Fine-tune on your data.
Adapt a supported model with your data or reward signal. Use GPU sandboxes for your own training code and rollout loops.
Run your media
models at scale.
Deploy on Hedra’s GPU infrastructure and optimize inference with World Model Runtime (WMR). Work with our engineers on quality, latency, throughput, and cost.
More generations from the same GPU.
WMR optimizes diffusion, attention, and decoding for supported media models. Our engineers help tune the runtime and GPU configuration for your workload.
Time to generate one 5-second 768p clip
MiniMax H3 · One AMD MI355X
Internal benchmark: MiniMax H3 · 5-second 768p clip · Single AMD MI355X · SGLang baseline · Aug–Sep 2026.
Train and serve on one stack.
Deploy with WMR.
Evaluate checkpoints on your task, then serve supported models with Hedra’s inference engine.
Keep your weights and data private.
Serve proprietary models in isolated GPU environments with regional data controls.
Choose where your model runs.
Reserve GPU capacity on Hedra, or deploy our stack inside your perimeter on clusters you operate. We’ll scope supported hardware and regional availability with you.
Generate through a managed inference API.
Access image, video, and audio models through one API. Hedra manages hosting and inference.
Bring us your model and workload.
Tell us your quality target, expected volume, and hosting requirements. We’ll help you plan the deployment.