●Deploy GPU instances on demand●Per-second billing — pay only for what you use●RTX, A100, and H100 GPUs available●No subscriptions — no commitments●Connect from any device, anywhere●Instant provisioning — up and running in seconds●Deploy GPU instances on demand●Per-second billing — pay only for what you use●RTX, A100, and H100 GPUs available●No subscriptions — no commitments●Connect from any device, anywhere●Instant provisioning — up and running in seconds●Deploy GPU instances on demand●Per-second billing — pay only for what you use●RTX, A100, and H100 GPUs available●No subscriptions — no commitments●Connect from any device, anywhere●Instant provisioning — up and running in seconds
[ sys.gpu.ready ]

Supercharged GPU Power, Instantly

Bare-metal GPU instances with per-second billing. No cold starts, no hidden fees. Deploy H100s, A100s, and consumer GPUs in under 10 seconds.

GPU-NODE-7f3a
NVIDIA A100-SXM4-80GB
GPU Utilization72% / 100%
GPU Temperature64°C / 100°C
VRAM Usage18.4 GB / 80 GB
CPU Load34% / 100%
1,980 MHz
Clock Speed
1,593 MHz
Memory Clock
287W / 400W
Power Draw

Build Your Rig

Configure your perfect GPU instance. Pay only for what you use.

$ turbo configure --interactive
GPU ModelRTX 4090
RAM64 GB
NVMe Storage500 GB
gpu: RTX 4090
ram: 64 GB DDR5
storage: 500 GB NVMe
os: Ubuntu 22.04 + CUDA 12.2
network: 10 Gbps

Your Price

$1.17
PER HOUR
$28.03
Per Day
$841
Per Month
Per-Second Rate
$0.000324

Live Cost Simulator

See exactly how our per-second billing works. Start the timer and watch the cost tick up in real time.

$0.000000
0s elapsed · RTX 4090 @ $0.000324/sec

What Can You Run?

Popular AI models and their recommended GPU configurations

Stable Diffusion XL

VRAM: 8 GB
Min: RTX 4060 Ti+
Speed: ~2s/image

LLaMA 2 70B

VRAM: 40 GB
Min: A100 40GB+
Speed: ~45 tok/s

Whisper Large v3

VRAM: 10 GB
Min: RTX 4070 Ti+
Speed: ~30x realtime

CodeLlama 34B

VRAM: 20 GB
Min: RTX 4090+
Speed: ~60 tok/s

Mixtral 8x7B

VRAM: 48 GB
Min: A100 80GB+
Speed: ~55 tok/s

FLUX.1 Pro

VRAM: 24 GB
Min: RTX 4090+
Speed: ~4s/image

GPT-NeoX 20B

VRAM: 45 GB
Min: A100 80GB+
Speed: ~35 tok/s

SAM (Segment Anything)

VRAM: 6 GB
Min: RTX 4060 Ti+
Speed: ~100ms/mask

Developer Stories

How developers use TurboGPU

“Trained a 7B parameter model in a fraction of the time. Per-second billing means I only pay for actual compute.”

from turbogpu import Instance gpu = Instance("H100", region="us-east") gpu.run("python train.py --model llama-7b") # Training complete: 2h 47m
— TurboGPU User
Machine Learning

“I render 4K cinematics overnight. The cost is a fraction of what I'd pay with a dedicated workstation.”

$ turbo launch --gpu rtx4090 --storage 1tb $ turbo exec blender -b scene.blend -o //render -a # Rendered 2,400 frames in 6h 12m # Total cost: $6.14
— TurboGPU User
3D & Creative

“The pricing is transparent and the GPUs are fast. Exactly what I needed for distributed training experiments.”

import turbogpu as tg cluster = tg.Cluster(gpus=4, type="A100-80GB") result = cluster.distributed_train( model="stable-diffusion-xl", dataset="laion-5b-subset" ) # Loss converged at epoch 12
— TurboGPU User
AI Research

Why Not AWS?

Transparent pricing. No surprises. No egress fees.

ProviderA100 80GBH100 80GBSpin-up TimeMin BillingEgress
TurboGPUBEST$1.89/hr$3.99/hrInstantPer secondFree
AWS (p5)$4.10/hr$8.22/hr2-5 min1 hour$0.09/GB
GCP (a3)$3.67/hr$7.21/hr1-3 min1 minute$0.12/GB
Azure (ND)$3.80/hr$7.85/hr3-8 min1 hour$0.087/GB

* Prices shown are indicative and may vary. See our pricing page for current TurboGPU rates. Competitor rates sourced from public pricing pages, March 2026, and may have changed.

Ready to Accelerate?

Spin up a GPU instance in under 10 seconds. Pay only for what you use — starting from $0.08/hr.

$ pip install turbogpu && turbo launch --gpu a100