01 / Engine
Start with your inference engine.
YYLO OS is an optimization layer for inference engines. It tunes serving performance for your hardware and the requests you need to handle.
YYLO OS / Inference optimization
Lower inference latency. On your hardware.
YYLO OS tunes your inference engine for the hardware it runs on. Hardware-specific kernels help make better use of your compute, while ongoing tuning adapts to changes in traffic, prompt lengths and response lengths.
Enterprise software. Runs in your cloud. NVIDIA GPUs and AWS Trainium.
How it works
How YYLO OS tunes inference.
02 / Kernels
Put more of your compute to work.
Dedicated optimized kernels target the operations involved in inference, improving compute utilization and reducing execution time.
03 / Traffic
Adjust as requests change.
A configuration that works for short prompts may not suit longer ones. YYLO OS keeps tuning as request volume and lengths change.
Compatibility
Hardware and models we support.
Hardware
- NVIDIA GPUs
- AWS Trainium
YYLO benchmarks have been run on NVIDIA Blackwell-series and H200 GPUs.
Models
- Kimi family
- GLM 5
- Qwen 3.5
- Qwen 3.8
- DeepSeek
Tell us your model variant, engine version and hardware configuration. We’ll confirm the supported combination before deployment.
Enterprise pricing
A clear starting point.
License YYLO OS for your own cloud. Your existing compute bill stays separate.
Larger fleets, multiple clusters and AWS Trainium deployments are scoped with our team.
Single-cluster deployment
From US$2,000/month
- Up to 8 NVIDIA GPUs in one cluster
- One supported engine and model setup
- Ongoing performance tuning
- Business-hours support
Software only. Cloud and GPU costs are not included. We’ll agree on onboarding, the subscription term and any additional integration work before you start.
Contact salesBefore you deploy
Questions from enterprise teams.
Where does YYLO OS run?
You deploy YYLO OS in your own cloud environment, alongside your inference setup. It is proprietary software, licensed for enterprise use.
Do we need to replace our inference engine?
YYLO OS tunes inference engines rather than providing a hosted model API. Share your engine and version so we can confirm the integration and any configuration changes needed.
What access and data does deployment require?
We review the required permissions, network access and telemetry with your team before deployment. Contact us to work through your security and data-handling requirements for the proposed setup.
How do we evaluate performance?
Start with your model, hardware and representative traffic. Compare time to first token and response latency against your existing configuration using the same request mix. Lower latency does not automatically mean a lower cloud bill.
What happens before a production rollout?
We agree on the supported configuration, evaluation criteria and rollout plan with your team. That includes any service interruptions, recovery steps and operational responsibilities for your environment.
What support is included?
The starting package includes business-hours support. Support hours, response expectations and any additional service requirements are agreed in your contract.
Contact us
Tell us about your inference setup.
Send us your engine, model, hardware and target response time. We’ll discuss whether YYLO OS fits.
Or email Golchin@yylo.dev.
Compare your options
Alternatives to consider.
Compare YYLO OS with managed platforms, enterprise software and engines you operate yourself.
Read the full comparison →