Customer support and RAG
Evaluate retrieval, answer quality, and cost per resolved conversation.
LLM cost reduction
Reduce production AI model spend without starting from scratch.
ChinaAPI helps teams evaluate Chinese model families for eligible workloads where quality, latency, and cost can be compared against existing OpenAI, Claude, Gemini, or other model usage.
Where it works
Route the right workload to the right model.
Content and operations
Test repeatable internal workflows where volume is meaningful and risk is controlled.
AI app inference
Compare model outputs and cost for product features that call LLM APIs at scale.
Model fallback
Use Chinese model families as alternatives for selected tasks or regional customers.
How to evaluate pricing
Start from task-level economics, not token price alone. A good pilot compares success rate, retries, latency, output length, and operational support. The best savings usually come from routing specific workloads to a lower-cost model family, then expanding only after quality is proven.
Request LLM pilot pricing
Share the current stack and monthly spend.
Useful details include model provider, use case, monthly spend, token volume, latency requirement, and expected growth.