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Cerebras vs StreamLake
StreamLake sells Kuaishou's proprietary KAT-Coder from China. Cerebras sells open-weight speed, distributed through AWS Marketplace and OpenRouter.
By The Subconscious Team · Updated
Cerebras vs StreamLake: key differences
StreamLake is Kuaishou's AI cloud, selling model-as-a-service and bare-metal compute. Its headline model, KAT-Coder-Pro V2.5, is a proprietary agentic coding model that StreamLake says was trained with large-scale agentic RL for repository-level work. Developers pay per token or through a KwaiKAT Coding Plan, with a Claude-protocol proxy for Claude Code. Cerebras serves open weights on a wafer-scale chip: GPT-OSS 120B near 3,000 tokens per second at $0.35 in and $0.75 out. StreamLake sells a specific coding model. Cerebras sells speed on general ones.
Data location is decisive for many buyers. StreamLake keeps data resident in China, and its pricing and docs lead with yuan, which complicates Western procurement. Cerebras reaches buyers through OpenRouter, Hugging Face, Vercel and AWS Marketplace. For long repository-level coding runs, a model trained for that job may matter more than raw tokens per second, and Cerebras' own caveat is that speed helps little when an agent waits on tools. For live autocomplete, Cerebras' speed is the whole point.
What Cerebras and StreamLake do
Cerebras
Cerebras builds a single chip the size of a silicon wafer, and its inference cloud is the fastest public host on the models it serves. Its developer table lists GPT-OSS 120B near 3,000 tokens per second, about six times Groq on the same weights, at $0.35 in and $0.75 out per million. The public shared catalog is thin, just GPT-OSS 120B and Gemma 4 31B as of August 2026. More model families live on dedicated endpoints and through partners like OpenRouter, Hugging Face, Vercel and AWS Marketplace.
Example models: GPT-OSS 120B, Gemma 4 31B
Full Cerebras profileStreamLake
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 profileShould you choose Cerebras or StreamLake?
Cerebras
Choose Cerebras for
- Live code autocomplete where speed is felt
- Western teams buying through AWS Marketplace or OpenRouter
- Fast outputs on open GPT-OSS 120B
StreamLake
Choose StreamLake for
- Repository-level agentic coding on KAT-Coder-Pro V2.5
- Low-cost coding through a subscription plan
- Chinese businesses wanting domestic MaaS and bare metal
Cerebras vs StreamLake at a glance
| Attribute | Cerebras | StreamLake |
|---|---|---|
| Model access | Open weights | Proprietary coding models |
| Flagship models | GPT-OSS 120B, Gemma 4 31B | KAT-Coder-Pro V2.5, KAT-Coder-Air |
| Speed | ~3,000 tok/s on GPT-OSS 120B | Unknown |
| Price | $0.35 in, $0.75 out (GPT-OSS 120B) | Per token or KwaiKAT Coding Plan |
| Customization | Unknown | Unknown |
| Deployment | Shared API, dedicated, partners | MaaS API, bare metal |
| Long context | Unknown | Unknown |
Frequently asked questions
What is the difference between Cerebras and StreamLake?
StreamLake sells Kuaishou's proprietary KAT-Coder from China. Cerebras sells open-weight speed, distributed through AWS Marketplace and OpenRouter.
When should I choose Cerebras over StreamLake?
Live code autocomplete where speed is felt; Western teams buying through AWS Marketplace or OpenRouter; Fast outputs on open GPT-OSS 120B.
When should I choose StreamLake over Cerebras?
Repository-level agentic coding on KAT-Coder-Pro V2.5; Low-cost coding through a subscription plan; Chinese businesses wanting domestic MaaS and bare metal.
Is Cerebras or StreamLake cheaper?
Cerebras: $0.35 in, $0.75 out (GPT-OSS 120B). StreamLake: Per token or KwaiKAT Coding Plan. The cheaper choice depends on the model and workload.
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