Cloud GPU for Deep Learning: A Practical Engineer's Checklist
Practical checklist for picking a cloud GPU for deep learning, covering VRAM, interconnect, queue time, and framework support...
2026-10-27 Read guideGPU price index
A800 SXM cloud rental prices
Every provider offering A800 SXM, normalised to hourly on-demand pricing with VRAM and region details.
Research by GPUCloudCompare Research
80 GB VRAM
Ampere
2.0 TB/s
2 offers
About the A800 SXM
- Memory
- 80 GB
- Architecture
- Ampere
- Memory bandwidth
- 2.0 TB/s
- Dense FP16 throughput
- 312 TFLOPS*
Vendor-published figures, with sparsity where the vendor states it. Always confirm on the official datasheet before sizing a cluster.
30-day price history
Daily snapshots of the lowest A800 SXM rate per provider.
- Vast.ai $0.6431/h
- 优云智算 UCloud $0.7801/h
This curve is built from our own daily collection runs, so the window fills in over time. Prices refresh every 6 hours and the line plots the daily median, the same measure Vast.ai uses.
Live GPU price comparison
Filter by provider, GPU or region — filters run locally in your browser.
| Provider | GPU model | VRAM | GPUs | vCPU | Region | On-demand /hr | Spot /hr | Actions |
|---|---|---|---|---|---|---|---|---|
| Vast.ai | A800 SXM | 80 GB | 1 | — | Distributed (global hosts) | $0.4681 Best price | — | Rent this GPU |
| 优云智算 UCloud | A800 SXM | 80 GB | 1 | — | China (Ulanqab/Shanghai/Denver) | $0.7801 | $0.3953 | Rent this GPU |
No offers match these filters. Relax the price limit or clear the search.
Which GPUs work well with the A800 SXM?
Use the LLM VRAM calculator to check whether a specific model fits in one A800 SXM, and the cost estimator to turn a hourly rate into a monthly budget including storage and egress.
Frequently asked questions
Everything about renting cloud GPUs, affiliate tracking and how we collect pricing data.
Which GPUs are best for LLM inference?
For models that fit in memory, memory bandwidth matters more than raw FLOPS, so cards like the L40S, RTX 4090 or A100 often give better tokens per dollar than an H100. Once a model needs multi-GPU tensor parallelism, NVLink-equipped H100 or H200 instances usually win on throughput.
How much VRAM do I need to fine-tune a model?
Full fine-tuning needs roughly the parameter count times the bytes per parameter for weights, plus optimiser state which can be several times larger again. LoRA and QLoRA reduce the optimiser footprint dramatically. Use the LLM VRAM calculator to size a specific configuration.
Is it cheaper to rent or to buy a GPU?
Renting usually wins unless you can keep a device busy for a large fraction of the year. Cloud rental also shifts the cost of hardware refreshes onto the provider, which matters when new generations arrive every twelve to eighteen months.
Why do the same GPU models have different prices?
Configuration differs: number of GPUs per instance, system RAM and vCPU allocation, local disk, region, and whether the capacity is interruptible. We normalise to a single GPU so you can see through those differences.