1endpoint
A unified API that gives developers access to many AI language models through one endpoint, with transparent per-token pricing and no platform fees.
🔗 Visit 1endpoint
Description
If you've ever built something on top of ChatGPT, Claude, or another AI model, you know the annoyance: every provider has its own API, its own pricing, its own quirks, and switching between them means rewriting integration code. 1endpoint solves that by putting one API in front of many different AI models, so you can swap the model you're using — for cost, speed, or quality reasons — without touching your application code.
Technically, it's a usage-based gateway billed per token (1,000 credits = $1), with input rates ranging roughly $0.042 to $1.50 per million tokens depending on which underlying model you call. Prompt caching brings cached-token costs down by about 80%, which matters a lot if your app sends similar context repeatedly (chatbots, agents, RAG pipelines). There's no subscription and no platform fee layered on top of provider costs — you pay for what you use, plus the gateway's margin baked into the per-token rate. The pitch is squarely for developers who want provider flexibility and cost optimization without building their own multi-provider abstraction layer.
💬 Our review
The short version: 1endpoint is a sensible pick if you're tired of hard-coding a single LLM provider into your app and want the freedom to switch models without a rewrite — the usage-based, no-subscription pricing is the right model for this kind of infrastructure.
The category itself is now fairly crowded — OpenRouter is the best-known player doing essentially the same thing (one API, many models, usage-based pricing), and most major clouds (AWS Bedrock, Azure AI, Google Vertex) offer their own multi-model gateways for teams already committed to that ecosystem. 1endpoint's differentiator has to be pricing and caching efficiency rather than novelty, since the core idea — a model-agnostic proxy — is not new. The 80% discount on cached tokens is a genuinely useful lever for high-volume, repetitive-context apps (agents, support bots) where that alone could offset switching costs. Pick it if you want a lightweight, no-subscription entry point to multi-model access; if you're already deep in AWS or Azure, their native multi-model options may integrate more tightly with your existing billing and infra.
💰 Pricing
📊 Global score
🤖 AI-enriched data
Usage-based only, no subscription. 1,000 credits = $1. Input $0.042-$1.50/1M tokens by model, cached tokens ~80% cheaper.
Pros
One API for multiple LLM providers, swap models without code changes
No subscription or platform fee, pure usage-based billing
80% cheaper cached tokens — meaningful savings for agents/chatbots
Transparent, published per-token pricing
Cons
Crowded category — OpenRouter already does the same thing with more brand recognition
No mention of SLA, uptime guarantees, or enterprise support tiers
No self-hosted/open-source option for teams wanting full control