Agentic GPU runtime
GPU that feels local.
Sub-second cold starts.
Serverless GPU for code and agents. Bring your Python, skip the Docker. Pay per GPU-second you actually run.
02/ Primitives
Graphene in four words.
GPU
T4 / L4 / A100 / H100
Cold start
sub-second
Billing
per GPU-second
Runtime
Python-native
03/ Workflow
Three commands. One GPU-run.
01 /
graphene init
Pick GPU and Python. We capture the runtime profile and create a ready revision.
02 /
graphene sync
Add dependencies. We resolve, build, and pin them server-side.
03 /
graphene run
Your code ships to the assigned node and streams output back. Per-second billing starts here.
04/ For agents
A /Burst parallelism
Fan out 50 runs in a second.
Agents do not run one thing at a time. Neither should the platform. Graphene was built for bursty, ephemeral GPU work that a human driver would not tolerate at a traditional cloud.
B /No Docker cycle
Edit a file. Run it.
Deps and OS setup land at sync time, not at every run. Hot run path does zero installation.
05