A local provider in Flame
Flame supports LM Studio alongside Ollama and compatible endpoints for model-powered surfaces such as chat, inline completion, and focused AI actions.
LM Studio integration
Use LM Studio local models in your development workspace
LM Studio can provide the local model endpoint. Flame supplies the project context and the development workspace around it: files, Git, terminals, tests, debugging, and review.
The developer problem
A local endpoint is more useful when it can work with the project in front of you.
Running a model locally gives developers control over the endpoint and model selection, but it should not force them to move project context into a separate chat interface. Files, diffs, test output, and terminal errors are part of a coding conversation.
Flame connects LM Studio as a local AI provider. That lets developers use their local model with project-aware AI surfaces while keeping Git, terminals, testing, debugging, and code review in the same desktop workspace.
A connected workflow
A local LM Studio coding workflow
The tool remains the system you know. Flame provides the local workspace where the work moves forward.
- 01
Configure the local endpoint
Add LM Studio in Flame’s AI settings and select an available local model for the AI surface where it fits.
- 02
Bring in the codebase context
Use selected files, diffs, terminal output, test results, and browser state as scoped context instead of manually copying fragments to another application.
- 03
Work with local developer tools
Keep your terminal, test runner, debugger, API client, and Git review in the project workspace while you use the model.
- 04
Choose the right provider per task
Use LM Studio for a local-model task, then select a cloud provider or a full coding-agent runtime when another job requires it.
How it works in Flame
LM Studio in Flame, with clear boundaries
Local requests stay on the host
When configured with a local LM Studio endpoint, Flame sends model requests to that local endpoint. This does not automatically make external services, browser resources, or every configured provider local.
Use real development context
Scoped AI context can include selected files, diffs, terminal output, test results, and browser state, while the project’s Git, terminal, test, and debugging tools remain in Flame.
Keep provider choice flexible
LM Studio can coexist with Ollama, cloud APIs, and Flame’s full coding-agent runtimes. Changing models does not require changing the projects, branches, or review workflow around them.
FAQ
LM Studio integration questions
Use LM Studio with Flame.
Download Flame to keep implementation, verification, review, and the final Git decision in one workspace.
Free to use on macOS, Windows, and Linux.