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StreamLake vs OpenScale
StreamLake sells Kuaishou's proprietary KAT-Coder models with China data residency. OpenScale sells open DeepSeek V4.1 Flash for coding agents at promo prices.
By The Subconscious Team · Updated
StreamLake vs OpenScale: key differences
StreamLake, the AI cloud of Kuaishou, sells KAT-Coder-Pro V2.5 at $0.74 in and $2.96 out per million tokens or through a KwaiKAT Coding Plan, plus hosted open models and bare metal. OpenScale's own comparison lists StreamLake's DeepSeek V4.1 Flash at $0.15 in and $0.60 out. OpenScale, a Y Combinator-backed API out of Singapore, serves DeepSeek V4.1 Flash at $0.06 in, $0.003 cached and $0.24 out per million tokens under a 50% promotion, at 200+ tokens per second, with a fast tier at about twice the speed.
Both target coding agents. StreamLake is the pick for developers who want a proprietary model trained for repository work, or for Chinese businesses that want domestic capacity. OpenScale is the pick for the lowest price on an open model, though it is a newer company with one model and no dedicated deployments.
What StreamLake and OpenScale 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, and it also hosts third-party open models like DeepSeek V4 Flash 0731.
Example models: KAT-Coder-Pro V2.5, KAT-Coder-Air V2.5
Full StreamLake profileOpenScale
OpenScale is a Y Combinator-backed inference API built by LatentSpace and run out of Singapore. It sells open models behind one endpoint that speaks Chat Completions, the OpenAI Responses API and Anthropic Messages, so Claude Code, Codex, OpenCode, Cline, GitHub Copilot, Zed and other coding agents can point at it with a base URL and key. Its public catalog today is DeepSeek V4.1 Flash in two versions, standard and fast, both with a 1M token context window and up to 384K output tokens.
Example models: DeepSeek V4.1 Flash
Full OpenScale profileShould you choose StreamLake or OpenScale?
StreamLake
Choose StreamLake for
- KAT-Coder on a subscription plan
- Domestic MaaS and bare metal in China
- Backing from a large company
OpenScale
Choose OpenScale for
- Lower prices on DeepSeek V4.1 Flash
- Zero data retention by default
- Teams that cannot keep data in China
StreamLake vs OpenScale at a glance
| Attribute | StreamLake | OpenScale |
|---|---|---|
| Model access | Proprietary coding models, plus hosted open models | Open weights |
| Flagship models | KAT-Coder-Pro V2.5, KAT-Coder-Air V2.5 | DeepSeek V4.1 Flash |
| Speed | Unknown | 200+ tok/s; fast tier ~2x |
| Price | $0.74 in, $2.96 out (Pro V2.5), or KwaiKAT Coding Plan | $0.06 in, $0.24 out (promo, DeepSeek V4.1 Flash) |
| Customization | Unknown | N/A |
| Deployment | MaaS API, bare metal | Serverless API |
| Long context | 256K | 1M context |
Frequently asked questions
What is the difference between StreamLake and OpenScale?
StreamLake sells Kuaishou's proprietary KAT-Coder models with China data residency. OpenScale sells open DeepSeek V4.1 Flash for coding agents at promo prices.
When should I choose StreamLake over OpenScale?
KAT-Coder on a subscription plan; Domestic MaaS and bare metal in China; Backing from a large company.
When should I choose OpenScale over StreamLake?
Lower prices on DeepSeek V4.1 Flash; Zero data retention by default; Teams that cannot keep data in China.
Is StreamLake or OpenScale cheaper?
StreamLake: $0.74 in, $2.96 out (Pro V2.5), or KwaiKAT Coding Plan. OpenScale: $0.06 in, $0.24 out (promo, DeepSeek V4.1 Flash). The cheaper choice depends on the model and workload.
Which has more context, StreamLake or OpenScale?
StreamLake: 256K. OpenScale: 1M context.
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.