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StreamLake vs Boundless
StreamLake is Kuaishou's AI cloud, built around its KAT-Coder models. Boundless serves open models with 1M context from the US or Europe.
By The Subconscious Team · Updated
StreamLake vs Boundless: key differences
StreamLake's headline model is KAT-Coder-Pro V2.5, Kuaishou's own agentic coding model, at $0.74 in and $2.96 out per million tokens, with KAT-Coder-Air V2.5 at $0.15 in and $0.60 out and 256K context. It also sells a KwaiKAT Coding Plan, a Claude-protocol proxy for Claude Code and bare-metal compute. Boundless serves open models such as DeepSeek V4.1 Flash at $0.20 in and $1.00 out and GLM-5.3 at $1.12 in and $3.52 out, most with 1M context, plus resold GPT and Claude models, through an API that works with the OpenAI and Anthropic SDKs. It keeps zero data retention and runs requests in the US or Europe.
Pick StreamLake for a dedicated coding model on a subscription plan, or for capacity inside China. Pick Boundless when US or European processing matters, when you want a choice of open model families with long context, or when you want engineers to tune and run a reserved deployment.
What StreamLake and Boundless 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 profileBoundless
Boundless launched in September 2026 as an inference partner for AI-native startups. It sells two things. The Model API serves pre-tuned models on shared capacity, billed per token from prepaid credits with a budget per API key. Tailored inference reserves capacity for one customer, and Boundless engineers pick the model on the customer’s own evals, tune precision, batching, caching, speculative decoding and parallelism, then run the deployment against uptime, throughput and latency targets written into the contract. A free two-week evaluation tests those targets on real traffic against the customer’s current provider first.
Example models: GLM-5.3, DeepSeek V4.1 Flash, Kimi K3
Full Boundless profileShould you choose StreamLake or Boundless?
StreamLake
Choose StreamLake for
- KAT-Coder for agentic coding
- KwaiKAT Coding Plan subscriptions
- Domestic capacity in China
Boundless
Choose Boundless for
- Processing in the US or Europe
- 1M context on most open models
- Tuned reserved deployments
StreamLake vs Boundless at a glance
| Attribute | StreamLake | Boundless |
|---|---|---|
| Model access | Proprietary coding models, plus hosted open models | Open weights, plus closed GPT and Claude |
| Flagship models | KAT-Coder-Pro V2.5, KAT-Coder-Air V2.5 | GLM-5.3, DeepSeek V4.1 Flash, Kimi K3 |
| Speed | Unknown | 342 tok/s on DeepSeek V4.1 Flash 1017 (Vercel) |
| Price | $0.74 in, $2.96 out (Pro V2.5), or KwaiKAT Coding Plan | $0.04–$2.30 in, $0.21–$11.40 out per 1M (open) |
| Customization | Unknown | Serving-stack tuning, no fine-tuning |
| Deployment | MaaS API, bare metal | Serverless API, reserved tailored capacity |
| Long context | 256K | 1M context on most models |
Frequently asked questions
What is the difference between StreamLake and Boundless?
StreamLake is Kuaishou's AI cloud, built around its KAT-Coder models. Boundless serves open models with 1M context from the US or Europe.
When should I choose StreamLake over Boundless?
KAT-Coder for agentic coding; KwaiKAT Coding Plan subscriptions; Domestic capacity in China.
When should I choose Boundless over StreamLake?
Processing in the US or Europe; 1M context on most open models; Tuned reserved deployments.
Is StreamLake or Boundless cheaper?
StreamLake: $0.74 in, $2.96 out (Pro V2.5), or KwaiKAT Coding Plan. Boundless: $0.04–$2.30 in, $0.21–$11.40 out per 1M (open). The cheaper choice depends on the model and workload.
Which has more context, StreamLake or Boundless?
StreamLake: 256K. Boundless: 1M context on most models.
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