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OpenAI vs StreamLake
Two closed-model vendors with a coding pitch. StreamLake's KAT-Coder comes on a cheap subscription; OpenAI's GPT-6 Astra comes with Western procurement and a larger platform.
By The Subconscious Team · Updated
OpenAI vs StreamLake: key differences
StreamLake is Kuaishou's AI cloud, and its headline product is KAT-Coder-Pro V2.5, a proprietary agentic coding model trained with large-scale agentic reinforcement learning for repository-level work. Like OpenAI, it keeps the weights closed. Unlike OpenAI, it sells a subscription, the KwaiKAT Coding Plan, next to per-token pricing, with OpenAI-protocol endpoints and a Claude-protocol proxy that drops into Claude Code or OpenClaw. OpenAI's coding pitch rests on GPT-6 Astra's frontier results on coding benchmarks and the hosted tools in the Responses API.
Procurement will decide this for most Western teams. StreamLake's pricing and much of its documentation lead with China and yuan, and data residency in China rules it out for many US and EU enterprise buyers. OpenAI sells through its own API, Azure OpenAI and Bedrock. StreamLake's audience is clearer on its home ground: developers who want low-cost agentic coding on a plan, and Chinese internet businesses that want domestic model hosting and bare-metal capacity. OpenAI's bill runs higher, especially past 272K tokens, but it covers far more than coding.
What OpenAI and StreamLake do
OpenAI
OpenAI runs the most widely adopted closed-model API. Its September 2026 lineup has GPT-6 Astra at the top for computer use, coding and long agentic runs, priced at $10 in and $50 out per million tokens. Below it sits the GPT-5.6 family: Sol for hard professional work, Terra as the balanced default, and Luna for high-volume jobs at $0.20 in and $1.20 out. All of them carry a 1.05M token context window with up to 128K output.
Example models: GPT-6 Astra, GPT-5.6 Terra
Full OpenAI 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 OpenAI or StreamLake?
OpenAI
Choose OpenAI for
- US and EU enterprises that need data kept outside China
- Coding plus computer use and general assistants
- Teams that need Azure or Bedrock procurement
StreamLake
Choose StreamLake for
- Low-cost agentic coding on a subscription plan
- Chinese businesses wanting domestic MaaS and bare metal
- Running a Claude Code-style harness on KAT-Coder
OpenAI vs StreamLake at a glance
| Attribute | OpenAI | StreamLake |
|---|---|---|
| Model access | Closed, plus open gpt-oss | Proprietary coding models |
| Flagship models | GPT-6 Astra, GPT-5.6 Sol, Terra, Luna | KAT-Coder-Pro V2.5, KAT-Coder-Air |
| Speed | Fast mode: up to 2.5x at 2x price | Unknown |
| Price | $0.20–$10 in, $1.20–$50 out per 1M | Per token or KwaiKAT Coding Plan |
| Customization | N/A | Unknown |
| Deployment | API, Azure OpenAI, Bedrock | MaaS API, bare metal |
| Long context | 1.05M; 2x input past 272K | Unknown |
Frequently asked questions
What is the difference between OpenAI and StreamLake?
Two closed-model vendors with a coding pitch. StreamLake's KAT-Coder comes on a cheap subscription; OpenAI's GPT-6 Astra comes with Western procurement and a larger platform.
When should I choose OpenAI over StreamLake?
US and EU enterprises that need data kept outside China; Coding plus computer use and general assistants; Teams that need Azure or Bedrock procurement.
When should I choose StreamLake over OpenAI?
Low-cost agentic coding on a subscription plan; Chinese businesses wanting domestic MaaS and bare metal; Running a Claude Code-style harness on KAT-Coder.
Is OpenAI or StreamLake cheaper?
OpenAI: $0.20–$10 in, $1.20–$50 out per 1M. StreamLake: Per token or KwaiKAT Coding Plan. 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.