

HeyGen
How a leading AI video platform unlocked new product capabilities by replacing expensive managed providers with a single, cost-effective inference API.
Non-virtualized NVIDIA GPUs with InfiniBand, as bare metal or serverless, from Sonic Pod sites across Europe and the US. Data stays in the EU. No egress fees. Published reserved pricing.
H100s are up to 46% cheaper on Runware than on Nebius. H200s up to 44%, B200s up to 35% and B300s up to 64%. On demand, with no commitment, every GPU in the table is 12 to 29% less.
Prices checked 22 Oct, 2026.
What 730 hours on a single H100 costs per month, at the list rates in the table above. Reserve a baseline and burst above it on Serverless to land between the two Runware figures.
Years of land, permits and construction, then GPUs financed on top. All of that overhead ends up in the hourly rate. When the market asks whether that still adds up, it is your capacity on the line.
So we rebuilt the stack. A Sonic Pod is a complete 1 MW AI data center in a 20 ft container: built in three weeks, set on a pad where power is cheap, live in days. No hundred-acre building, no overbuilt redundancy, no cloud provider's margin in the rate. Leave Nebius and you land on infrastructure we own, run and keep building.

Same NVIDIA GPUs, same non-virtualized access, same InfiniBand, in Europe and the US. The difference is the building: Runware designs and owns its Sonic Pod data centers, so there is no leased facility and no cloud margin in the GPU-hour.
Nothing to port. Your Kubernetes or Slurm runs on our bare metal as is. The containers you serve become Serverless apps. Storage moves to WEKA.
Same stack, on GPU nodes reserved for the term. InfiniBand on B300 and NVL72.
Bring the container, pick the GPUs, set the worker limits.
OpenAI Chat Completions format. Change the base URL and the key.
Lower bill, no GPU platform to run. Here's what moving to Runware looked like for teams shipping at production scale.


How a leading AI video platform unlocked new product capabilities by replacing expensive managed providers with a single, cost-effective inference API.


How OpenArt achieved sub-second image generation at scale with Runware's Sonic Engine.

How a fast-growing video generation startup deployed a major model release in hours.


How NightCafe scaled their AI art community without hiring a single infrastructure engineer.
Yes. Nebius sells HGX instances with InfiniBand, Managed Kubernetes, Soperator for Slurm, AI Storage and per-token inference through Token Factory. We sell bare-metal GPU nodes and clusters, serverless GPU compute and an LLM API, on data centers we build ourselves in Europe and the US. Same hardware, different building, lower rate.
On demand, Runware is 12 to 29% cheaper than Nebius across the 4 GPUs both price; reserved, 35 to 64%. An H100 is $4.50 per GPU-hour on Nebius, $3.95 on Runware on demand and $2.45 reserved. Nebius's figures are from its on-demand rate card, checked 22 Oct, 2026. Runware's are the Serverless rate card, billed by the second.
Nebius lists preemptible rates from $0.79 an hour. They move with demand and the VM can be taken back. A Serverless worker keeps its GPU until your app releases it, so the table compares on-demand with on-demand. We don't sell a spot tier.
Pick eu-west or eu-central on Serverless, or one of five European Sonic Pod sites for bare metal. ISO 27001, SOC 2, and the data stays in the EU. See Sonic Pods.
No. Most GPU clouds rent the data center and finance the GPUs. We design, build and run our own Sonic Pods, on 600 MW+ across the US and 2 GW+ across Europe. Your reservation sits on hardware we own, and we build the next pod when you need it. See Sonic Pods.
Yes, on bare metal. Run the stack you run on Nebius today on our GPU nodes and clusters, with InfiniBand on B300 and NVL72. Serverless is the other option: we run the workload, so there is no shell into a worker. See GPU Compute.
Reserve serverless capacity from one GPU at $2.45 per GPU-hour for 1 to 24 months, or talk to an engineer about bare-metal HGX B300 and GB300 NVL72 clusters: hardware, site, term and delivery date.