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StreamLake vs Wafer
Both sell subscription access for coding agents. StreamLake offers Kuaishou's closed KAT-Coder from China; Wafer offers agent-tuned open models on a $10 weekly pass.
By The Subconscious Team · Updated
StreamLake vs Wafer: key differences
The pitch overlaps more than it first appears. StreamLake sells KAT-Coder-Pro V2.5, a proprietary coding model from Kuaishou's KwaiKAT team that StreamLake says was trained with large-scale agentic reinforcement learning for repository-level work. Developers pay per token or buy a KwaiKAT Coding Plan, with a Claude-protocol proxy for Claude Code or OpenClaw. Wafer sells big open models, like Qwen 3.5 397B and GLM 5.1, on stacks its agents tune, and its Wafer Pass from $10 a week covers every hosted model and plugs into Claude Code, Cline and OpenHands.
Model type and region split them. StreamLake's model is closed and in-house, and its pricing and documentation lead with China and yuan, with data residency in China that rules it out for many US and EU buyers. Wafer is a young San Francisco company with a small catalog, and its reported 2x to 2.8x speedups are measured against stock vLLM or SGLang. Wafer also runs on NVIDIA or AMD and sells dedicated deployments tuned to a latency SLO. StreamLake sells bare metal to Chinese internet businesses.
What StreamLake and Wafer 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 profileWafer
Wafer builds AI agents that act as GPU performance engineers, then sells inference on the stacks those agents tune. The company came out of Y Combinator's Summer 2025 batch as a "Cursor for CUDA" that turned slow PyTorch into custom kernels. Founders Emilio Andere and Steven Arellano are based in San Francisco. Its agents profile a workload, generate candidate configs across batching, decoding, quantization, engines, kernels and hardware, measure each one and deploy the winner.
Example models: Qwen 3.5 397B Turbo, GLM 5.1 Turbo
Full Wafer profileShould you choose StreamLake or Wafer?
StreamLake
Choose StreamLake for
- Teams that want Kuaishou's purpose-built coding model
- Chinese businesses needing domestic MaaS and bare metal
- Coding subscriptions priced in yuan
Wafer
Choose Wafer for
- Western teams wanting open models on a flat pass
- Dedicated endpoints tuned to a latency target
- Hedging GPU supply across NVIDIA and AMD
StreamLake vs Wafer at a glance
| Attribute | StreamLake | Wafer |
|---|---|---|
| Model access | Proprietary coding models | Open weights |
| Flagship models | KAT-Coder-Pro V2.5, KAT-Coder-Air | Qwen 3.5 397B Turbo, GLM 5.1 Turbo |
| Speed | Unknown | 2–2.8x vs stock vLLM or SGLang |
| Price | Per token or KwaiKAT Coding Plan | Wafer Pass from $10 a week |
| Customization | Unknown | Agent-tuned dedicated deployments |
| Deployment | MaaS API, bare metal | Serverless pass, dedicated |
| Long context | Unknown | Varies by model |
Frequently asked questions
What is the difference between StreamLake and Wafer?
Both sell subscription access for coding agents. StreamLake offers Kuaishou's closed KAT-Coder from China; Wafer offers agent-tuned open models on a $10 weekly pass.
When should I choose StreamLake over Wafer?
Teams that want Kuaishou's purpose-built coding model; Chinese businesses needing domestic MaaS and bare metal; Coding subscriptions priced in yuan.
When should I choose Wafer over StreamLake?
Western teams wanting open models on a flat pass; Dedicated endpoints tuned to a latency target; Hedging GPU supply across NVIDIA and AMD.
Is StreamLake or Wafer cheaper?
StreamLake: Per token or KwaiKAT Coding Plan. Wafer: Wafer Pass from $10 a week. The cheaper choice depends on the model and workload.
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