Connect a model

Minnow does not ship model weights. Connect a local runtime, download and serve a model inside Minnow, add a cloud API, or use an installed agent CLI. You need at least one connection, and you can have several at once.

Everything on this page lives in the Models app. Open it from the app rail.

Pick your route

Mixing is normal and often the right answer: a small fast local model for routine turns, a cloud model bound to the roles that need real reasoning. See Routing.

Not sure which to pay for, or whether you need to pay at all? Costs and providers compares prices, subscriptions, free tiers, and local hardware.

LM Studio

1. Install and open LM Studio.
2. Download a chat model and load it.
3. Open the Developer / Local Server tab and start the server. The default is http://localhost:1234.
4. In Minnow: Models → Providers. If LM Studio is already running on its default port, Minnow detects it. Otherwise add the base URL yourself.
5. Refresh the provider, then pick a model from the menubar model chip.

Seeing [providers] fetch failed in a log at startup is normal when LM Studio is not running yet. Start the server and refresh.

Ollama

1. Install Ollama and pull a model (ollama pull …).
2. Ollama exposes an OpenAI-compatible API at http://localhost:11434.
3. In Models → Providers, add or confirm a provider with that base URL, then refresh.

As with LM Studio, Minnow registers Ollama automatically when it is already listening on the default port.

Serve a model inside Minnow

If you would rather not run a separate app, Minnow can do the whole job.

• Discover → Recommended estimates memory use from your CPU, RAM, GPU, and selected context. Start here if you do not know what your machine can handle.
• Discover → Hugging Face searches repositories. Inspect a model’s files, choose a quantization, and download it. Pause and resume transfers from the Downloads shelf.
• My models lists downloaded weights. Open a model’s inspector to load it with llama.cpp, or MLX on Apple Silicon. Minnow registers the running model as a provider.
• Local Server shows loaded models, runtime status, and logs. Storage manages model folders and Hugging Face credentials.

Model files are large and excluded from backups by default. See Backup and restore.

Cloud APIs

Any OpenAI-compatible HTTPS endpoint works. Models → Providers has one-click presets for common services — OpenCode Go/Zen, Anthropic, DeepSeek, GitHub Copilot, OpenRouter, OpenAI, Groq, Mistral — plus a custom option where you supply a base URL yourself.

API keys are encrypted at rest with AES-256-GCM under a key file in your Minnow home. If you lose that key file, the keys cannot be decrypted and you re-enter them. Read Privacy and security before you paste a key you care about.

Using a cloud provider, including a cloud-connected agent CLI, sends prompts and context to that provider. See Privacy and security for other network services and permissions.

Agent CLIs

Open Models → CLIs, scan for installed Claude Code, Codex, or Cursor CLI, then expand a row and enable it. If it is missing, Install opens the vendor installer in Minnow Terminal, and Update runs the CLI’s own updater there. Sign in opens an inline connection flow: approve access in your browser and Minnow verifies the login automatically. Verify checks an existing login.

The CLI’s models appear in the normal picker and can be assigned to chats and work agents. Minnow applies its mode restrictions and tool permissions to their tool calls. Vendor account requirements, model access, and usage limits apply. Background helper tasks are off by default for CLI connections.

See Models → CLIs for supported CLI versions, conversation persistence, and usage displays.

Choosing the model for a turn

There are two different pickers, and confusing them causes a lot of “why is it using the wrong model?” confusion:

The list is whatever your enabled providers report on refresh. If it is empty, the provider is not reachable or has no model loaded.

Local runtimes usually expose Load / Unload controls in the composer picker, which act on the model that chat is bound to — not the global default.

Routing: which model does what

Models → Routing binds models to roles instead of making one model do everything. The shared Utility tasks binding covers chat titles, prompt and issue expansion, and git commit messages. Leave it unset to use each task’s current composer, top-bar, or editor model. Evaluation, research, planning, review, and board work keep their own bindings.

Two neighbouring sections shape how models behave:

• Sampler — temperature, top-p, top-k, min-p, penalties, max tokens. Defaults are tuned to avoid the repetition-loop failure mode common in local models; change them only if you know what you are chasing.
• Thinking — reasoning mode and budget for models that expose it.

Usage & cost tracks token totals and, if you enter per-million pricing, what it cost you.

Model routers

Models → Routers groups models from My models and configured providers. Set each entry’s concurrent slots, then select the router in the normal model picker. A chat keeps its assigned model while that model remains available; failures can move it to another entry.

Router failover clears a failed partial reply before starting the replacement response. Local models can load on demand. Use Default for new chats to select a workspace default without changing existing chats.

See Models → Routers for capacity, overrides, and failover behavior.

When the picker stays empty

1. Is the provider process actually running?
2. Is a model loaded in it? Minnow lists only what the provider reports.
3. Is the base URL right, including /v1 where the provider requires it?
4. Press refresh in Models → Providers.

If replies arrive empty or garbled, the endpoint is probably not speaking standard /v1/chat/completions SSE. Try a different model or provider profile.

Next

Your first chat

Related

• Costs and providers — what each route costs, including free options
• Models app — the full tour
• Voice — speech-to-text and text-to-speech models
• Troubleshooting