Real-time streaming
Encode, transcode and light inference on live video without paying hyperscaler egress for every viewer. L40S and 4090s are the usual cards; load balancing sits in front if you run more than one worker.
Pick a SKU, a mode and a run length
Illustrative USD before tax. Spot is typical, not a guarantee. Reserved discounts are the published 18 / 24 / 28 / 31% schedule.
How this actually runs
Most teams do not buy a ‘solution’. They have a job: serve a model, finish a sequence, train a checkpoint, move off a hyperscaler bill. The GPUs are the same. What changes is isolation, term, queue and whether engineering is in the room.
Inference wants a reserved or bare-metal baseline behind load balancing, with on-demand overflow when QPS jumps. Training wants a host that will not disappear mid-epoch - bare metal or a reserved block, InfiniBand if you scale past one node. Render wants the farm software on L40S / 4090, or a reserved block if the delivery date is real.
Batch and ETL should be on spot if they checkpoint, on-demand if they do not. Reserved is wasted money on a job that runs twice a week. Scientific codes that already scale on CUDA use the same H100 / A100 SKUs as training; the research programme is a separate conversation about hybrid scheduling, not a SKU.
Migration is inventory first: map instance types, storage and network to our card, run one job on on-demand, then reserve or go bare metal if the numbers work. We will not promise global edge latency from two sites. If your users are far from our sites, we measure before we quote, and sometimes the honest answer is keep inference where they are.
Engineering retainers exist for the cases where the hard part is the system, not the card: pipelines, pricing engines, inference control planes, farm-to-deadline wiring. Same commercial model as advertising - flat monthly, compute à la carte. Discovery is two weeks against real systems before anyone signs a retainer.
Same GPUs, four different jobs
Switch the tab. The recommendation changes. If none of these is your job, say so on the contact form. We will tell you whether rentals, a retainer or a no is the honest answer.
Keep a reserved or bare-metal baseline behind load balancing. Overflow onto on-demand in the same site when traffic spikes. Same image, same network, higher unit price only on the extra seconds.
- H100 / A100 / L40S are the usual SKUs
- vLLM, TensorRT, Triton or your container
- Cross-site failover is opt-in
- Data and weights stay in-country
GPU time on a clock, not a contract
Hardware encode on L40S or 4090. Scale workers with the number of concurrent streams, not with a reserved instance year.
Captions, moderation or vision models on the same box or a sidecar GPU. Overflow to on-demand for events.
In-region transfer is included. We will tell you honestly if your viewer map does not match either site.
Illustrative week · mix of work on one account
Published SKUs, both sites
Full table including reserved discount math lives on Pricing. Spot is typical. Fabric is InfiniBand at InfiniBand fabric, or 100 GbE (25 GbE on smaller cards) depending on the SKU.
| Instance | Site | VRAM | CPU / RAM | Fabric | On-demand | Spot typ. |
|---|---|---|---|---|---|---|
| H100 PCIe 80GB | InfiniBand | 80GB HBM3 | 24 / 200 GB | InfiniBand | $2.19 | $0.66 |
| A100 PCIe 80GB | InfiniBand | 80GB HBM2e | 16 / 180 GB | InfiniBand | $1.24 | $0.37 |
| L40S 48GB | 100 GbE | 48GB GDDR6 | 12 / 128 GB | 100 GbE | $0.86 | $0.26 |
| RTX 4090 24GB | 25 GbE | 24GB GDDR6X | 8 / 64 GB | 25 GbE | $0.41 | $0.12 |
| RTX A6000 48GB | Multi-site | 48GB GDDR6 | 12 / 96 GB | 25–100 GbE | $0.95 | $0.29 |
| CPU render node | Multi-site | 64 / 256 GB | 25 GbE | $0.68 | $0.20 |