When an agent runs day and night, every model call affects the cost of the job—and one rate limit can interrupt it. Connect your existing workflow to supported LLMs with one GPTProto key and shared balance. Choose the model for each step and see its rate before you scale.
Give my agent a GPTProto setup it can route with.
1. One base_url for everything: https://gptproto.com/v1
2. Route by task, not by vendor:
plan → claude-opus-5
execute → gpt-5.6
extract → glm-5.2
3. Stay OpenAI-compatible — same SDK, same tools, same streaming.A rate limit interrupts the job. More providers mean more accounts to manage. Every step adds to the bill.
A rate limit interrupts the job.
One failed call can stop a multi-step task until your application retries or handles the error.
Read the limits docsMore providers mean more accounts to manage.
Different steps may need different models, keys and balances.
Get one API keyEvery step adds to the bill.
Input tokens, output tokens and repeated runs determine what the workflow actually costs.
Check current input and output rates before assigning models to planning, extraction, or response steps.
Claude Code, OpenClaw, Feishu / Telegram agent frameworks automating coding, office work, content distribution and scheduled tasks.
OpenAI / Anthropic compatibleStable high throughputTool calling| Model | Price: GPTProto | vs Official | vs OpenRouter | Context | Modalities | Stability | Action |
|---|---|---|---|---|---|---|---|
 Claude Opus 5Claude | $4.50 / $22.50$0.45 Cache read · per 1M tokens | −10% | −15% | 1M | → | Try | |
 GPT 5.6 SolOpenAI | $3.20 / $16.00$0.32 Cache read · per 1M tokens | −20% | −24% | 1.05M | → | Try | |
 Gemini 3 Pro PreviewGoogle | $1.20 / $7.20$0.12 Cache read · per 1M tokens | −40% | −43% | 1.05M | → | Try | |
 DeepSeek v4 ProDeepSeek | $1.12 / $3.37$0.04 Cache read · per 1M tokens | −15% | −19% | 1.05M | → | Try | |
 GLM 5.2Z-AI | $1.26 / $3.96$0.23 Cache read · per 1M tokens | −10% | −15% | 1.05M | → | Try | |
 Kimi K3MoonshotAI | $2.70 / $13.50$0.27 Cache read · per 1M tokens | −10% | −15% | 1.05M | → | Try | |
 Qwen3 MaxQwen | $1.08 / $5.40$0.22 Cache read · per 1M tokens | −10% | −15% | 262K | → | Try |
Repo-wide edits, refactors and test loops — long tool-call chains where context window and price per step decide how far an agent can go.
Long contextTool callingLow cost| Model | Price: GPTProto | vs Official | vs OpenRouter | Context | Modalities | Stability | Action |
|---|---|---|---|---|---|---|---|
| Claude Opus 5Claude | $4.50 / $22.50$0.45 Cache read · per 1M tokens | −10% | −15% | 1M | → | Try | |
| GPT 5.6 SolOpenAI | $3.20 / $16.00$0.32 Cache read · per 1M tokens | −20% | −24% | 1.05M | → | Try | |
| Gemini 3 Pro PreviewGoogle | $1.20 / $7.20$0.12 Cache read · per 1M tokens | −40% | −43% | 1.05M | → | Try | |
| DeepSeek v4 ProDeepSeek | $1.12 / $3.37$0.04 Cache read · per 1M tokens | −15% | −19% | 1.05M | → | Try | |
| GLM 5.2Z-AI | $1.26 / $3.96$0.23 Cache read · per 1M tokens | −10% | −15% | 1.05M | → | Try | |
| Qwen3 MaxQwen | $1.08 / $5.40$0.22 Cache read · per 1M tokens | −10% | −15% | 262K | → | Try |
The current top 10 models by aggregate benchmark score — reasoning, coding and knowledge combined into one number.
Aggregate scoreFrontier tierUpdated as models ship| Model | Price: GPTProto | vs Official | vs OpenRouter | Context | Modalities | Stability | Action |
|---|---|---|---|---|---|---|---|
| Claude Fable 5.1NewClaude | $15.84 / $63.36$1.58 Cache read · per 1M tokens | −20% | −22% | 200K | → | Try | |
| Qwen3.8 MaxNewQwen | $1.80 / $5.40$0.19 Cache read · per 1M tokens | −10% | −27% | 1M | → | Try | |
| GPT 6 AstraOpenAI | $8.00 / $40.00$2.60 Cache read · per 1M tokens | −20% | −39% | 1.05M | → | Try | |
| Claude Opus 5Claude | $4.50 / $22.50$1.44 Cache read · per 1M tokens | −10% | −76% | 1M | → | Try | |
| Claude Fable 5Claude | $9.00 / $45.00$1.28 Cache read · per 1M tokens | −10% | −45% | 1M | → | Try | |
| GPT 5.6 SolOpenAI | $3.20 / $16.00$2.40 Cache read · per 1M tokens | −20% | −74% | 1.05M | → | Try | |
| GLM 5.3Z-AI | $1.26 / $3.96$0.13 Cache read · per 1M tokens | −10% | −24% | 1.31M | → | Try | |
 Grok 4.6Grok | $1.20 / $3.60$0.60 Cache read · per 1M tokens | −40% | −61% | 500K | → | Try | |
| Kimi K3MoonshotAI | $2.70 / $13.50$0.47 Cache read · per 1M tokens | −10% | — | 1.05M | → | Try | |
| GPT 5.6 TerraOpenAI | $1.60 / $9.60$1.60 Cache read · per 1M tokens | −20% | −80% | 1.05M | → | Try |
Choose a workload and expected frequency to see a suggested top-up. Check the cost estimate below before you decide.
Video and agent workloads burn credits faster — the recommendation adjusts automatically as you switch scenario or usage level.
Keep your agent logic where it is. Use GPTProto to access supported models with one key and shared balance.
Planning, execution and extraction have different price-to-quality tradeoffs. Point each one at a different model behind the same key — one endpoint, one bill, no per-vendor glue code.
Major models are served through redundant upstream channels, so a single provider outage never takes your app with it.
Browse modelsContinuous monitoring with automatic traffic shifting — issues are routed around before your users ever notice a thing.
Enter your expected runs, calls, and token usage to compare current model rates. See the assumptions behind every estimate.
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."
Use one balance across supported models at their published rates. See your credited amount before payment.
Get started. Great for testing the endpoint and trying new models.
The sweet spot for individual developers and small projects shipping to production.
Built for teams running production workloads. Bonus credits stack on already-discounted model pricing.
Check model access, usage and billing details before you integrate.
Yes. One GPTProto key can access supported models from multiple providers, with usage drawn from a shared balance. Your agent chooses the model for each call. Check the model page for its supported capabilities and request format before switching models.
GPTProto can use alternative upstream routes for supported requests when a route has a problem. A rate limit, timeout, or interrupted response can still cause a request to fail. Set timeouts, retries, and backoff in your agent, and check the limits for the models you plan to use.
For an existing OpenAI-compatible chat integration, start by updating the base URL, API key, and model ID. Then test the features your workflow depends on, such as streaming, tool calls, and structured output, with each selected model. Your agent's task logic stays in your application or framework.
Give the agent its own API key with an amount limit and limit period, and check usage and remaining balance in the dashboard. You can also limit the number of steps or model calls in each run from your application. If the key reaches its limit or the balance runs out, requests may stop until you adjust it.
Each model has its own published rate. Eligible top-up bonuses add credits to your balance; model requests then use that balance at the applicable rate. To estimate your workload cost, check both the selected models' current rates and the credits shown at checkout.
If your company needs an invoice, contact the GPTProto team before topping up. They can confirm which billing documents are available for your account and what company details are required.
Compare models, learn API setup, and explore image and video workflows for real projects.
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.