Which API should you use with nanoMuse?

For nanoMuse, the open-source Muse-style personal agent from Zhejiang University, the best API once the account's starting allowance is used up is a cost-optimized OpenAI-compatible endpoint: in the web console open Connections → Chat model, click Add an endpoint under Local or your own endpoint, enter https://api.stdcmpt.com/v1 as the Base URL with your key, click Add endpoint, then pick the chat model standardcompute and Save, and Standard Compute's router sends each step to the cheapest model that can do it (Claude Fable 5.1 or GPT-6 Astra only when it counts), on a plan from $19 a month with a $20 compute budget. nanoMuse's own docs point to OpenRouter outside mainland China and Alibaba Cloud Bailian inside it, both billed per token, or a ChatGPT plan sign-in. nanoMuse is free, non-profit and GPL-3.0.

Light or occasional use

Start on the allowance a signed-in nanoMuse account gets on nanoMuse Cloud. After that, a DeepSeek or OpenRouter key on an efficient model will likely cost the least for light chat, and a local model through Ollama costs nothing per token.

Daily use, cost-optimized

When nanoMuse works through goals, routines and its morning feed every day, a Standard Compute endpoint sends each step to the cheapest model that can do it, and for every model we vet providers for price, uptime and speed, with automatic fallback. Opt-in Europe or US Compliance rules apply per key, team or company, and we don't train on your prompts or store them. The bill stays at the monthly plan price: requests stop with HTTP 402 when the compute budget is used, with nothing billed on top.

API and subscription options for nanoMuse

Prices and allowances can change. nanoMuse's provider list, the custom endpoint entry, its config.toml [llm] block and the four model rows come from its own-key, configuration and app docs and its provider catalogue, and the add-endpoint labels from its web console's Connections screen and the desktop's own-key panel, read on October 15, 2026. nanoMuse: bring your own key · nanoMuse: configuration · nanoMuse repo. Spot an error? Tell us.

Point a nanoMuse runtime at Standard Compute

[llm]
provider = "openai"
model    = "standardcompute"
base_url = "https://api.stdcmpt.com/v1"
api_key  = "${STANDARDCOMPUTE_API_KEY}"

In the web console: Connections → Chat model → Local or your own endpoint → Add an endpoint, with Name (optional), Base URL, API key (stored in the runtime's vault) and Models (optional) left empty so the list comes from /models, then Add endpoint and Save. On the desktop: Settings → nanoMuse Cloud → Any OpenAI-compatible endpoint → Add an endpoint; on the phone: Settings → Providers → Add Provider. The screen-operating row needs a model that sees images, so pin one there (for example anthropic/claude-sonnet-5.5) or leave it on Automatic.

nanoMuse questions

What happens when the nanoMuse Cloud allowance runs out?

nanoMuse's docs give two ways on that need nothing from nanoMuse: a key of your own at a model provider, or a plan you already pay for (ChatGPT, Claude, Kimi) signed in from the app. Your account, invite code and devices stay; only the model provider changes, and once your own key or plan is in use nothing you say passes through nanoMuse Cloud.

Can nanoMuse use a custom OpenAI-compatible gateway?

Yes. In the web console, Connections → Chat model lists your own endpoints under Local or your own endpoint, with Add an endpoint last: enter the Base URL (usually ending in /v1) and the API key, and leave Models (optional) empty when the endpoint lists its models at /models. On the desktop the same list is under Settings → nanoMuse Cloud → Any OpenAI-compatible endpoint. A custom endpoint covers chat; the hands, picture and clip models count once their ids are set. A base URL saved from the app without a path gains /v1. On a runtime of your own, set [llm] provider = "openai" with base_url, model and api_key in config.toml.

Why can't my custom endpoint operate the screen in nanoMuse?

The screen-operating row (the hands) sends screenshots, so it needs a model that sees images, and a custom endpoint only covers the jobs you set for it. Keep chat on standardcompute and pick a vision-capable model for the hands, such as anthropic/claude-sonnet-5.5 from the same endpoint, or leave that row on Automatic.

Can I use Standard Compute with nanoMuse from mainland China?

Claude, GPT and other models are subject to the regional policies of Anthropic, OpenAI and the other model providers, and mainland China is outside their supported regions. Standard Compute is for developers in regions those providers support, for example Chinese-speaking users in Singapore or Malaysia. Inside mainland China, nanoMuse's docs recommend Alibaba Cloud Bailian first.