Use models served by LM Studio as local Stellary execution targets while the project, cards, documents, assignments, and results remain in the shared workspace.
LM Studio
Connected
Stellary
Launch workspace
Stellary Desktop connects to the local server, exposes ready models, and lets you decide which models other workspace agents may use.
01
Start LM Studio and make the selected model available through its local API.
02
Add or detect the local server from Stellary Desktop.
03
Expose only the ready models authorized for the current workspace.
04
Select local execution and the compatible LM Studio target on an agent.
05
Launch an eligible mission and keep its result in Activity.
Mission STL-128
Start LM Studio and make the selected model available through its local API.
Checklist
Linked context
Only models reported as ready by a connected machine appear as usable targets.
The model runs on the connected machine. Stellary controls whether it is visible to the workspace and keeps the mission attached to the project.
Only models reported as ready by a connected machine appear as usable targets.
Private local models stay private until the user explicitly shares them with the workspace.
Local server responses are useful, but some targets do not edit repositories or support every agent tool.
1. Start LM Studio local server
2. Open Stellary Desktop
3. Connect or refresh local AI apps
4. Share the ready model with the workspace
5. Select it on an agent using local executionLM Studio is useful when a team wants a model served from its own machine for project responses. The machine must remain connected and the server must report the model as ready.
Model privacy and workspace availability are separate choices: seeing a model yourself does not automatically make it available to every member or agent.
A local API server may produce text without offering the repository-editing behavior of an agent CLI. Stellary should expose that distinction instead of presenting every model as interchangeable.
Use LM Studio for eligible response or analysis missions. Use a CLI runner such as Codex or Claude Code when the mission needs to operate directly in a linked codebase.
LM Studio local server
Agent CLI runner
Primary capability
LM Studio local server
Serve model responses through a local API.
Agent CLI runner
Operate as a coding agent in a repository.
Repository changes
LM Studio local server
Not assumed.
Agent CLI runner
Available when the runner and policy support them.
Model choice
LM Studio local server
Models loaded and served locally.
Agent CLI runner
Models exposed by the installed CLI.
Best fit
LM Studio local server
Private local inference and response tasks.
Agent CLI runner
Tool-using code missions.
No. LM Studio runs on the connected local machine. Stellary Desktop reports the available server and models to the workspace catalog.
No. The user chooses which ready models are shared with the workspace. Other local models remain private.
Repository editing is not assumed for local API servers. Use a compatible agent CLI runner when the mission needs direct codebase operations.
Its local targets are no longer available for new missions. The interface should show that state instead of allowing a silent failure.
Keep inference on your machine while the mission and review remain in Stellary.
Download Stellary Desktop