◆ Decentralized GPU compute
Rendering power
without the farm.
Marven pools idle GPUs across the world into one on-demand network. Push a render or a training run, draw the compute you need, pay for the seconds you use.
◆ Why Marven
Cloud rendering, minus the lock-in.
Parallel by default
Jobs fan out across thousands of GPUs at once. A frame sequence that took a night finishes before lunch.
Elastic supply
The pool grows as operators plug in idle hardware. You draw as much as a job needs, then release it.
Metered pricing
Pay for GPU-seconds you actually use. No reserved instances, no monthly floor, no idle burn.
◆ 3D + generative AI
One network for every
frame you need made.
Marven speaks to the GPU render engines artists already use and the generative models AI teams are building on. Same pool, same billing, one place to watch it all run.
- OctaneRender
- Redshift
- Blender Cycles
- Karma
- V-Ray
- ComfyUI
- Flux
- Stable Diffusion
- Wan 2.1
- Hunyuan
◆ How it works
From submit to output in four moves.
Submit the job
Push a scene from your DCC tool or an inference graph through the Marven CLI, API, or console.
Scheduler splits it
Marven shards the work into tiles or batches and places them on the lowest-latency idle GPUs available.
Nodes render
Operators run the chunks in a sandboxed runtime. Results are hashed and verified before they count.
Output streams back
Finished frames and tensors land in your bucket as they complete. You watch progress fill in live.
◆ Who runs on Marven
Built for both sides of the GPU.
Studios & artists
Final-frame rendering and look-dev iterations without owning a farm.
Node operators
Turn idle gaming or mining rigs into metered revenue between your own workloads.
AI teams
Burst training runs and large-batch inference on commodity GPUs.
Agencies
Spin up capacity per pitch, then hand the invoice straight to the client.
In the news
Point a render at the whole world.
Open a console, drop in a scene, and watch idle GPUs everywhere pick up the work.