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Groq vs StreamLake
StreamLake sells Kuaishou's proprietary KAT-Coder models from China. Groq serves fast open models. A coding-model vendor against a speed host.
By The Subconscious Team · Updated
Groq vs StreamLake: key differences
StreamLake is Kuaishou's AI cloud, and its main attraction is KAT-Coder-Pro V2.5, a proprietary agentic coding model StreamLake says was trained for repository-level work like reading an issue, editing across files and fixing its own test failures. It sells per token or through a KwaiKAT Coding Plan, with a Claude-protocol proxy for Claude Code. Groq has no coding-specific model. It serves GPT-OSS and Qwen 3.6 on its LPU at high speed with an OpenAI-compatible API. The question is whether a team wants a specialist coding model or fast general inference.
Procurement will narrow it for many buyers. StreamLake's pricing and docs lead with China and yuan, and data residency in China rules it out for many US and EU enterprises. Groq's small-model prices, by contrast, sit near the floor with no plan required. StreamLake also sells bare-metal capacity for Chinese internet businesses. Groq caps context around 131K, which can limit repo-level coding, a job KAT-Coder is built for.
What Groq and StreamLake do
Groq
Groq serves open models on its own chip, the LPU, which keeps model weights in on-chip SRAM and runs a deterministic schedule instead of waiting on GPU memory. Groq publishes 1,000 tokens per second on GPT-OSS 20B and 500 on GPT-OSS 120B. Latency stays tight between median and tail, which matters for strict SLAs. The API is OpenAI-compatible and also hosts Whisper for speech to text plus an agentic system called Groq Compound with built-in search and code execution.
Example models: GPT-OSS 120B, Qwen 3.6 27B
Full Groq 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 Groq or StreamLake?
Groq
Choose Groq for
- Fast general inference for Western teams
- Voice and chat with tight latency
- Cheap high-frequency calls on small models
StreamLake
Choose StreamLake for
- KAT-Coder-Pro V2.5 for repository-level coding
- Subscription-priced agentic coding in Claude Code
- Chinese businesses wanting domestic MaaS
Groq vs StreamLake at a glance
| Attribute | Groq | StreamLake |
|---|---|---|
| Model access | Open weights | Proprietary coding models |
| Flagship models | GPT-OSS 120B, Qwen 3.6 27B | KAT-Coder-Pro V2.5, KAT-Coder-Air |
| Speed | 500–1,000 tok/s | Unknown |
| Price | Near the floor on small models | Per token or KwaiKAT Coding Plan |
| Customization | No fine-tuned model hosting | Unknown |
| Deployment | GroqCloud API | MaaS API, bare metal |
| Long context | Around 131K max | Unknown |
Frequently asked questions
What is the difference between Groq and StreamLake?
StreamLake sells Kuaishou's proprietary KAT-Coder models from China. Groq serves fast open models. A coding-model vendor against a speed host.
When should I choose Groq over StreamLake?
Fast general inference for Western teams; Voice and chat with tight latency; Cheap high-frequency calls on small models.
When should I choose StreamLake over Groq?
KAT-Coder-Pro V2.5 for repository-level coding; Subscription-priced agentic coding in Claude Code; Chinese businesses wanting domestic MaaS.
Is Groq or StreamLake cheaper?
Groq: Near the floor on small models. StreamLake: Per token or KwaiKAT Coding Plan. The cheaper choice depends on the model and workload.
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