AI / GPU Infrastructure

Managed GPU Infrastructure for AI Teams

Deploy your LLM or training job on H100 and A100 GPUs in India. We handle CUDA, vLLM, and 24/7 ops. You own the model and the results.

Talk to a GPU Engineer See GPU Hardware
500+ GPUs via E2E Networks India datacenter (Mumbai DPDP) 5,000 INR free trial credits 17 years infra ops since 2009
Running production workloads for
Revolt MotorsPC JewellerRR KabelImpresarioIntentwiseLoomBhimaBGaussMitutoyo
500+
GPUs Available via E2E
3–5x
Cheaper Than US GPU Clouds
2–7 days
Provisioning Lead Time
24/7
Managed Ops & Monitoring
0
Per-Token Charges

What ZenoCloud Manages

Give us your model. We handle everything else — from bare metal to the API endpoint.

GPU Provisioning

Hardware racked, tested, and benchmarked. NVIDIA-SMI health check and memory bandwidth validation before handoff. CUDA 12.4 + cuDNN 9.0 stack.

Runtime Installation

vLLM, Ollama, TGI, or TorchServe installed and configured for your model family. CUDA, driver compatibility, and NCCL all handled.

OpenAI-Compatible API

You get an HTTPS endpoint at your subdomain. Drop-in replacement for openai.api_base — no application code changes required.

Monitoring & Alerting

Prometheus + Grafana dashboards for GPU utilization, request latency (p50/p95/p99), queue depth, KV cache, and error rate.

Security & Data Privacy

Single-tenant bare metal. Your inference requests never touch ZenoCloud logging. LUKS encryption at rest. DPA available on request.

Auto-Restart & Scaling

systemd restarts vLLM on crash within 10 seconds. Horizontal scaling via nginx load balancer when concurrency grows beyond single GPU.

GPU Hardware Available

All GPUs are in India datacenter (Mumbai via E2E Networks). Managed pricing includes hardware, power, bandwidth, OS, runtime, and 24/7 ops — not just GPU rental.

L4
VRAM 24GB GDDR6
FP16 TFLOPS 120
Best For 7B models (FP16), embeddings, dev/test
Reserved / Month ₹30,000 ($360)
L40S
VRAM 48GB GDDR6
FP16 TFLOPS 362
Best For 13B models, Stable Diffusion XL, image gen
Reserved / Month ₹75,000 ($900)
A100 80GB
VRAM 80GB HBM2e
FP16 TFLOPS 312
Best For 70B inference (FP16), Llama 3.1 70B, Mixtral
Reserved / Month ₹1,50,000 ($1,800)
H100 SXM
VRAM 80GB HBM3
FP16 TFLOPS 989
Best For 70B+ training, 2x A100 throughput, large clusters
Reserved / Month ₹1,50,000 ($1,800)
H200 SXM
VRAM 141GB HBM3e
FP16 TFLOPS 989
Best For 405B+ models, DeepSeek V3, multi-GPU clusters
Reserved / Month ₹2,00,000 ($2,400)

* Reserved 3-month pricing. On-demand +25%. H100/H200 multi-node NVLink clusters on custom pricing. Contact for A100 40GB and RTX 4090 configs.

Pricing

Managed AI Infrastructure Packages

Pricing includes GPU, OS, runtime, monitoring, and 24/7 ops. Not raw GPU rental — a deployed, running system.

Starter
/month

For indie builders, POC stage, and dev/test deployments

  • Single GPU: L4 (24GB) or RTX 4090 (24GB)
  • vLLM or Ollama runtime deployment
  • OpenAI-compatible API endpoint
  • Basic Grafana monitoring dashboard
  • Email support + documentation
  • 5,000 INR free trial credits
Start Free Trial
Most Popular
Growth
/month

For funded startups and production AI workloads

  • Multi-GPU: A100 40GB or 80GB
  • Auto-scaling + nginx load balancing
  • Full Prometheus + Grafana monitoring with alerting
  • Model optimization: quantization, batching
  • Slack/email support + onboarding call
  • Monthly performance reports
Talk to an Engineer
Scale
/month

For Series A+ teams with heavy inference or training workloads

  • H100 / H200 SXM, multi-node NVLink fabric
  • Custom SLA + dedicated ML ops engineer
  • Full ML ops: training + inference pipelines
  • Custom model fine-tuning environments
  • 24/7 named engineer, 15-min P1 response
  • Quarterly architecture reviews
Scope a Custom Plan

All tiers include 5,000 INR free trial credits. No long-term contracts required at Starter and Growth. Scale tier requires 3-month minimum commitment.

Managed GPU vs Raw GPU Rental

RunPod and Lambda Labs give you a server. ZenoCloud gives you a running, managed production deployment — in an India datacenter.

RunPod / Lambda Labs
ZenoCloud Managed
GPU hardware provisioning
OS + CUDA stack setup
vLLM / runtime installation
Model download and configuration
OpenAI-compatible API endpoint
Grafana monitoring dashboard
24/7 ops team (crash recovery)
Horizontal scaling support
India DC (DPDP compliance)
INR billing, no FX risk
Self-serve control panel
See Managed Pricing
FAQ

Frequently Asked Questions

How much does it cost to self-host an LLM in India?
A 7B model (Mistral 7B, Llama 3.1 8B) on an L4 GPU costs ₹30,000/month ($360). A 70B model (Llama 3.1 70B) on A100 80GB costs ₹1,50,000/month ($1,800). H100 clusters for 405B+ models start at ₹2,00,000/month. All prices include hardware, OS, runtime, monitoring, and 24/7 ops — not just hardware rental.
What is the difference between managed GPU and raw GPU rental?
Raw GPU rental (RunPod, Lambda Labs) gives you root access to a server. You install CUDA, download your model, configure vLLM, set up monitoring, and handle incidents. ZenoCloud managed GPU includes all of that plus 24/7 ops, automated crash recovery, and an OpenAI-compatible API endpoint ready in 2–7 days.
Which GPU should I choose for my model?
7B models (FP16): L4 or RTX 4090. 13B models: L40S or A100 40GB. 70B models (FP16): A100 80GB or H100. 70B models quantized to 4-bit: A100 40GB. 405B+ models (Llama 3.1 405B, DeepSeek V3): H100 or H200 NVLink cluster. We recommend the right GPU after a 15-minute scoping call based on your concurrency and budget.
Does ZenoCloud satisfy DPDP Act 2023 data localization requirements?
Yes. All inference runs in our Mumbai datacenter within Indian jurisdiction. Your inference payloads and responses stay on your GPU server — we collect only infrastructure metrics (GPU utilization, container health). We sign a Data Processing Agreement confirming no data is used for training or leaves India.
How long does GPU provisioning take?
Single-GPU setups (L4, RTX 4090) are ready in 2–3 business days. A100 40GB/80GB single-node takes 3–5 days. H100 / H200 multi-node NVLink clusters take 5–7 days. We confirm lead time during the scoping call.
Can I bring my own fine-tuned model or HuggingFace checkpoint?
Yes. Provide a HuggingFace Hub repo URL (public or private with read token), an S3-compatible bucket URL, or a local .safetensors checkpoint. We upload the model to your NVMe storage, encrypted at rest with LUKS, and configure vLLM. LoRA / PEFT adapters are merged or applied at runtime.
Is there a free trial?
Yes — 5,000 INR in free GPU credits, no credit card required. Credits cover approximately 100 hours on an L4 GPU or roughly 20 hours on an A100. Talk to a GPU engineer to activate your trial and scope the right deployment for your model.
Pre-revenue, real infrastructure

Deploy Your First LLM in 5 Business Days

Tell us your model, concurrency requirements, and compliance needs. We'll scope a deployment plan and get you running with 5,000 INR in free trial credits.

Talk to a GPU Engineer Claim ₹5,000 GPU Credit
+1 714 242 5683 · +91 99991 08033 · support@zenocloud.io

Explore AI Infrastructure

Sub-products within the AI / GPU pillar — from inference and LLM hosting to model training and raw GPU hardware.

LLM Hosting

Self-host Llama, Mistral, DeepSeek on dedicated GPUs

AI Inference Hosting

vLLM, TGI, Triton — production inference at scale

AI Model Training

Fine-tuning and training on A100 / H100 clusters

ML Infrastructure

Full ML ops stack: storage, scheduling, monitoring

GPU Hosting Catalog

L4, L40S, A100, H100, H200 — specs and pricing

H100 GPU Servers

NVIDIA H100 80GB SXM — specs and availability