Inference.net vs StreamLake

StreamLake sells Kuaishou's KAT-Coder and bare metal from China. Inference.net sells cheap batch and custom distilled models. Different buyers.

By The Subconscious Team · Updated September 30, 2026

Inference.net vs StreamLake: key differences

StreamLake is the AI cloud of Kuaishou, selling model-as-a-service inference and bare-metal compute, with the proprietary KAT-Coder-Pro V2.5 coding model as its headline. It offers per-token pricing, a KwaiKAT Coding Plan and a Claude-protocol proxy for Claude Code. Inference.net sells capacity differently, aggregating spare GPU time for its Batch API and offering a gateway that captures traffic and distills it into a custom model on a dedicated GPU. One sells a finished model. The other sells cheap compute and a way to build your own.

StreamLake's data residency in China and yuan-first pricing rule it out for many US and EU enterprises, while Chinese internet businesses may prefer it. Inference.net's model is open-ended: bring a task, and it helps replace a closed API call with a smaller fine-tuned model. For agentic coding on a subscription, StreamLake has a purpose-built model. For offline extraction, classification or custom distillation, Inference.net fits better.

What Inference.net and StreamLake do

Inference.net

Inference.net started as a buyer of last resort for idle GPU time. Its scheduler aggregates small unused chunks of capacity across data centers and runs models on them, and it passes the steep discounts it gets from those data centers on to customers. That origin still shows in its OpenAI-compatible Batch API, which takes up to 1M requests per file with completion windows from 24 hours to 7 days and far higher headroom than synchronous limits.

Example models: open catalog models plus customer fine-tunes served on dedicated GPUs

Full Inference.net profile

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 profile

Should you choose Inference.net or StreamLake?

Inference.net

Choose Inference.net for

Offline extraction and classification at low cost
Building a custom model from your traffic
Teams that cannot use China-resident data

StreamLake

Choose StreamLake for

Agentic coding with KAT-Coder-Pro V2.5
Subscription coding plans inside Claude Code
Chinese businesses needing domestic MaaS and bare metal

Inference.net vs StreamLake at a glance

Attribute	Inference.net	StreamLake
Model access	Open, closed and custom	Proprietary coding models
Flagship models	Customer fine-tunes	KAT-Coder-Pro V2.5, KAT-Coder-Air
Speed	Batch windows of 24h to 7 days	Unknown
Price	Discounted spare GPU capacity	Per token or KwaiKAT Coding Plan
Customization	Distill traces into custom models	Unknown
Deployment	Batch API, gateway, dedicated GPUs	MaaS API, bare metal
Long context	Varies by model	Unknown

Frequently asked questions

What is the difference between Inference.net and StreamLake?

StreamLake sells Kuaishou's KAT-Coder and bare metal from China. Inference.net sells cheap batch and custom distilled models. Different buyers.

When should I choose Inference.net over StreamLake?

Offline extraction and classification at low cost; Building a custom model from your traffic; Teams that cannot use China-resident data.

When should I choose StreamLake over Inference.net?

Agentic coding with KAT-Coder-Pro V2.5; Subscription coding plans inside Claude Code; Chinese businesses needing domestic MaaS and bare metal.

Is Inference.net or StreamLake cheaper?

Inference.net: Discounted spare GPU capacity. StreamLake: Per token or KwaiKAT Coding Plan. The cheaper choice depends on the model and workload.

Related comparisons

Running long-horizon agents?

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.

Subconscious vs Inference.net Subconscious vs StreamLake