Keep the coding CLI you already use. Compare GPTProto rates for supported models, connect through the protocol your client expects, and test the setup on one task before moving a full workflow.
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...A refactor can involve many model calls. Before changing providers, check the rate for your model, the client protocol, and how failed requests are handled.
The bill grows across long sessions.
Repo-wide edits and repeated test loops can use more input, output and cached tokens than a short chat. Compare the rate for the model and token types you actually use.
Compare model rates →A 429 can interrupt a run.
Rate limits and upstream errors can break a coding session. Check your client's retry behavior and test GPTProto's supported routes before moving important work.
How requests are handled →A mismatched endpoint wastes time.
Claude Code, Codex CLI and OpenCode do not all use the same API shape. Choose your client first, then follow its matching endpoint and model setup.
Check GPTProto's current input, output and cache-read rates beside the provider's published API rates. Discounts vary by model; availability in a specific CLI depends on its protocol and supported features.
The models Claude Code, Codex CLI and their peers ship with — the ones you are most likely already sending. Rates are per 1M tokens, discounted from each vendor's list.
Llamada a herramientasContexto largoCache-aware pricing| Modelo | Precio: GPTProto | vs Oficial | vs OpenRouter | Contexto | Modalidades | Estabilidad | Acción |
|---|---|---|---|---|---|---|---|
 Claude Opus 5Claude | $4.50 / $22.50$0.45 Lectura de caché · por 1M de tokens | −10% | −15% | 1M | → | Probar | |
| Claude Sonnet 5Claude | $1.80 / $9.00$0.18 Lectura de caché · por 1M de tokens | −10% | −15% | 1M | → | Probar | |
| Claude Haiku 4.5 (Build 20251001)Claude | $0.90 / $4.50$0.09 Lectura de caché · por 1M de tokens | −10% | −15% | 200K | → | Probar | |
 GPT 5.2 CodexOpenAI | $1.23 / $9.80$0.12 Lectura de caché · por 1M de tokens | −30% | −34% | 400K | → | Probar | |
| GPT 5.1 Codex MaxOpenAI | $0.88 / $7.00$0.09 Lectura de caché · por 1M de tokens | −30% | −34% | 400K | → | Probar | |
| GPT 5.4 MiniOpenAI | $0.60 / $3.60$0.06 Lectura de caché · por 1M de tokens | −20% | −24% | 400K | → | Probar | |
| GPT 5 NanoOpenAI | $0.035 / $0.28$0.00 Lectura de caché · por 1M de tokens | −30% | −34% | 400K | → | Probar |
Wide-context models for repo-scale reads and high-volume background jobs, plus the cheapest per-token options for agent loops that fire thousands of calls.
1M contextBajo costoStable JSON output| Modelo | Precio: GPTProto | vs Oficial | vs OpenRouter | Contexto | Modalidades | Estabilidad | Acción |
|---|---|---|---|---|---|---|---|
| GPT 5.6 LunaOpenAI | $0.16 / $0.96$0.02 Lectura de caché · por 1M de tokens | −20% | −24% | 1.05M | → | Probar | |
 GLM 5.2Z-AI | $1.26 / $3.96$0.23 Lectura de caché · por 1M de tokens | −10% | −15% | 1.05M | → | Probar | |
 DeepSeek v4 ProDeepSeek | $1.12 / $3.37$0.04 Lectura de caché · por 1M de tokens | −15% | −19% | 1.05M | → | Probar | |
 Kimi K3MoonshotAI | $2.70 / $13.50$0.27 Lectura de caché · por 1M de tokens | −10% | −15% | 1.05M | → | Probar |
Choose the kind of CLI work you do and how often you run it. This is a starting point; your actual spend depends on model choice and token usage.
Batch work and long-context runs burn credits faster — the recommendation adjusts automatically as you switch workload or usage level.
GPTProto exposes different API routes for different clients. Select a supported model, configure the matching endpoint and key, then confirm a short coding task works as expected.
2 lines changed · 0 code rewrites · 200+ models on one key · model names stay the same.
GPTProto exposes different API routes for different clients. Select a supported model, configure the matching endpoint and key, then confirm a short coding task works as expected.
See which client uses the Anthropic-compatible Messages route and which needs the OpenAI Responses route. Copy only the setup for your CLI.
Manage supported model access and API spending in one GPTProto account. Check the rate and available features before changing a model in your CLI.
Explore supported models →Where a supported model has alternative upstream routes, GPTProto may reroute eligible requests. A request can still fail; keep retry and backoff in your client.
Select a model and enter your monthly input, output and cached-input tokens. We compare the same workload against that model's published provider API rates.
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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."
Start with a small balance, test a real session and scale up when you know your usage. Model prices and any top-up bonuses are shown separately.
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.
The answers that matter when you compare model rates and test a new endpoint.
These clients have different provider settings and API requirements. GPTProto offers Anthropic-compatible Messages and OpenAI Responses routes for supported models. Choose the guide for your client and run a short test; a model listed in the catalog is not automatically compatible with every CLI feature.
Claude Code uses an Anthropic-compatible Messages route when configured with a compatible gateway. Codex CLI's custom providers use the Responses API. Each client needs its own base URL, authentication settings and supported model ID; follow the matching guide instead of copying one CLI's config into another.
Start by changing the provider configuration, then test the tasks you rely on. Prompt and repository files may remain the same, but streaming, tool calls, model options and output formats can behave differently. Check a real edit-and-test loop before switching your daily workflow.
Use the model ID shown in GPTProto's catalog for the route you selected. Model availability and supported features may differ by endpoint. Check the model page and your CLI setup guide before starting a long run.
No API can promise that. Limits and upstream failures can still occur. GPTProto may route eligible requests through alternative channels where supported, but your CLI or application should still handle retries and backoff. Test behavior with your chosen model before moving important work.
This page compares model API usage, billed according to tokens and applicable model rates. It does not change a subscription or bundled usage you may have with the CLI vendor. Check whether your current workflow uses a subscription, a vendor API key or both before comparing costs.
We apply the selected model's input, output and, where relevant, cached-input rates to the monthly usage you enter. The comparison uses the same token quantities at the provider's published API rates. Any top-up bonus appears as a separate line so you can see the model discount on its own.
If a top-up tier includes bonus credits, the checkout page shows the total credit you receive. Usage is charged at the displayed GPTProto model rate. Bonus amounts, eligibility and validity depend on the current offer; check them before paying.
Yes, you can restore your previous provider settings. Keep a copy of the original configuration and test both paths with a small task. Unused GPTProto credit remains subject to the account terms shown at checkout.
Your key, account, chosen model and upstream route can each have limits. Review the limits shown for your account and model, and contact support before a workload that needs guaranteed capacity. The page should not promise unlimited calls without a documented commitment.
Each guide should list the current client version, API route, model ID, authentication steps, a short verification task and common errors.
Crea imágenes y videos en el navegador, o lleva modelos de texto, imagen y video a tu app con una clave de API. También puedes ver tarifas con descuento.