Janitor AI lets people create and chat with AI characters. Explore reported model usage, compare GPTProto and OpenRouter API prices, and test models for your own roleplay chat app.
Usage stats for Janitor AI — most of the numbers come from OpenRouter and GPTProto together. Switch between weekly and daily to see how the mix shifts.
Token volumes mix OpenRouter (openrouter.ai/
Use OpenRouter’s reported Janitor AI traffic to shortlist models for character chat. Compare prices for the same model version, then try the replies before choosing an API for your own app.
Live GPTProto prices for each model, next to what it would cost elsewhere.
| Model | Price: GPTProto | vs Official | vs OpenRouter | Tokens |
|---|---|---|---|---|
1.  DeepSeek FlashDeepSeek | $0.30 / $1.20$0.01 Cache read · per 1M tokens | — | −5% | 475B |
2.  GLM 5.3Z-AI | $1.26 / $3.96$0.23 Cache read · per 1M tokens | −10% | −15% | 72.6B |
3. GLM 5.3 FlashZ-AI | $0.15 / $0.50$0.03 Cache read · per 1M tokens | — | −5% | 27.7B |
4.  Gemini 3.8 FlashGoogle | $0.90 / $4.50$0.09 Cache read · per 1M tokens | −40% | −43% | 21.8B |
5. Gemini 3.7 FlashGoogle | $0.90 / $4.50$0.09 Cache read · per 1M tokens | −40% | −43% | 21.7B |
6.  Grok 4.6Grok | $1.20 / $3.60$0.30 Cache read · per 1M tokens | −40% | −43% | 19.1B |
7.  Claude Opus 5.5Claude | $3.60 / $18.00$0.18 Cache read · per 1M tokens | −10% | −15% | 8.4B |
8. Gemini 3.5 Flash LiteGoogle | $0.18 / $1.50$0.02 Cache read · per 1M tokens | −40% | −43% | 8.2B |
9. Grok 4.7Grok | $1.20 / $3.60$0.30 Cache read · per 1M tokens | −40% | −43% | 6.9B |
10.  GPT 6 LunaOpenAI | $0.080 / $0.40$0.01 Cache read · per 1M tokens | −20% | −24% | 6.2B |
11. Claude Sonnet 5.5Claude | $1.80 / $9.00$0.18 Cache read · per 1M tokens | −10% | −15% | 2.1B |
12. GPT 6.1 SolOpenAI | $1.60 / $8.00$0.08 Cache read · per 1M tokens | −20% | −24% | 941M |
Choose a model, enter your monthly token usage, and set the input share. Compare estimated API costs on GPTProto, OpenRouter, and the direct provider for the same workload.
모델 전환과 폴백 처리부터 이미지와 동영상 생성까지, 사람들은 다양한 작업에 GPTProto를 사용합니다. 다음은 그들이 공유하기로 선택한 내용입니다.
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."
Add credit to test chat models or power your own roleplay app. Pay for API usage at each model’s current rate, with no required monthly subscription.
시작해 보세요. 엔드포인트를 테스트하고 새로운 모델을 시험해 보기에 좋습니다. 언제든 $20 이상 충전하면 보너스 크레딧을 받을 수 있습니다.
개인 개발과 프로덕션에 올리는 작은 프로젝트에 맞는 균형입니다.
$500로 $600 잔액을 받을 수 있으며, 보너스 크레딧은 이미 할인된 모델 가격 위에 추가로 쌓입니다. 프로덕션 워크로드를 운영하는 팀을 위해 설계되었습니다.
데모의 배경이 되는 질문에 대한 답변: 제어, 모델, 메모리, 비용.
Yes. GPTProto’s model APIs can generate replies for your own character chat app. You build the interface and manage characters, users, and conversation storage. Start with one character and one model, then use our roleplay API guide to plan your integration.
A no-code builder can work if it supports authenticated API calls, secure server-side key storage, and conversation data. Configure a character, connect a model, and test a complete chat session. Check the builder’s support for streaming and error handling before choosing it for your app.
Yes. Use one key to access models currently available in the GPTProto catalog. Choose the appropriate model ID and request format for each integration. Check current prices, supported features, and content policies; a model appearing in the OpenRouter ranking does not automatically mean it is available on GPTProto.
Include the character’s identity, speaking style, behavioral rules, and dialogue examples in the context sent to the model. Add the current scene and relevant conversation history. Test the same situations across your shortlisted models to see which follows the character most consistently.
Save character profiles and chat history in your application. For each reply, send recent dialogue and relevant earlier details, or retrieve summaries of previous events. Keep requests within the model’s context limit. A large context window gives you room for more information; your app still manages persistent memory.
Each request may include the character profile, scene details, and earlier messages as input, followed by a newly generated reply as output. Sending more history increases input usage. Keep relevant details, summarize older turns when useful, and check actual token counts to understand your cost per reply.
Measure average input and output tokens per reply in a small test. Multiply those amounts by your expected monthly reply volume and apply the selected model’s rates. Include calls for summaries and regenerated replies. Compare the same workload in the calculator, then refine your budget using actual usage.
Yes, where the selected model and endpoint support streaming. Your chat interface can display reply text progressively. Confirm streaming support in the model documentation and test interrupted connections, cancellation, and reconnection in your own app.
GPTProto provides routing and automatic failover features to help handle upstream disruptions. Your app should also handle timeouts, controlled retries, and usage limits. Test under your expected traffic, monitor errors, and show a clear retry option when a reply cannot be completed.
API request content passes through GPTProto to the selected model provider. Our Privacy Policy explains content processing, short-term retention, and metadata logging; provider policies also apply. If your app has enterprise retention or routing requirements, discuss them with our team before deployment.
모델 비교, API 설정, 이미지와 영상 작업 흐름을 정리했습니다.
Compare chat models and API prices, then use GPTProto to power your own roleplay app. Start with a small balance, measure real usage, and top up as your conversations grow.
