Point Claude Code and Codex CLI at one endpoint. Same models, same protocol, same SDK — 10–30% below each vendor’s list price. Pay per token, no minimum, no subscription.
Set up GPTProto for Claude Code.
1. In ~/.claude/settings.json, under "env" set:
ANTHROPIC_BASE_URL = "https://gptproto.com"
ANTHROPIC_API_KEY = "sk-gptproto-<your key>"
Keep it exactly like that - no /v1, no trailing slash. Claude Code appends /v1/messages itself, so a /v1 here becom...Automation built on agent frameworks — coding, office ops, content distribution and scheduled jobs running unattended.
Tool callingOpenAI-compatibleHigh throughputReliable routing| Model | Price · GPTProto | vs Official | vs OpenRouter | Context | Modality | Stability | Action |
|---|---|---|---|---|---|---|---|
 Grok 4.1 Fast ReasoningGrok | $0.12 / $0.30$0.03 cache read · per 1M tokens | −40% | −43% | — | → | Try | |
 DeepSeek v3DeepSeek | $0.16 / $0.65per 1M tokens | −40% | −43% | — | → | Try | |
 GPT 5.6 LunaOpenAI | $0.16 / $0.96$0.02 cache read · per 1M tokens | −20% | −24% | 1.05M | → | Try | |
| DeepSeek v4 FlashDeepSeek | $0.30 / $1.20$0.01 cache read · per 1M tokens | — | −5% | 1.05M | → | Try | |
| Grok 4Grok | $1.80 / $9.00per 1M tokens | −40% | −43% | — | → | Try | |
 GLM 5.2Z-AI | $1.26 / $3.96$0.23 cache read · per 1M tokens | −10% | −15% | 1.05M | → | Try | |
 Claude Sonnet 4.6Claude | $2.70 / $13.50$0.27 cache read · per 1M tokens | −10% | −15% | 1M | → | Try | |
| GPT 5.4 MiniOpenAI | $0.60 / $3.60$0.06 cache read · per 1M tokens | −20% | −24% | 400K | → | Try | |
| GPT Image 2OpenAI | $6.40per image | −20% | −24% | — | → | Try | |
| GPT 4.1 MiniOpenAI | $0.28 / $1.12$0.07 cache read · per 1M tokens | −30% | −34% | 1.05M | → | Try | |
| Claude Opus 5Claude | $4.50 / $22.50$0.45 cache read · per 1M tokens | −10% | −15% | 1M | → | Try | |
 Gemini 3.5 Flash LiteGoogle | $0.18 / $1.50$0.02 cache read · per 1M tokens | −40% | −43% | 1.05M | → | Try | |
| GPT 4o MiniOpenAI | $0.10 / $0.42$0.05 cache read · per 1M tokens | −30% | −34% | 128K | → | Try | |
 Minimax M3MiniMax | $0.48 / $0.96$0.10 cache read · per 1M tokens | −20% | −24% | 1.05M | → | Try | |
| Claude Sonnet 5Claude | $1.80 / $9.00$0.18 cache read · per 1M tokens | −10% | −15% | 1M | → | Try | |
| Grok 4.3Grok | $0.75 / $1.50$0.12 cache read · per 1M tokens | −40% | −43% | 1M | → | Try | |
| Grok 4.7Grok | $1.20 / $3.60$0.30 cache read · per 1M tokens | −40% | −43% | 500K | → | Try | |
| DeepSeek FlashDeepSeek | $0.30 / $1.20$0.01 cache read · per 1M tokens | — | −5% | — | → | Try | |
 Hy4 PreviewHunyuan | $0.79 / $2.38$0.04 cache read · per 1M tokens | −5% | −10% | 1.05M | → | Try | |
| GPT 6 AstraNewOpenAI | $8.00 / $40.00$0.80 cache read · per 1M tokens | −20% | −24% | 1.05M | → | Try |
Choose a workflow and usage level to see an example monthly cost on GPTProto, alongside the same usage at comparable provider rates.
Batch work and long-context runs burn credits faster — the recommendation adjusts automatically as you switch workload or usage level.
Two environment variables for Claude Code, three lines of config.toml for Codex CLI. Nothing else in your project moves.
2 lines changed · 0 code rewrites · 200+ models on one key · model names stay the same.
Both CLIs point at the same origin. One balance covers every client, and a dropped channel does not stop the session.
Anthropic-native and OpenAI-compatible routes are served from one origin, so both CLIs point at the same host. No gateway, no adapter, no extra SDK.
Every CLI, cron job and agent draws on the same balance, at the same discounted rates. Top up once — bonus credits spend at those rates too.
See top-up tiersMajor models run on redundant channels. If one hits its limit or goes down, traffic shifts to a backup — the ceiling is that channel’s, not the platform’s.
Choose a model and enter your monthly usage to compare estimated costs on GPTProto, the official provider, and OpenRouter.
Real posts from real, public accounts — nothing here is invented.
For a team already juggling DeepSeek, Kimi, Qwen, or other providers, a shared routing layer can be reasonable if it removes duplicated work and the fallback behavior is tested. GPTProto is one implementation of this approach.
I've been testing GPTProto recently, and it's honestly made my creative workflow much simpler. Instead of paying for multiple subscriptions, I can access several leading AI models from one place.
I turned this single prompt into a cinematic fantasy video using GPTProto. "Continuous 15-second cinematic shot, 4K resolution, hyper-realistic dark fantasy photorealism…"
I challenged myself to create a cinematic AI cooking short in just 15 seconds. I used GPTProto to bring the entire workflow together, from image generation to video, all in one place.
Made with Seedance 2.0 + GPT Image 2 on GPTProto. A Pixar-style commercial with the perfect glow.
What worked for me was pointing the cloud connections at GPTProto so the frontend only sees one endpoint and I just change the model name to swap. I am not rebuilding a connection from scratch every time.
I route the calls through GPTProto so a fallback is a config switch instead of a weekend rewrite when a model disappears. It turns "my default model just got export controlled" from an incident into a config change.
I used to switch between different AI tools just to compare results. Now I just use GPTProto. GPT-5, Claude, Gemini, Kimi, and more — all in one workspace.
I route the calls through GPTProto so the model id and latency land in one place regardless of which provider is behind it. The win is having the log schema consistent across providers.
I created this 15-second cinematic product video with GPTProto using Seedance 2.0, and I was really impressed by how smooth the workflow was.
GPTProto routes the character prompt and shot list to a top model on one API key: 20 minutes … voices it and burns in captions from the same key: 20 minutes.
Text, images, and voice are configured separately. You can keep OpenRouter for text and use GPTProto for visuals.
The call layer underneath the router is GPTProto, so swapping a model does not require provisioning a new provider integration. Changing models becomes cheap enough that the question stops being "should we change."
You only pay for what you use. One balance covers Claude Code, Codex CLI and every other client you run — top-ups of $20+ earn bonus credits that spend at the same discounted rates.
Enough to point one CLI at the endpoint and run a real session. Top up $20+ anytime to unlock bonus credits.
The sweet spot for a developer running Claude Code and Codex CLI every day without watching the meter.
Built for a fleet of CLIs and agent runners. Bonus credits stack on top of already-discounted model pricing, so the whole balance prices 10–30% under list.
Short answers. No sales talk.
Any client that speaks one of the two protocols OpenAI and Anthropic already defined. That covers Claude Code, Codex CLI, OpenCode, Cline, Kilo Code and most OpenAI-SDK agent frameworks out there. You choose the protocol by choosing the base URL — nothing gets installed in between.
Because the two clients append different paths. Claude Code appends /v1/messages to whatever you set, so its base URL must be https://gptproto.com — no /v1, no trailing slash. Add /v1 and the request goes to /v1/v1/messages, which returns 404. Codex CLI is the mirror image: it expects the OpenAI-compatible route, which only exists under /v1/chat/completions, so its base_url is https://gptproto.com/v1.
No. Both endpoints are protocol-compatible, so your SDK, streaming, tool calls, function schemas and the CLI binaries themselves are untouched. What changes is a base URL and an API key — environment variables or one config file. Most people are running in under ten minutes.
The IDs match the underlying models, so the ones you already use — claude-opus-5, claude-sonnet-5, gpt-5.2-codex, glm-5.2 — keep working. GET /v1/models on the same host returns the full list if you want to check a specific one before switching.
No seat fee and no fixed plan — you pay per token against upstream capacity we buy in bulk, and the discount is passed through as a flat multiplier per model. Claude models are ~10% under list, the Codex family ~30%, and everything in between. The rate is the rate: it does not shrink as you use more.
Yes. Bonus credits from a top-up spend at the same discounted model prices, so the 10–30% applies across your whole balance — including the credits you did not pay for. A $500 top-up lands as $600 of balance that buys $600 at discount rates.
Requests route through redundant upstream channels with automatic failover. If a channel 429s or drops, traffic shifts to a backup rather than failing your request. You can still pin your own model fallback in the request if you want deterministic routing.
There is no per-minute ceiling you have to plan around the way you do on a single vendor’s plan — throughput comes from the pooled channels behind each model. Fair-use limits apply per account; if a workload needs sustained very high concurrency, contact us from your registered email and we will size it.
Yes, trivially. Nothing is installed and nothing was rewritten, so reverting is changing the same two values back. Your balance stays in the account and there is no subscription to cancel or term to sit out.
Exact base URLs, model IDs and per-endpoint examples for both protocols.
Create images and videos online, or bring text, image, and video models into your app with one API key. Explore discounted rates on selected models.