Core Dual E5-2697v2
Memory: 128GB RAM
Disk: 240GB SSD+2TB SSD
Bandwidth: 100Mbps Unmetered

IP: 1 Dedicated IPv4
Location: USA

More GPU Server Hosting Pricingarrow_circle_right

Model Comparison

DeepSeek R1 vs DeepSeek V3

Both models are open-source — but built for different jobs. Picking the wrong one wastes VRAM and reduces output quality.

Feature	DeepSeek R1	DeepSeek V3
Primary Strength	Reasoning, math, code logic, chain-of-thought	General NLP, instruction following, writing
Architecture	RL from reasoning traces	Standard Transformer, mixture-of-experts
Model Sizes	1.5B, 7B, 8B, 14B, 32B, 70B, 671B	7B, 67B, 685B
Min. VRAM (Q4)	~3 GB (1.5B)	~5 GB (7B)
Math / Coding Benchmarks	Matches or exceeds OpenAI o1	Strong, below R1 on reasoning
Creative Writing	Good	Excellent
Tokens per Second	Slightly slower (deeper reasoning)	Faster on same hardware
Best For	Agents, coding, data analysis, science	Chatbots, summarization, translation
License	MIT (open-source)	MIT (open-source)

Quick Decision Guide

Should You Use DeepSeek R1 or V3?

Choose DeepSeek R1 if…

You need a coding assistant, math solver, or data analyst

Your app needs multi-step reasoning or chain-of-thought

You're replacing OpenAI o1 with an open-source alternative

Legal, finance, science, or technical domain applications

You want smaller models that punch above their weight class

Choose DeepSeek V3 if…

You're building a general-purpose chatbot or assistant

Main use-case is summarization, translation, or writing

You need maximum tokens-per-second throughput

You're replacing GPT-4 for instruction-following tasks

Content generation, e-commerce, or customer-service bots

Our GPU servers run both models. Switch between them with a single Ollama command — no reinstall needed.

Deployment Guide

How to Run DeepSeek R1 Locally with Ollama

From zero to a running private AI model in under 20 minutes.

Order & Login GPU Server

Choose your plan, complete checkout, receive credentials within 20–40 minutes.

Install Ollama

One-line install on Linux. Ollama auto-detects your NVIDIA GPU and configures CUDA.

Pull & Run the Model

Run ollama run deepseek-r1:14b — model downloads and starts automatically.

Chat with DeepSeek R1

Use terminal, Ollama Web UI, or REST API. Your fully private AI is live.

Sample Commands — Ollama on Linux

# Step 1 — install Ollama

curl -fsSL https://ollama.com/install.sh | sh

# GPU VPS A4000 (16 GB) — R1 1.5B, 7B, 8B, 14B

ollama run deepseek-r1:1.5b

ollama run deepseek-r1:14b

# Dedicated A5000 / RTX 4090 (24 GB) — R1 32B

ollama run deepseek-r1:32b

# Dedicated A6000 (48 GB) or A100 (80 GB) — R1 70B

ollama run deepseek-r1:70b

Ready to deploy DeepSeek R1 on your own server?

DeepSeek hosting from $64/mo · Full root access · Deploy DeepSeek R1 in 20 min · 24/7 support

View DS Server Plans More GPU Hostings

Performance Benchmarks

Real-World Inference Benchmarks

Benchmarked on Ollama 0.5.7 with Q4 quantization. Select your target model size.

Metric

GPU VPS A4000

Dedicated P100

Dedicated V100

Download Speed

36 MB/s

11 MB/s

CPU Usage

2.5%

RAM Usage

17%

GPU Utilization

83%

91%

80% (efficient)

Inference Speed (tok/s)

30.2

18.99

48.63

Model: DeepSeek R1 14B · 9 GB · Q4 · Ollama 0.5.7. V100 leads on raw inference speed; A4000 VPS offers fastest download and lowest entry cost.

Metric

A5000 (24 GB)

RTX 4090 (24 GB)

A100 40 GB

A6000 (48 GB)

Download Speed

113 MB/s

CPU Usage

RAM Usage

GPU Utilization

97%

98%

81%

89%

Inference Speed (tok/s)

24.21

34.22

35.01

27.96

Model: DeepSeek R1 32B · 20 GB · Q4 · Ollama 0.5.7. A100 and RTX 4090 lead on inference speed; A100 offers the most headroom with lower GPU utilization.

Metric

Multi-GPU Dual A100

Dedicated H100

Download Speed

117 MB/s

113 MB/s

CPU Usage

RAM Usage

GPU Utilization

44% (dual)

92%

Inference Speed (tok/s)

19.34

24.94

Model: DeepSeek R1 70B · 43 GB · Q4 · Ollama 0.5.7. H100 leads single-GPU; Dual A100 provides more memory headroom for full-precision runs.

LLM Frameworks

Run DeepSeek R1 with Any Framework

All frameworks work out-of-the-box on our GPU servers. Install in minutes, switch anytime.

Ollama

One-command install and run. Includes OpenAI-compatible REST API. Best for getting started quickly and managing multiple model versions side-by-side.

vLLM

High-throughput production inference with PagedAttention and continuous batching. Ideal for serving concurrent users with tensor parallelism across multiple GPUs.

llama.cpp

CPU + GPU hybrid inference with aggressive quantization (Q4, Q5, Q8). Run larger models on smaller VRAM budgets — squeeze 32B into a 24 GB GPU.

HuggingFace Transformers

Full PyTorch ecosystem for research, fine-tuning, and custom pipelines. Access DeepSeek R1 weights directly from HuggingFace Hub with complete training support.

FAQ

Frequently Asked Questions

What is DeepSeek R1 and why should I self-host it?

DeepSeek R1 is a powerful open-source reasoning model that matches OpenAI o1 on math, code, and logic benchmarks. Self-hosting gives you complete data privacy, no rate limits, unlimited inference at a flat monthly cost, and full control to fine-tune the model — none of which are possible via API.

How much VRAM do I need to run DeepSeek R1?

R1 1.5B needs ~3 GB VRAM (Q4). R1 7B needs ~5–6 GB. R1 14B needs ~9–10 GB (Q4). R1 32B needs ~20 GB (Q4). R1 70B needs ~40–48 GB (Q4). Use the GPU requirements guide at the top of this page to match your model to the right server tier.

What is the difference between DeepSeek R1 and DeepSeek V3?

DeepSeek R1 is specialized for reasoning — math, code, logical inference — using reinforcement learning from reasoning traces. DeepSeek V3 is general-purpose, better for writing, translation, and instruction following. Choose R1 to replace OpenAI o1; choose V3 to replace GPT-4 for general tasks.

How much cheaper is self-hosting vs the OpenAI API?

At 10 M tokens/month, GPT-4o API costs $50+ in usage fees. A dedicated GPU server starts at $64/mo — same or lower price with unlimited tokens. At 50 M+ tokens/month, self-hosting is 10–100× cheaper than any commercial API with no usage caps.

How long does it take to deploy DeepSeek R1?

Servers are provisioned within 20–40 minutes. Installing Ollama takes under 1 minute. Downloading R1 14B Q4 (~9 GB) takes a few minutes. Most customers are running DeepSeek R1 within 30 minutes of ordering.

Can I run both DeepSeek R1 and V3 on the same server?

Yes. Ollama lets you pull and switch between multiple models instantly. Only one model loads into VRAM at a time. As long as your VRAM fits your active model, you can maintain a library of different versions and switch with a single command.

Get Started Today

Self-Host DeepSeek R1.
Your Data. Your Rules. Your Price.

Private GPU server · Full root access · Unlimited inference · Deploy in 20 minutes

View Server Plans GPU Requirements Guide

No hidden fees

24/7/365 expert support

99.9% uptime SLA

Cancel anytime

Deploy DeepSeek R1on Your Own GPU Server

DeepSeek R1 GPU Requirements: What VRAM Do You Need?

DeepSeek R1 Cost: Self-Host vs OpenAI API

Why Choose a Dedicated DeepSeek GPU Server?Not the API.

Complete Data Privacy

No Rate Limits, Ever

Predictable Flat Cost

Full Model Control

Lower Latency

Framework Freedom

Choose Your DeepSeek R1 Hosting Plans

DeepSeek R1 vs DeepSeek V3

Should You Use DeepSeek R1 or V3?

How to Run DeepSeek R1 Locally with Ollama

Real-World Inference Benchmarks

Run DeepSeek R1 with Any Framework

Frequently Asked Questions

Deploy DeepSeek R1
on Your Own GPU Server

Why Choose a Dedicated DeepSeek GPU Server?
Not the API.