As an indie developer building AI products, I kept hitting the same wall: how do I control LLM costs without vendor lock-in?
Direct API keys meant zero visibility into per-project spending. Month-end surprise bills. No way to cap costs per feature. Rate limit headaches.
So I built CostLLM — an OpenAI-compatible API gateway that sits between your code and the LLM provider.
client = OpenAI(api_key="sk-proj-...")
client = OpenAI(
base_url="https://api.costllm.ai/v1",
api_key="YOUR_COSTLLM_API_KEY"
)
| Model | Type |
|---|---|
| deepseek-v4-flash | Fast chat |
| deepseek-v4-pro | Complex reasoning |
| deepseek-chat | General purpose |
| deepseek-reasoner | Deep analysis |
Building a production API gateway taught me a lot about concurrency, streaming, error handling, and payment webhooks. The hardest part wasn't the code — it was designing a pricing model that works for both free users and growing teams.
I'd love feedback from other developers working with LLM APIs — especially around cost visibility, key management, and what you'd want from a gateway.