The GPU cloud built for
fast-moving startups.
Reserve GPU VMs, bare-metal nodes, or private clusters.
Add capacity, release eligible windows, or transfer an approved commitment as plans change.
Trusted by
Why Lilac
Dedicated GPUs. Flexibility built in.
Products
One GPU Network.
Four ways to use Compute.
Dedicated clusters
Dedicated GPU infrastructure, directly from Lilac
Compare indicative pricing across GPU VMs, bare-metal nodes, and multi-node clusters. Lilac handles capacity, access, and support.
Reserve H100s
Indicative pricing. Final rates depend on configuration and term.
*Estimate pricing
Serverless
Frontier models, simple per-token pricing
Use supported open models through an OpenAI-compatible API. No GPU reservation, no minimums, and no infrastructure to manage.
Subscriptions
Monthly inference credits that stretch further
Choose a flat monthly credit pool for supported models. Lower-cost capacity lets a predictable subscription cover more product usage.
Batch
Run GPU jobs to completion
Submit a container image and a command. Lilac runs it on available GPU capacity with simple per-second pricing and no cluster to manage.
Commitment lifecycle
Commit without getting trapped.
Reserve what you need now. Use Lilac Flex to sell eligible downtime into spot demand, or transfer an approved commitment as plans change.
Reserve
Choose the capacity you need now.
Select the GPU, region, scale, and term. The final quote names the site, network, delivery date, and commercial terms.
Lilac Flex
Automatically sell eligible downtime.
Opt in to offer unused reservation windows to Lilac's spot workloads. When demand is matched, bill credits lower your effective GPU cost.
Transfer
Change the owner when plans change.
Relist an eligible commitment or take one over from a verified startup. Lilac qualifies the buyer and coordinates approval.
Blog
Notes from the team
Updates, thinking, and technical deep-dives from the Lilac team.
GPU cloud for startups



