Rent a GPU. Professional compute, made accessible.

Run AI, rendering, and compute workloads on dedicated NVIDIA GPUs with simple hourly pricing and no long-term commitment.
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Find the GPU that fits your workload

Compare VRAM, performance, and hourly pricing to find the right fit. No hidden fees or egress charges.

B200 (Dedicated)

Dedicated Blackwell B200, non-shared access for training and running the largest AI models.

From₦9,536.34/hour
Get GPU

953634 credits/hour (1 credit = ₦0.01). Billed only while your instance is running.

192GB VRAM

Recommended for:

Workloads requiring dedicated resources

AI inference at scale

Frontier LLM training

Scientific simulations and high-performance computing

B200

Latest Blackwell flagship for training and running the largest AI models.

From₦6,061.23/hour
Get GPU

606123 credits/hour (1 credit = ₦0.01). Billed only while your instance is running.

192GB VRAM

Recommended for:

Fine-tuning of large models

AI inference at scale

Frontier LLM training

Scientific simulations and high-performance computing

A100 80GB PCIe

Proven performance for serious AI training, inference, and research.

From₦1,926.12/hour
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192612 credits/hour (1 credit = ₦0.01). Billed only while your instance is running.

80GB VRAM

Recommended for:

AI model training

LLM inference with larger memory needs

Scientific computing and research

Data analytics at scale

L40S

Versatile Ada Lovelace GPU balancing strong inference performance with great price efficiency.

From₦1,239.18/hour
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123918 credits/hour (1 credit = ₦0.01). Billed only while your instance is running.

48GB VRAM

Recommended for:

AI inference and generative AI

3D rendering and virtual workstations

Fine-tuning of medium-sized models

Video transcoding and streaming

RTX PRO 6000 (Server)

Enterprise Blackwell GPU built for demanding professional AI and visualization workloads.

From₦808.16/hour
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80816 credits/hour (1 credit = ₦0.01). Billed only while your instance is running.

96GB VRAM

Recommended for:

Large-model inference and fine-tuning

Video processing and streaming

Engineering simulations and scientific computing

Intensive 3D rendering and visualisation

RTX 4090

Unbeatable price-to-performance for experimentation and smaller workloads - the ideal entry into GPU computing.

From₦511.84/hour
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51184 credits/hour (1 credit = ₦0.01). Billed only while your instance is running.

24GB VRAM

Recommended for:

Development and experimentation

AI image and video generation

3D rendering

Inference for small and medium models

Not sure what to choose?
Browse use cases to find your recommended GPU.
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Explore what you can do with GPU power

From your first model to production inference, run demanding GPU workloads without buying hardware or justifying CapEx.

Chat and LLM inference

Power chatbots, copilots, and APIs with low-latency GPU performance, available around the clock. Use Ollama and Open WebUI, or bring your own model with vLLM or LangChain.

Recommended GPU: L40S
Serve models up to 30B parametersLaunch Ollama in one clickSimple hourly pricing
Deploy for inference

Train & fine-tune models

Train custom models and fine-tune LLMs with dedicated VRAM. Checkpoints persist across restarts, so long-running jobs can stop and resume without losing progress.

Recommended GPU: A100 80GB
96GB VRAMPersistent checkpointsBuilt for large model training
Deploy for AI training

Build & explore with AI

Spin up a GPU instance and set up your own environment in minutes. Connect through your browser or terminal, then start iterating right away.

Recommended GPU: RTX 4090
Full root access to install your own stackBrowser or SSH terminal accessAffordable enough to run all day
Start building

Generate images & video

Run Stable Diffusion, ComfyUI, and rendering jobs with enough VRAM for high-resolution output and batch processing.

Recommended GPU: RTX 4090
Enough VRAM for batch image jobsFast, affordable renderingBuilt-in Stable Diffusion support
Deploy for generation

Process & encode video

Encode, transcode, and render video at high throughput with hardware acceleration, without tying up your own machines.

Recommended GPU: RTX PRO 6000 (Server)
Ninth-generation NVENC for fast, high-quality encodingFull-speed 8K encodingEncoding that runs independently of your CPU
Deploy for encoding

Start faster with ready-made apps

Launch preconfigured apps in one click, skip manual setup, and get straight to work.
Start now
Start faster with ready-made apps
Only pay while your GPU is running

Only pay while your GPU is running

GPUs are billed hourly using credits from one shared balance. Add credits as needed, destroy your instance when you're done, and keep any unused credits for later.

Why choose Hostinger GPU for AI workloads

Pay only for what you use

Per-minute billing means you only pay for the compute you use.

Ready in about 30 seconds

Launch preconfigured apps without installing drivers, containers, or dependencies.

Manage from one dashboard

Monitor usage and manage your instances whenever you need.

Your workload is ready. So are the GPUs.

Launch on dedicated GPUs in seconds. Pay by the hour, with no long-term contract or hardware to buy.
Start now
Your workload is ready. So are the GPUs.

Hostinger GPU FAQs

Find answers to the most frequently asked questions about Hostinger GPU.
Yes. GPU instances are billed by the hour in credits, and you're only charged while an instance is running. Stop it whenever you're done, there's no minimum commitment or long-term contract.
Destroying an instance is permanent and cannot be undone. Anything not saved to persistent storage is lost. Rebooting, by contrast, restarts the instance without deleting it, your files and setup stay intact.
It depends mostly on model size. Smaller models and image generation run well on RTX 4090 or L40S, larger models and serious training benefit from A100 or B200's extra VRAM. If you're not sure, our GPU picker matches your workload to the right option.
Both. Every instance comes with full terminal and SSH access, so you can install anything you need. If you'd rather skip setup, one-click apps like Ollama are ready to deploy from the start.
Availability changes in real time based on demand and varies by region. We show live availability before you deploy, so you'll always know what's actually in stock rather than finding out after committing.
Renting a GPU means accessing high-performance graphics processing power over the cloud instead of buying the physical hardware. You pay only for the compute time you use, by the hour or even by the second, and the provider handles maintenance, cooling, and driver updates. It's a common choice for AI training, machine learning inference, 3D rendering, and other tasks that need heavy processing power without the upfront cost of owning a GPU.

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