✓
Request Sent We'll reach out within 24 hours
GUIDED PILOT

Test your real ML workload.
$500 in credits, on us.

Egress costs −70% vs AWS. H100 from $3.04/hr.

Choose your configuration ↓
emma Cloud GPU interface: instance configuration and job queues emma Cloud GPU instance configuration ISO/IEC 27001, SOC, 99.99% Uptime SLA

GPU infrastructure across 7 clouds. One platform, no vendor lock-in.

Configure your pilot

Hours shown = how long your $500 credit runs each config

↓ START HERE
Starter Inference
NVIDIA L4 24 GB · 4 CPU · 16 GB RAM
RAG Embeddings Llama-3 8B ML experiments
714 hr
$0.70/hr
★ MOST POPULAR
Production Inference
NVIDIA L40S 48 GB · 4 CPU · 32 GB RAM
LLM API Multi-model serving Embeddings
269 hr
$1.86/hr
Fine-tuning Lab
NVIDIA A100 80 GB · 24 CPU · 220 GB RAM
LoRA / QLoRA RLHF Llama / Mistral Mid-size training
136 hr
$3.67/hr
Advanced Training
NVIDIA H100 80 GB · 16 CPU · 256 GB RAM
Transformer training HPC inference Research workloads
73 hr
$6.88/hr
↔ MAX COMPUTE
Frontier Models
NVIDIA H100 94 GB · 40 CPU · 320 GB RAM
LLM training Multimodal models ML research
72 hr
$6.98/hr

See exactly what you get

$500
Your Pilot Budget
714 hr
NVIDIA L4 24 GB · 4 CPU · 16 GB RAM
  • Dedicated engineer: setup + tuning
  • Migration support: 1 workload

Helps us prepare your activation call

Response within 24h · 15-min call

By applying, you agree to emma’s Terms and Privacy Policy.

// FAQ

Engineer to Engineer

We work as a capacity aggregator across 7+ clouds, buying reserved capacity and optimizing load across EU regional data centers — including our own infrastructure in Luxembourg. You get the same H100 or H200, but without the massive brand markup from AWS or GCP.
Most cloud bills include a hidden egress tax — up to 40% of your total spend. Through the emma private backbone, we built a private network between providers that cuts egress costs by up to 70%. Transfer terabytes of model weights or datasets between nodes without the hyperscaler markup.
We offer both. Bare Metal for tasks where every millisecond matters (e.g. training LLMs from scratch), and optimized instances for inference. All configurations support the latest generation NVLink for maximum GPU-to-GPU bandwidth.
Our images already include PyTorch 2.5+, CUDA 12.x and vLLM. No hours wasted on driver setup. After account approval and $500 credits are applied, deployment takes minutes.
We operate on an on-demand model. No mandatory subscription, no hidden fees. Once the welcome credits run out, you continue at the same low rates you saw in the table.