AI Cost Firewall – OpenAI-compatible gateway with semantic caching
LLM gateway with Redis + Qdrant caching, but LiteLLM does this.

LLM API gateway with 2x credit matching, but model names appear fabricated.
AI application developers managing multi-model inference and cost optimization
Lambda Labs · Together AI · Anthropic API
It's an OpenAI-compatible API gateway. Swap your base URL to frogapi.app/v1, keep your SDK code, and pick from 9 models: GPT-5.2, GPT-5-Mini, GPT-5-Nano, DeepSeek-V3.2, Mistral-Large-3, Llama-4-Maverick, Kimi-K2.5, Grok-4.1-Fast, GPT-OSS-120B.
Per-token pricing matches the source models exactly. The way it works out cheaper: every deposit is matched with free credits. Put in $10, get $20 in credits. So your effective cost per token is half.
No subscriptions, no tiers. Pay per token.
Would love feedback.
LLM gateway with Redis + Qdrant caching, but LiteLLM does this.
Runs as a single binary with embedded SQLite and zero-config start, acting as a transparent, provider-agnostic proxy that logs model, tokens, latency, cost and API key hashes while leaving full body capture opt-in. It also proxies streaming responses in real time and exposes stable JSON analytics endpoints — a practical, instrumentable way to get reproducible, audit-ready traces for real LLM traffic, though long-term value depends on how it handles provider edge-cases and SDK compatibility.
Drop-in proxy that cuts GPT token costs 40-60% without changing app code.
Drop-in OpenAI API gateway with failover—LiteLLM does this but this has a dashboard.
Multi-backend LLM manager when Ollama and LM Studio already handle this.
Go gateway with circuit breakers, but auth isn't production-ready yet.