Innomium Compute
GPUs for training and inference.
Rent B200, B300, H100, H200, RTX 5090, and A100 by the hour — marketplace rates, fast deployment, and billing that stops when your instance does.
Blackwell·NVIDIA B200 — frontier training & long-context inference.
- Inventory
- Live worldwide
- Billing
- Metered by runtime
- Deploy
- Ready in minutes
Lower cost
Pay for measured runtime at the rate shown before launch. Top up with USDT, deploy, and stop whenever the job is done.
Faster to start
Pick a GPU, deploy in minutes, and open a browser terminal. No ticket queues. No multi-week onboarding.
Built for reliability
Live global inventory, clear availability, optional auto-termination, and a wallet guard that stops workloads when funds run out.
Hardware
From RTX to Blackwell
Live inventory across consumer and datacenter GPUs. Filter the catalog the way you shop a marketplace — not a sales call.
Blackwell
Available now
NVIDIA B200
Frontier training & long-context inference with 192GB-class memory bandwidth.
View availability →
Blackwell Ultra
Available now
NVIDIA B300
Next-wave Blackwell Ultra for dense inference and AI reasoning workloads.
View availability →
Hopper
Live inventory
NVIDIA H100
The workhorse for fine-tunes, RL, and production inference — still the volume favorite.
View availability →
Hopper
Live inventory
NVIDIA H200
Higher HBM for long-context models and larger training batches.
View availability →
GeForce
From low $/hr
GeForce RTX 5090
Consumer Blackwell for experiments, LoRA, and creative workloads at low $/hr.
View availability →
Ampere
Live inventory
NVIDIA A100
Proven Ampere for production jobs and cost-efficient training.
View availability →
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Workflow
Three steps to a running GPU
01
Browse live inventory
Filter by GPU, location, CUDA, network speed, and price. See Innomium hourly rates up front.
02
Deploy in minutes
Choose a template, attach a volume if you need persistence, and launch.
03
Train, ship, stop
Use the browser terminal or your usual SSH workflow. Stop when done — billing follows runtime.
Workload first
Start with the model, not the GPU name.
Explore in notebooks, adapt models with fine-tuning, run full training, evaluate checkpoints, or host private inference. Innomium filters hard memory compatibility first, then ranks available capacity by final price, reliability, network, and environment readiness.
GPU families
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Locations
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Live price range
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Verified CVM inventory
None currently verified
Compatibility estimate—not a performance benchmark.
Inside the workspace
A visible path from capacity to useful work.
01 · Catalog
Filter synchronized GPU inventory by workload, VRAM, location, price, reliability, network, and verified CVM capability.
02 · Launch
Review environment, SSH keys, persistent storage, ports, auto-termination, reserve, and final all-inclusive rate.
03 · Workspace
Follow readiness, copy direct SSH, open the browser terminal or Jupyter, and monitor cost and runway.
04 · Persist
Write durable data to one attached external volume. Terminating the instance deletes only its local disk.
Environment library
Curated when you want speed. Custom when you want control.
Templates capture the image tag or digest, entrypoint, command, environment references, internal ports, mount path, and CUDA requirement. Secrets are referenced—not rendered back to the browser.
Persistence contract
Local instance disk
Fast working storage. Ephemeral. Permanently removed when you terminate.
External volume
Attached to one instance at a time. Survives termination for the next workspace.
Security
Know the isolation boundary.
Workloads run on vetted third-party infrastructure. Standard non-CVM hosts may be accessible to infrastructure operators. Where upstream metadata explicitly verifies CVM capability, you can filter for it. Unknown stays “Not verified.” Keep long-lived secrets outside rented hosts.
Security model →Transparent billing
One final Innomium rate.
We hold one hour at launch, meter in one-minute operational intervals from the actual billable timestamp, show balance runway, warn as funds run low, and begin termination with a safety buffer. Unused reserve is released after confirmed termination.
Pricing and reserves →Fund with USDT
TRON mainnet, clearly identified.
- 1. Create a deposit invoice.
- 2. Send official USDT-TRC20 to its unique address.
- 3. Watch confirmations and receive the actual confirmed amount as compute credit.
Wrong-token or wrong-network transfers are not automatically recoverable. Credits are prepaid, non-transferable, and non-withdrawable.
Operate with context
Documentation, support, and status stay close to the workload.
Every failed request keeps the next action visible: retry, understand what happened, or open a ticket with sanitized diagnostics.
Is capacity dedicated?
The catalog describes the machine allocation and any supported GPU split. Treat unverified fields as unknown.
When does billing begin?
At the actual infrastructure billable start, recorded separately from your click and workspace-ready time.
Does terminate pause an instance?
No. Terminate is destructive. Public v1 does not offer resumable stop or snapshots.
Can I use another token or chain?
No. Public v1 accepts only official USDT-TRC20 on TRON mainnet.
Insights
Compute notes & platform updates
data-cloud
Cloud Architecture for AI Workloads: Separate Experiments, Platforms, and Products
Design identity, networking, data, compute, deployment, observability, cost, and recovery around distinct AI workload classes.
data-cloud
AI Inference Cost Optimization: Measure Latency, Throughput, and Quality Together
Optimize model choice, context, batching, caching, quantization, routing, hardware, and concurrency without concealing quality loss.
data-cloud
Kubernetes GPU Workloads in Production: Scheduling Is Only the Beginning
Plan drivers, device plugins, node pools, images, storage, topology, quotas, telemetry, upgrades, isolation, and failure recovery.
Start on a GPU in minutes.
No annual contracts. Crypto top-ups. Stop when the job finishes.