Run AI workloads without owning the infrastructure.
The compute layer of the FelixSphere stack. On-demand inference and GPU compute for the work beyond chat, billed by consumption instead of reservations.
AI has work to do. Give it the compute.
Batch processing
Run large inference jobs over datasets without holding capacity between runs.
Embeddings
Embed corpora of any size for retrieval, search, and clustering.
Document pipelines
Parse, extract, and classify documents at volume.
Fine-tuning
Adapt models to your domain on capacity you do not have to plan.
From workload to output, without capacity planning.
- 01Define
Describe the work: the model, the data, the output you need.
- 02Run on demand
Compute is allocated for the job, executed, and released.
- 03Keep the output
Results land where you need them. You pay for what ran.
Your work has a runtime. Your bill should too.
Unify Compute is in development. Rates and availability will be announced at launch. For enterprise and AI lab requirements beyond on-demand workloads, FelixSphere scopes capacity directly.
- Training runs
- Production inference
- Dedicated compute
- GPU clusters
- Private and enterprise AI infrastructure
Have spare compute or unused token credits? Sell them to us.
Sell GPU compute
Idle clusters, reserved capacity you are not using, or spare GPUs in your data center. We put it to work on AI workloads.
Sell token credits
Unused AI model and API credits from providers you have committed to. We turn them into capacity for UnifyAPI traffic.
Tell us about the workload.
Batch job, fine-tune, or a production inference footprint. We will tell you how we would run it.