The cheapest way to call Claude, GPT & Gemini APIs

What “cheapest” should actually mean#

A lower price per token is only a saving if the response quality, context window and tool-calling behavior match what the official API would return. Chasing the lowest number without checking integrity is how people end up on a relay that quietly serves a smaller or quantized model. So treat price and verifiability as one decision, not two.

Where a gateway lowers your real cost#

• One bill, no per-vendor overhead. No separate Anthropic, OpenAI and Google accounts, cards, and monthly reconciliation.
• Route each task to the right-priced model. Use a cheaper model for drafts and a frontier model only when it matters — all under one key.
• Add Chinese-made models without extra hurdles. DeepSeek, Kimi and Qwen are often painful to sign up for from abroad; here they're behind the same key.
• Below official list price. DaoXE is priced under going direct — current advantage: typically ~30–80% below list via low-price groups (confirm on the pricing page).

Payment & real cost#

How to call each model family#

Every family is reachable through the same base URL and key. Claude is available through both the OpenAI-compatible path and the native Anthropic Messages path — use Messages for Claude Code and Anthropic SDKs.

Quick start (60 seconds)#

1. List your models. Copy an exact ID for the family you want.
2. Send one small request. Keep max_tokens tiny to keep the test cheap.
3. Compare quality & price. Against the official API for the same prompt, at temperature=0.

export DAOXE_API_KEY="your_api_key"

curl --fail-with-body --show-error --silent \
  https://daoxe.com/v1/models \
  -H "Authorization: Bearer ${DAOXE_API_KEY}"

curl --fail-with-body --show-error --silent \
  https://daoxe.com/v1/chat/completions \
  -H "Authorization: Bearer ${DAOXE_API_KEY}" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "YOUR_EXACT_MODEL_ID",
    "max_tokens": 64,
    "messages": [{"role": "user", "content": "Say hello in one sentence."}]
  }'

The catch nobody mentions#

Some cheap endpoints look great for a week, then quietly degrade — a smaller model, aggressive quantization, or a truncated context window. The fix isn't faith, it's measurement: run a fixed probe set on a schedule and diff against the official API. That's exactly what the open benchmark and the model-swapping guide are for.

Frequently asked questions#