Llama 3 8B inference / SDXL / ComfyUI
- GPU sizing starting point
- RTX 4090 24GB
- What to validate
- Precision, context length, batch size and peak VRAM.
Size AI inference, training and rendering around GPU memory, software compatibility and job duration. Compare available hardware and billing options.
Compare GPU configurations and billing options for your workload.
| Plan | GPU | VRAM | CPU | Memory | Storage | Bandwidth | Pricing | |
|---|---|---|---|---|---|---|---|---|
| Starter Ideal for inference |
1x RTX4090 | 24 GB | 8 vCPU | 32 GB | 200 GB NVMe | 1 Gbps | $599/month | Configure server |
| A100 40GPopular Ideal for training |
1x A100 40G | 40 GB | 16 vCPU | 64 GB | 500 GB NVMe | 10 Gbps | $1299/month | Configure server |
| A100 80G Ideal for large model training |
1x A100 80G | 80 GB | 32 vCPU | 128 GB | 1 TB NVMe | 10 Gbps | $2199/month | Configure server |
| H100 Ideal for ultra-large scale training |
1x H100 80G | 80 GB | 64 vCPU | 256 GB | 2 TB NVMe | 25 Gbps | $3999/month | Configure server |
Choosing a GPU server
Measure access from customer networks and account for the locations of databases, backups and application dependencies.
Size AI inference, training and rendering around GPU memory, software compatibility and job duration. Compare available hardware and billing options.
Verify image versions, licensing and administration access against the application you intend to run.
Include renewal terms, data transfer, additional IPs, software licenses and backup requirements in the total cost.
Confirm maintenance windows, restart requirements and recovery steps before scaling or migrating production workloads.
Include the service ID, timestamps, logs and network test results to help distinguish infrastructure from application issues.
Enterprise-grade GPU computing infrastructure
High-speed InfiniBand interconnect between GPU nodes, multi-card training communication bandwidth high, latency extremely low
Compare GPU allocation and hardware access for your workload, then test performance with your own software.
Availability is governed by the product SLA, measurement method and exclusions. Measure latency and performance from your own environment.
Built-in traffic scrubbing system, defense against large-scale DDoS attacks, business stays online unaffected
Covering AI and high-performance computing all scenarios
A100 and H100 GPUs are options for large-scale model training. Training time depends on the model, precision and interconnect.
Supports PyTorch/TensorFlow, first choice for deep learning research and engineering deployment
High-performance GPU accelerates 3D rendering, greatly improves film production and design efficiency
GPU parallel computing accelerates scientific simulation, molecular dynamics, climate simulation and other scenarios
For large language models, compare A100 and H100 memory capacity, supported precision and multi-GPU communication requirements.
Compare RTX 4090, A100 and H100 configurations by model memory requirements, inference throughput and total cost.
GPU Server complete technical specifications
GPU Server frequently asked questions
Start with model or scene memory, precision and concurrency. Then check GPU architecture, CPU capacity, system RAM and data-loading performance.
Use the billing options shown for the selected configuration. Confirm minimum charges, what happens when a job stops and the cost of long-running tasks.
Check the billing term, transfer allowance, IP allocation, software licensing and renewal conditions. Available payment methods are shown at checkout.
Upgrade procedures depend on the product and resource. Confirm whether a change requires a restart, migration or disk reconfiguration, and keep a tested backup before making changes.
Test from the networks your customers use, including peak periods. Consider latency, packet loss, return paths and the locations of databases, backups and external services.
Available images vary by node and plan. Check the version, licensing, access method and application compatibility in the configuration flow before ordering.
Practical guidance on server selection, deployment and everyday operations.
Available gateways, settlement currency and fees depend on the final checkout. Review the billing term and total before paying.
Refund windows, transfer limits, refund destination and eligibility for 99.9% availability compensation depend on your order's service terms. Confirm whether a first-order 24-hour refund applies before purchase; custom hardware and GPU plans may have different rules.
Confirm service termsA practical handover checklist, from sizing the instance to moving live traffic.
Start with model size, precision, context and batch size. For multi-GPU jobs, verify device count, allocation and the actual interconnect.
Check driver, CUDA and framework compatibility. Run a small inference or rendering job before importing the full dataset.
Record time to first token, tokens per second, peak VRAM or batch render time on representative inputs. Include retries in job estimates.
Confirm charges when stopped, released or retaining disks. Export models, workflow files and outputs before terminating the instance.
Start with your model and workload, then validate memory usage, concurrency and the delivered software environment.
Hardware reference: RTX 4090 24GB GDDR6X; RTX 3090 24GB; A10 24GB; A30 24GB; A100 40GB/80GB HBM2e; H100 80GB HBM3. Available models, allocation and topology depend on the selected configuration.
Specify Ubuntu 22.04/24.04, NVIDIA driver, CUDA, cuDNN, PyTorch and TensorFlow versions when ordering. Verify the delivered image with nvidia-smi and a minimal inference run. The report’s RTX 4090 cost reference is $1.20/hour; confirm the actual hourly offer before estimating a job.
Confirm resources, renewal costs, payment options and delivery timing. Request a product-specific test IP and check routes from your users’ networks.
Match CPU, RAM, storage, IPs and OS to your order. Verify login, remote management access and connectivity.
Run a representative workload and test backup recovery. Save your results and open a support ticket if the delivered configuration differs.