Get Started Login
  • Home
  • GPU Cloud for AI & Machine Learning
Cloud Use Case

Cloud GPU for AI & Machine Learning

On-demand NVIDIA GPUs for AI/ML training, inference, and experimentation. H100, H200, L40S, A16, RTX 6000 Ada. Fixed pricing, no egress fees.

$4/mo
Starting price
24
Global Data Centers
99.9%
Uptime SLA
24/7
Human Support

Why Choose OMC Cloud for AI/ML

AI and ML workloads have unique requirements: GPU compute for training, fast NVMe storage for datasets, and predictable pricing for budget planning. AWS and GCP GPU pricing is volatile — spot instances get interrupted mid-training, on-demand costs $30+/hour, and egress fees punish you for downloading your own model weights.

OMC Cloud offers NVIDIA H100 (80GB HBM3), H200, L40S (48GB), A16, and RTX 6000 Ada GPUs with fixed monthly pricing. No spot interruptions, no bidding, no egress fees. Download trained models, datasets, and checkpoints freely. Pre-configured for PyTorch, TensorFlow, and JAX — or install from scratch with full CUDA root access.

Key Benefits

01
NVIDIA H100 & H200
Latest-generation GPUs with 80GB HBM3. Fastest training and inference available.
02
Fixed Monthly Pricing
No spot interruptions, no bidding, no hourly volatility. Budget with confidence.
03
Zero Egress Fees
Download models, checkpoints, datasets without per-GB charges. Your data is yours.
04
Full CUDA Control
Custom CUDA, cuDNN, NCCL versions via root access. No vendor restrictions.
05
Pre-Configured Environments
PyTorch, TensorFlow, JAX ready — or start from clean Ubuntu and build your own.
06
NVMe Dataset Storage
Fast data loading for large training datasets. No IOPS limits or throttling.
07
Training + Inference
Train on H100, deploy inference on L40S. Full lifecycle on one platform.
08
24/7 ML Support
Infrastructure experts who understand GPU workloads — not just generic VM support.

How It Works

1

Choose

Select data center, CPU, RAM, storage, and OS.

2

Deploy

Server ready in under 60 seconds via console or API.

3

Go Live

Install your stack, configure, launch with 24/7 support.

GPU Cloud: OMC vs AWS vs Google Cloud

FeatureOMC CloudAWS (EC2 GPU)Google Cloud (A3/G2)
PricingFixed monthlyOn-demand $10-30/hr or spotOn-demand $8-25/hr
Spot InterruptionsNever — fixed instancesYes, mid-training killsYes, preemptible
Egress FeesZero$0.09/GB$0.12/GB
GPU OptionsH100, H200, L40S, A16, AdaA100, H100, T4, V100H100, L4, T4, A100
CUDA ControlFull root accessAMI-based, limitedContainer-based
Setup60 secondsMinutes to hoursMinutes
Support24/7 human, includedPaid tiersPaid tiers
Billing ComplexityOne line itemCPU + GPU + storage + egress + ...Similar to AWS

Recommended Configurations

GPU instances with fixed monthly pricing. No hidden fees.

Experimentation
$49/mo
per month
  • • NVIDIA L40S (48GB)
  • • 4 vCPU, 16 GB RAM
  • • 100 GB NVMe
  • • Fine-tuning (LoRA)
  • • Inference serving
Deploy Now
Training
$89/mo
per month
  • • NVIDIA L40S (48GB)
  • • 8 vCPU, 32 GB RAM
  • • 200 GB NVMe
  • • Full fine-tuning
  • • 7B-34B models
Deploy Now
Large Scale
$199/mo
per month
  • • NVIDIA H100 (80GB HBM3)
  • • 16 vCPU, 64 GB RAM
  • • 500 GB NVMe
  • • 70B+ model training
  • • Multi-GPU available
Deploy Now

Technical Specifications

GPUs: NVIDIA H100 (80GB), H200, L40S (48GB), A16, RTX 6000 Ada
Frameworks: PyTorch 2.x, TensorFlow, JAX, DeepSpeed, FSDP
Quantization: GPTQ, AWQ, GGUF, bitsandbytes
CUDA: Full root, custom CUDA/cuDNN/NCCL versions
Storage: NVMe SSD, no IOPS limits
Network: Up to 40 Gbps
OS: Ubuntu 22.04/24.04 recommended
Models: Llama 3, Gemma 4, Mistral, SDXL, FLUX, custom

Frequently Asked Questions

Which NVIDIA GPUs are available?+

H100 (80GB HBM3), H200, L40S (48GB GDDR6X), A16, and RTX 6000 Ada. H100 is best for large-scale training; L40S is optimal for inference and fine-tuning.

How does pricing compare to AWS?+

Significantly cheaper for sustained workloads. An H100 on OMC Cloud is $199/mo fixed. AWS on-demand p5.xlarge is $30+/hr ($21,600/mo). Even reserved instances are 5-10x more expensive.

Can I fine-tune Llama 3 or Gemma 4?+

Yes. L40S (48GB) handles LoRA/QLoRA fine-tuning of 7B-34B models. H100 (80GB) handles full fine-tuning of 70B+ models.

Are there egress fees when I download my model?+

No. Zero egress fees. Download trained models, checkpoints, and datasets freely at any time.

Can I use PyTorch 2.x with torch.compile?+

Yes. Full root access means install any PyTorch version with torch.compile, FlashAttention, and custom CUDA extensions.

What about multi-GPU training?+

Multi-GPU configurations available on single nodes. Use NCCL for distributed training. Contact sales for multi-node clusters.

Is there a free trial for GPU instances?+

Yes. 30-day free trial available for GPU instances. Test your training pipeline before committing.

Can I switch between GPU types?+

Deploy a new server with a different GPU type and migrate your code and data. Our team can assist with the transition.

Customers Also Deploy

LLM Training
Fine-tune specific LLM models
LLM Inference
Deploy models for production
Stable Diffusion
Image generation on GPU

Start Your 30-Day Free Trial

Deploy in under 60 seconds. No credit card required.

Get a Personalized Cloud Quote

Our cloud expert will contact you as soon as possible with a solution tailored to your workload.

  • ✓ Free consultation — zero commitment
  • ✓ Custom pricing for your exact workload
  • ✓ 30-day free trial included
  • ✓ 24/7 human support from day one
Since 1995
Cloud infrastructure
24
Global Data Centers
99.9%
Uptime SLA

Talk to an Expert

3 fields. 30 seconds. That's it.

    No commitment · Quick response guaranteed
    [email protected] · 074-7300078

    The company

    Products

    Solutions

    2025 OMC, Inc., all rights reserved