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Zming Technology

GPU cloud for AI workloads.

Bare-metal GPU servers, managed inference, and model hosting — plus third-party GPU maintenance so capacity and uptime stay within reach.

Operator-run infrastructure Quoted in USD No training on Customer Content
View live capacity → Three ways to run

Customer workloads, prompts, model data, outputs, stored files, and Customer Content are not used to train Zming or third-party models unless expressly agreed in writing.

FacilitiesTier III+ hostingColocation & GPU-dense racks
GPU optionsRTX PRO · H100 · H200 · B200Available, reserved, or procurement
Ops24/7 responseBreak/fix & remote hands
Fleet1000+ GPUs deployed99.99% SLA target

§ 02 · Live capacity · zm-us-1

Inventory

Live capacity

Public availability changes frequently. For reserved capacity, contact us for current GPU inventory, term pricing, and deployment timelines.

GPU classStatusBest for
RTX PRO 6000 Blackwell Available · private capacity Inference, rendering, CUDA, model hosting
H100 / H200 Reserved · on request Training, fine-tuning, high-throughput inference
B200-class systems Procurement-based Frontier model training and large-scale inference
GB200 / NVL-class systems Large reserved deployments Rack-scale AI infrastructure

Availability depends on procurement, reservation term, cooling requirements, and deployment schedule. Legacy A100-class capacity may be available on request.

Platform

What runs here.

A GPU compute platform for inference, fine-tuning, rendering, CUDA workloads, model hosting, and private AI deployments.

8 workload classes · served from zm-us-1

JOB-01

LLM inference

vLLM, TGI, TensorRT-LLM. Token-billed, endpoint-based, or pinned-GPU.

JOB-02

Fine-tuning

Full-parameter, LoRA, and QLoRA on reserved Hopper or Blackwell-class capacity.

JOB-03

Batch AI jobs

Overnight runs, queued jobs, and scheduled compute. Billed per GPU-hour or reserved term.

JOB-04

Computer vision

YOLO, DINO, SAM, custom CNNs. Single-node or pipeline.

JOB-05

Rendering

Octane, Redshift, Blender Cycles, and GPU rendering on RTX-class infrastructure.

JOB-06

CUDA / HPC

Direct CUDA, NVLink-capable systems, high-speed networking, and bare-metal access where available.

JOB-07

Managed endpoints

Your model, our serving stack, private API endpoint.

JOB-08

Private AI deployments

Dedicated infrastructure. Your weights, your data — never shared, never used for training.

Frameworks: PyTorch · JAX · TensorFlow · vLLM · TGI · TensorRT · Triton · Ray

Delivery

Three ways to run.

From hardware you can SSH into, to a single HTTPS call — same operator, same documentation.

zm-us-1 · all three tiers · single billing entity

01 · Bare-Metal GPU Cloud

Dedicated servers with root access

For teams that need full control: training, multi-node clusters, custom kernels.

  • Dedicated RTX PRO, Hopper, or Blackwell-class GPU servers
  • Root access and single-tenant deployment options
  • NVLink / high-speed networking where available
  • Hourly, monthly, or reserved capacity
From quote / GPU · hr
02 · Managed Inference

Private model endpoints

Host open-source or custom models behind private APIs. We run the serving stack; your weights stay yours.

  • Private API endpoints
  • vLLM, TGI, TensorRT-LLM
  • p50 / p95 latency reporting where available
  • Autoscale or pinned-GPU deployment options
03 · Model-as-a-Service

Ready-to-call models

LLMs, diffusion, embedding, and vision models — hosted inference without managing the stack.

  • Llama, Qwen, Mistral, embeddings, vision, diffusion
  • Hosted inference endpoints
  • Token billing or private endpoint pricing
  • Customer Content is not used for training

Why Zming

Built for teams that need AI compute without hyperscale procurement.

✓
Operator-run GPU compute and inference infrastructure
✓
Bare-metal control with dedicated deployment options
✓
Managed inference for open-source and customer-provided models
✓
Clear billing — hourly, monthly, reserved, and token-based
✓
No training on Customer Content by default
✓
Direct operator support + GPU fleet maintenance

Commercial

Same facility, four contracts.

Pick the model that matches your workload. Switch later — billing rolls up to one entity.

01 · Dedicated GPU server
Hourly · pay-as-you-go
02 · Reserved GPU capacity
Monthly · annual · custom term
03 · Managed model endpoint
Per-request · autoscaling
04 · Public API
Token billing

Configuration · RESERVED

Regionzm-us-1 · Houston, TX
GPURTX PRO 6000 Blackwell, H200, or B200-class systems
TopologySingle-node, multi-node, NVLink-capable, or high-speed fabric
CPU · RAMConfigured to workload requirements
StorageLocal NVMe or reserved shared storage
NetworkDedicated bandwidth options available
TermMonthly, annual, or custom reserved term
Quote · USD
Funding-ready paperwork available on request: service agreement, itemized invoices, workload descriptions, usage records.

Finance

Compute that your finance team can file.

Zming can provide service agreements, itemized invoices, workload descriptions, and usage records for budgeting, procurement, and rebate applications.

Service agreement

Clear scope, term, region, deliverables.

Itemized invoices

GPU-hours, model calls, storage — line by line.

Workload description

What ran, when, on which hardware.

Usage records

CSV export for internal and grant applications.

Your data is not our training data.

Zming does not use Customer Content to train Zming models or third-party models unless the customer expressly agrees in writing. Customer Content includes prompts, outputs, files, model weights, training data, fine-tuning data, hosted workloads, and other materials submitted to or generated through the Services.

Facility

Operator-run. Power-ready. Maintenance-backed.

Capacity is available through Zming-operated and partner-supported deployments, with GPU maintenance for the same fleet.

HOU-01 · primary facility

Region code
zm-us-1
GPU options
RTX PRO 6000 Blackwell · H100/H200 · B200-class procurement
Networking
High-speed fabric / InfiniBand options
Facility
Tier III+ · multi-carrier
Ops
24/7 response · spare-parts pool

Exact GPU availability depends on procurement, reservation term, cooling requirements, and deployment schedule.

Regions

zm-us-1 · online

zm-us-2 · expanding

partner capacity · on request

Address for commercial contact: 25852 Daily Asford, Houston, TX 77042

Customer stories

How teams use Zming.

Representative deployments across rental, private inference, and GPU fleet maintenance. Metrics are illustrative of outcomes we support.

LLM startups Robotics & vision Media / rendering Enterprise IT Research labs
CASE · 01 Generative AI · Inference

Private vLLM endpoints for a product launch

A SaaS team needed H100 inference without a hyperscale sales cycle. Zming stood up pinned-GPU endpoints with p95 latency reporting and reserved capacity for launch week.

  • 8× H100 reserved · 90 days
  • < 2 days to first endpoint
  • Zero training on Customer Content
CASE · 02 Industrial AI · Fine-tuning

LoRA fine-tunes on reserved Hopper capacity

An industrial robotics company ran overnight QLoRA jobs on reserved H200 nodes, with itemized GPU-hour invoices for procurement and internal cost allocation.

  • 4× H200 monthly reserved
  • CSV usage exports for finance
  • SSH bare-metal control
CASE · 03 Ops · GPU Maintenance

Post-warranty break/fix for a dense GPU rack

When OEM queues stretched days, Zming provided 7×24×4 parts and on-site engineers for NVLink and PSU failures — extending fleet life past EoSL without an emergency refresh.

  • 7×24×4 SLA
  • First-visit oriented fixes
  • Spare pool for critical SKUs

“We needed capacity and paperwork in the same week — not a six-month cloud enterprise deal. Zming quoted reserved GPUs, stood up endpoints, and sent invoices finance could actually file.”

— Infrastructure lead, AI product company

FAQ

Questions teams ask first.

Can we rent H100 / H200 without a long contract?

Yes. On-demand and short reserved terms are available depending on inventory. For guaranteed stock, we recommend a monthly or custom reserved term.

Do you support custom Docker images and root access?

Bare-metal and dedicated nodes can include SSH/root and custom containers. Managed endpoints keep the serving stack with us while your weights stay yours.

Is Customer Content used for training?

No — not by default. Zming does not train on Customer Content unless you expressly agree in writing.

What GPU maintenance SLAs are available?

Common packages include 7×24×4, 5×9×4, next-business-day, and custom SLAs by device criticality.

Can finance get usage documentation?

Yes. Service agreements, itemized invoices, workload descriptions, and CSV usage records are available on request.

GPU Maintenance

Keep dense GPU fleets online.

Third-party break/fix, parts, and on-site ops for GPU-powered servers — post-warranty and EoSL friendly.

Break / fix & parts

GPU, PSU, NVLink bridge, and chassis components with SLA-driven dispatch.

On-site & remote hands

24×7 escalation, rack-level troubleshooting, First-Time Fix oriented workflows.

Post-warranty & EoSL

Extend useful life past OEM coverage so you refresh on your schedule.

Deployments & cooling

GPU-dense rack builds, cabling, and high-density cooling coordination.

Need reserved GPU capacity?

For reserved clusters, private inference endpoints, procurement-based Blackwell deployments, or fleet maintenance — contact Zming.

Contact engineering →

Contact

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