Key takeaways
Kimi (Moonshot) is the China LLM to test first when ultra-long documents dominate context. Overseas access succeeds when you use the correct platform endpoint and model ID for your account region. Compare with GLM for agents (/en/articles/kimi-vs-glm-selection-guide-2026) and budget tokens carefully—long context multiplies cost (/en/articles/china-llm-api-pricing-2026).
10-minute first call
Create a Moonshot account allowed for your region → create API key → set OpenAI-compatible base URL from official docs → pick a current Kimi model ID with the context window you need → send a short then a long-document prompt → log tokens and P95 latency. Confirm IDs on the live console.
Long-context pitfalls
Stuffing entire PDFs without chunking can blow budgets and latency. Prefer retrieval + selective context when possible (/en/articles/china-llm-rag-selection-guide). Test tools + long context together if agents read documents (/en/articles/china-llm-agent-tool-calling-2026).
Next steps on Swift Horse
Kimi model page /en/models → vs GLM /en/articles/kimi-vs-glm-selection-guide-2026 → SDK /en/articles/china-llm-openai-compatible-sdk-2026 → failover /en/articles/china-llm-latency-failover-2026.
FAQ
Can overseas teams use Kimi API?
Many can via Moonshot platform paths; verify eligibility, latency, and compliance for your region.
When should I choose Kimi over DeepSeek?
When document length dominates; DeepSeek often leads coding POCs—see /en/articles/china-llm-coding-assistant-2026.
Is Kimi OpenAI API compatible?
Moonshot offers OpenAI-compatible endpoints for many chat models. Test streaming and tools on your SDK.
Is this official Moonshot documentation?
No—independent Swift Horse quickstart. Authoritative specs live on Moonshot docs.