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.
One API Key for AI AgentsThat Run 24/7.
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.What Gets Harder as YourAgent Runs More Often
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.
Compare the ModelsYour Agent Calls Most.
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 throughput도구 호출| 모델 | 가격: GPTProto | 공식 대비 | OpenRouter 대비 | 컨텍스트 | 모달리티 | 안정성 | 작업 |
|---|---|---|---|---|---|---|---|
| $4.50 / $22.50$0.45 캐시 읽기 · 1M 토큰당 | −10% | −15% | 1M | → | 사용해 보기 | ||
| $3.20 / $16.00$0.32 캐시 읽기 · 1M 토큰당 | −20% | −24% | 1.05M | → | 사용해 보기 | ||
| $1.20 / $7.20$0.12 캐시 읽기 · 1M 토큰당 | −40% | −43% | 1.05M | → | 사용해 보기 | ||
| $1.12 / $3.37$0.04 캐시 읽기 · 1M 토큰당 | −15% | −19% | 1.05M | → | 사용해 보기 | ||
| $1.26 / $3.96$0.23 캐시 읽기 · 1M 토큰당 | −10% | −15% | 1.05M | → | 사용해 보기 | ||
| $2.70 / $13.50$0.27 캐시 읽기 · 1M 토큰당 | −10% | −15% | 1.05M | → | 사용해 보기 | ||
| $1.08 / $5.40$0.22 캐시 읽기 · 1M 토큰당 | −10% | −15% | 262K | → | 사용해 보기 |
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.
긴 컨텍스트도구 호출저비용| 모델 | 가격: GPTProto | 공식 대비 | OpenRouter 대비 | 컨텍스트 | 모달리티 | 안정성 | 작업 |
|---|---|---|---|---|---|---|---|
| $4.50 / $22.50$0.45 캐시 읽기 · 1M 토큰당 | −10% | −15% | 1M | → | 사용해 보기 | ||
| $3.20 / $16.00$0.32 캐시 읽기 · 1M 토큰당 | −20% | −24% | 1.05M | → | 사용해 보기 | ||
| $1.20 / $7.20$0.12 캐시 읽기 · 1M 토큰당 | −40% | −43% | 1.05M | → | 사용해 보기 | ||
| $1.12 / $3.37$0.04 캐시 읽기 · 1M 토큰당 | −15% | −19% | 1.05M | → | 사용해 보기 | ||
| $1.26 / $3.96$0.23 캐시 읽기 · 1M 토큰당 | −10% | −15% | 1.05M | → | 사용해 보기 | ||
| $1.08 / $5.40$0.22 캐시 읽기 · 1M 토큰당 | −10% | −15% | 262K | → | 사용해 보기 |
종합 벤치마크 점수 기준 현재 상위 10개 모델. 추론, 코딩, 지식을 하나의 숫자로 묶습니다.
종합 점수최전선 수준모델 공개에 맞춰 업데이트| 모델 | 가격: GPTProto | 공식 대비 | OpenRouter 대비 | 컨텍스트 | 모달리티 | 안정성 | 작업 |
|---|---|---|---|---|---|---|---|
| $15.84 / $63.36$1.58 캐시 읽기 · 1M 토큰당 | −20% | −22% | 200K | → | 사용해 보기 | ||
| $1.80 / $5.40$0.19 캐시 읽기 · 1M 토큰당 | −10% | −27% | 1M | → | 사용해 보기 | ||
| $8.00 / $40.00$2.60 캐시 읽기 · 1M 토큰당 | −20% | −39% | 1.05M | → | 사용해 보기 | ||
| $4.50 / $22.50$1.44 캐시 읽기 · 1M 토큰당 | −10% | −76% | 1M | → | 사용해 보기 | ||
| $9.00 / $45.00$1.28 캐시 읽기 · 1M 토큰당 | −10% | −45% | 1M | → | 사용해 보기 | ||
| $3.20 / $16.00$2.40 캐시 읽기 · 1M 토큰당 | −20% | −74% | 1.05M | → | 사용해 보기 | ||
| $1.26 / $3.96$0.13 캐시 읽기 · 1M 토큰당 | −10% | −24% | 1.31M | → | 사용해 보기 | ||
| $1.20 / $3.60$0.60 캐시 읽기 · 1M 토큰당 | −40% | −61% | 500K | → | 사용해 보기 | ||
| $2.70 / $13.50$0.47 캐시 읽기 · 1M 토큰당 | −10% | — | 1.05M | → | 사용해 보기 | ||
| $1.60 / $9.60$1.60 캐시 읽기 · 1M 토큰당 | −20% | −80% | 1.05M | → | 사용해 보기 |
Find a Starting Balance
for Your Workload
Choose a workload and expected frequency to see a suggested top-up. Check the cost estimate below before you decide.
영상과 에이전트는 크레딧이 더 빨리 줄어듭니다. 용도나 사용량을 바꾸면 추천도 자동으로 바뀝니다.
A Simpler Model API Layer
for Your Agents
Keep your agent logic where it is. Use GPTProto to access supported models with one key and shared balance.
Choose a model for each step
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.
Use one key and shared balance
Major models are served through redundant upstream channels, so a single provider outage never takes your app with it.
Browse models24시간 모니터링
계속 모니터링하고 트래픽을 자동으로 전환합니다. 사용자가 알아차리기 전에 문제를 우회합니다.
Estimate Your Agent'sModel Costs
Enter your expected runs, calls, and token usage to compare current model rates. See the assumptions behind every estimate.
See How Builders UseGPTProto
실재하는 공개 계정의 글입니다. 여기 있는 것은 만들어낸 것이 아닙니다.

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."
Top Up When
You Need To
Use one balance across supported models at their published rates. See your credited amount before payment.
시작용입니다. 엔드포인트 확인과 새 모델 시험에 맞습니다.
개인 개발과 프로덕션에 올리는 작은 프로젝트에 맞는 균형입니다.
프로덕션 워크로드를 돌리는 팀용입니다. 이미 할인된 모델 요금에 보너스 크레딧이 더해집니다.
Questions About ConnectingYour Agent?
Check model access, usage and billing details before you integrate.
01Can one API key connect my existing agent to different models?
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.
02What happens if an agent request hits a rate limit or an upstream model fails?
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.
03Do I have to rebuild my agent to use GPTProto?
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.
04How do I keep an agent that runs around the clock within budget?
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.
05How do model discounts and top-up bonuses affect my costs?
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.
06Can I get an invoice for my company?
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.
AI 모델 가이드.실용적인 API 튜토리얼.
모델 비교, API 설정, 이미지와 영상 작업 흐름을 정리했습니다.
다음 1억 토큰은정가일 필요가 없습니다.
브라우저에서 이미지와 영상을 만들거나, API 키 하나로 텍스트, 이미지, 영상 모델을 앱에 넣을 수 있습니다. 할인 요금도 확인할 수 있습니다.
- ✓OpenAI 호환
- ✓200개 이상 모델
- ✓공식보다 10–30% 저렴
- ✓높은 가동률, 자동 페일오버