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NexGPU

A global distributed GPU network

Compute that flows like water

NexGPU aggregates distributed GPU supply worldwide, from consumer cards to datacenter silicon. Private LLM deployment, training, video rendering and AI video generation — billed by the hour, deployed in one click, elastic from one card to a multi-node cluster. Best prices anywhere, and templates complete enough that a first-timer gets running fast.

Same GPU, 60% below competing clouds.See the sources

Get startedSee pricing
Start anytime
Billed by the hour, monthly plans available, and nothing charged while stopped.
Templates for everything
One-click deploy for private LLMs, image and video generation and AI training.
Support that answers
Bilingual support around the clock, straight over Telegram. No ticket queue.
Private and secure
Every instance is end-to-end encrypted.

02

Live GPU rates

1,175 verified nodes across 51 countries, priced by supply and demand.

  • H200

    Datacenter

    140GB VRAM

    17 available

    from$6.660/hr

    Rent

  • H100 SXM

    Datacenter

    80GB VRAM

    16 available

    from$3.582/hr

    Rent

  • A100 SXM4

    Datacenter

    80GB VRAM

    22 available

    from$1.088/hr

    Rent

  • RTX 5090

    Consumer

    32GB VRAM

    107 available

    from$0.723/hr

    Rent

  • RTX 4090

    Consumer

    24GB VRAM

    130 available

    from$0.540/hr

    Rent

  • RTX 3090

    Consumer

    24GB VRAM

    66 available

    from$0.193/hr

    Rent
View all 1,175 offers

03

Same GPU, 47%–68% below AWS

Each vendor's published on-demand list price, divided by GPU count where sold per node.

NexGPU on-demand per-GPU hourly rates compared with AWS, CoreWeave and Lambda
GPUNexGPUAWSCoreWeaveLambdavs AWS
H100 SXM80GB$3.582$6.88$6.16$3.99−47%
H200141GB$6.660not published$6.31cluster only—
A100 SXM80GB$1.088$3.43$2.70$1.99−68%
RTX 5090 · RTX 4090Consumer$0.540fromNot offered by any of the three
Sources ▾
  • H100 SXM — AWS p5.48xlarge $55.04 ÷ 8 = $6.88 · CoreWeave HGX H100 $49.24 ÷ 8 = $6.16 · Lambda 8x H100 SXM $3.99
  • A100 SXM — AWS p4de.24xlarge $27.447 ÷ 8 = $3.43 · CoreWeave A100 $21.6 ÷ 8 = $2.70 · Lambda 1x A100 SXM $1.99
  • AWS · CoreWeave · Lambda
See all pricingTalk to sales

04

Training in three steps

From picking a card to your first running job — no ops experience required.

  1. 01

    Filter for a GPU

    Filter by VRAM, price, region, reliability and bandwidth. See rentable inventory across the network in real time and lock the machine that fits.

  2. 02

    Deploy a template

    2,000+ pre-built templates cover PyTorch, vLLM, ComfyUI and Stable Diffusion — or pull your own Docker image straight from your registry.

  3. 03

    Get to work

    Connect over SSH, Jupyter or the web terminal. Automate with the API and CLI, then scale up or destroy the instance whenever you like.

No ops experience needed; first job running in minutes.

05

From one card to a cluster

One platform serving enterprise R&D teams and independent developers alike.

For enterprises

Cluster capability for enterprise AI teams

A100 / H100 / H200 and high-VRAM nodes, supporting distributed frameworks such as DeepSpeed and Megatron, with optional RDMA interconnect for large parallel scaling.

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For developers and creators

High-end GPUs you can actually afford

Rent RTX 4090, RTX 5090 and A6000 class cards by the hour from $0.540/hr — enough for Stable Diffusion work, LoRA fine-tuning, model experiments and 3D rendering.

Browse templates

The platform

A global GPU network

Distributed GPU supply aggregated worldwide, spanning consumer and datacenter cards. Single-card, multi-card and cluster deployments, scaled elastically and called on demand.

Browse solutions
  • 1,175 / 1,175 nodes verified
  • median reliability 99.53%
  • up to 14 GPUs · 2,152GB per node
  • Invoicing · PO purchasing · reserved instances

Frameworks and tools that run out of the box

  • PyTorch
  • TensorFlow
  • JAX
  • ComfyUI
  • Stable Diffusion
  • FLUX
  • vLLM
  • Ollama
  • Whisper
  • RAPIDS
  • Blender
  • Axolotl
  • Unsloth
  • LLaMA Factory

06

Popular models, one click

Weights and inference stack pre-configured — pick a card and launch.

  • DeepSeek V4

    Reasoning · MIT

    DeepSeek · 1M

    • Flash · 3-bit110GB
    • Flash · 4-bit162GB
    • Flash · 8-bit169GB
    • Pro · Q2_K420GB

  • Qwen3.8

    Multimodal · Apache 2.0

    Alibaba Qwen · 262K → 1M

    • 27B · INT420GBRTX 4090
    • 27B · INT836GBRTX A6000
    • 27B · FP1664GBA100 / H100
    • Max · 量化420GB

From $0.193/hr, billed hourly, destroy any time.

Browse all templates

07

A global compute network

51 countries and regions — pick a node close to you, or pin a region.

  • United States395
  • Canada130
  • South Korea91
  • Japan50
  • Czechia44
  • Chinese mainland42
  • Norway39
  • Taiwan36
  • United Kingdom33
  • Vietnam29
  • Spain26
  • Hungary19

39 further countries and regions · 124 nodes

08

Frequently asked questions

The things worth knowing about billing, deployment and data before you start.

How does NexGPU bill?
By the hour, for as long as the instance runs. Destroy it whenever you like — there is no long-term contract and no minimum spend. Storage is priced separately per GB per month. Enterprise accounts can add reserved instances, monthly or annual commitments and dedicated pools, with pricing that scales down with volume.
Why is this so much cheaper than AWS?
NexGPU aggregates distributed GPU supply worldwide rather than building single-region datacenters, so it does not carry a traditional cloud's facility and redundancy overhead. Consumer cards such as the RTX 4090 also deliver far better price-performance than datacenter parts on most fine-tuning and inference work — and the traditional clouds do not offer that category at all.
How long does deployment take?
Once you pick an instance, booting from a pre-built template usually completes in a few minutes, depending on image size and node bandwidth. There are 2,000+ templates covering PyTorch, vLLM, ComfyUI and Stable Diffusion, and you can pull your own Docker image instead.
Is my data and model safe?
Instances are dedicated to you; data written while an instance runs lives on the node you rented and is released when you destroy it. Enterprise plans add data isolation, private networking and dedicated clusters. We recommend keeping an off-site backup of anything important. The Terms of Service and Privacy Policy govern the specifics.
How do I connect?
SSH, Jupyter Notebook and a browser terminal are all supported, along with a REST API and CLI for automation that integrates with your existing CI/CD.
Can I run multi-node distributed training?
Yes. The network offers 2-, 4-, 8- and up to 16-GPU nodes with as much as 1,432 GB of VRAM in a single node, supporting DeepSpeed, Megatron and similar frameworks. RDMA interconnect is available on enterprise plans.

Start building on NexGPU

Enterprise R&D team or solo developer — either way, your first job can be running in minutes.

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Sign up to browse live network pricing. No payment method required.