AICredits vs LiteLLM: Managed Gateway vs Self-Hosted Proxy

What LiteLLM does well

LiteLLM is an excellent open-source proxy that unifies 100+ LLM providers behind a single OpenAI-compatible endpoint. It is free, self-hosted, and has a massive community (40K+ GitHub stars, 1,000+ contributors). If you have DevOps capacity and are comfortable running your own infrastructure, LiteLLM is a legitimate choice.

Netflix, Lemonade, and RocketMoney use LiteLLM — mostly for internal routing and cost control. The GitHub star count and Docker pull volume are genuine signals of a healthy open-source project.

Where AICredits fills the gap

LiteLLM does not solve the Indian developer payment problem. You still need international credit cards to pay OpenAI, Anthropic, and other providers directly. You also need to run and maintain LiteLLM infrastructure — either on your own VPS or inside your Kubernetes cluster.

AICredits is a managed service. You do not run anything. You create an account, top up your wallet in INR via UPI, and make API calls. No servers to maintain, no Redis to configure, no Docker Compose to debug at 2 AM when production breaks.

Feature comparison at a glance

| Feature | LiteLLM | AICredits | |---------|---------|-----------| | Open source | ✅ | ❌ | | Self-hosted | ✅ | ❌ | | INR billing via UPI | ❌ | ✅ | | Managed service | ❌ | ✅ | | Multi-provider routing | ✅ | ✅ | | Per-key budget limits | ✅ | ✅ | | Semantic caching | ❌ | ✅ | | PII masking guardrails | ❌ | ✅ | | Setup time | Hours–days | Minutes |

When to use LiteLLM

Choose LiteLLM if:

• You have DevOps bandwidth and want full infrastructure control
• You need enterprise features like SSO and audit logs
• You want self-hosted data residency
• You are already paying providers in USD and just need routing logic

When to use AICredits

Choose AICredits if:

• You are an Indian developer or team and need INR billing via UPI
• You want a managed service with zero infrastructure overhead
• You are getting started and do not want to commit to self-hosted complexity
• You need semantic caching and guardrails without building them yourself

Migration: switching from LiteLLM to AICredits

If you are currently running LiteLLM and want to try AICredits, the switch is one line:

# LiteLLM proxy
client = OpenAI(base_url="http://your-litellm-proxy:4000", api_key="...")
 
# AICredits — same SDK, same model IDs
client = OpenAI(base_url="https://api.aicredits.in/v1", api_key="sk-your-aicredits-key")

Your model IDs and request format stay the same. You can run both in parallel during a transition period — route some traffic to AICredits for testing while keeping LiteLLM as the fallback.