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StreamLake vs Luminal
StreamLake is Kuaishou's AI cloud, home of the KAT-Coder models. Luminal compiles open models into faster code for your own GPUs.
By The Subconscious Team · Updated
StreamLake vs Luminal: key differences
StreamLake serves Kuaishou's proprietary KAT-Coder-Pro V2.5 and KAT-Coder-Air for agentic coding, per token or through the KwaiKAT Coding Plan, with docs and pricing led by China and yuan. Luminal sells no models. Its compiler turns open weights into native GPU kernels ahead of time, served on early-access endpoints or licensed on-prem.
StreamLake fits teams that want KAT-Coder and are comfortable with China data residency. Luminal fits teams that want to self-host an open coding model in their own region, with a reported 36K tokens per second on GPT-OSS 120B across 8 H100s.
What StreamLake and Luminal do
StreamLake
StreamLake is the AI cloud brand of Kuaishou, the Chinese short-video company behind the Kling video models. It sells model-as-a-service inference and bare-metal compute to internet businesses, drawing on the infrastructure Kuaishou built to serve video at massive scale. Its developer site offers APIs, SDKs and integration guides aimed at taking teams from testing to production.
Example models: KAT-Coder-Pro V2.5, KAT-Coder-Air
Full StreamLake profileLuminal
Luminal builds an inference compiler. Where vLLM and SGLang interpret a model at runtime, Luminal compiles it ahead of time into native kernels for GPUs and ASICs. Models get lowered to a small graph of 15 primitive ops, and the compiler searches over fusion, tiling, memory and scheduling choices instead of relying on hand-written rules, which it says can find optimizations like Flash Attention on its own. The compiler is open source in Rust under Apache 2.0 or MIT, runs on CUDA and Metal with ROCm on the roadmap, and works as a torch.compile backend.
Example models: GPT-OSS 120B, Llama 3 8B
Full Luminal profileShould you choose StreamLake or Luminal?
StreamLake
Choose StreamLake for
- KAT-Coder models for agentic coding
- A flat coding plan
- Bare-metal capacity in China
Luminal
Choose Luminal for
- Self-hosting an open coding model in your region
- Maximum throughput per GPU on a self-chosen model
- An open-source engine teams can run on their own hardware
StreamLake vs Luminal at a glance
| Attribute | StreamLake | Luminal |
|---|---|---|
| Model access | Proprietary coding models | Bring your own weights |
| Flagship models | KAT-Coder-Pro V2.5, KAT-Coder-Air | No public catalog |
| Speed | Unknown | 36K tok/s on GPT-OSS 120B, 8xH100 (vendor) |
| Price | Per token or KwaiKAT Coding Plan | Pay per use; rates not published |
| Customization | Unknown | Compiles any PyTorch or HF model |
| Deployment | MaaS API, bare metal | Serverless (early access), on-prem license |
| Long context | Unknown | Unknown |
Frequently asked questions
What is the difference between StreamLake and Luminal?
StreamLake is Kuaishou's AI cloud, home of the KAT-Coder models. Luminal compiles open models into faster code for your own GPUs.
When should I choose StreamLake over Luminal?
KAT-Coder models for agentic coding; A flat coding plan; Bare-metal capacity in China.
When should I choose Luminal over StreamLake?
Self-hosting an open coding model in your region; Maximum throughput per GPU on a self-chosen model; An open-source engine teams can run on their own hardware.
Is StreamLake or Luminal cheaper?
StreamLake: Per token or KwaiKAT Coding Plan. Luminal: Pay per use; rates not published. The cheaper choice depends on the model and workload.
Related comparisons
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If your agents run past 200K tokens, compare both against Subconscious. Our inference stack treats a long-horizon trace as the primary workload, so speed, cost, and accuracy hold up deep into the trace.