# AnythingLLM vs LM Studio: which open source option fits your team?

> AnythingLLM and LM Studio both run models you choose on one machine, and the choice between them comes down to scope and governance. AnythingLLM is open source document chat; LM Studio is a closed-source app for local models; Kortix is the open-source AI Operating System a team owns.

URL: https://anythingllm-alternative.com/anythingllm-vs-lm-studio

## AnythingLLM vs LM Studio, with Kortix beside them

All three run models you choose; they differ on what a team can own, share, and review.

| | Kortix (recommended) | AnythingLLM | LM Studio |
| --- | --- | --- | --- |
| Open source | Yes | Yes | No |
| What it is | Open-source AI Operating System: agents, skills, memory, connectors in one repo | Local-first desktop and Docker app for chatting with your documents | Desktop app for running local models on your own machine |
| Model support | Any model provider with your own keys | Local and cloud LLM providers | Local models via llama.cpp and MLX |
| Self-host | Self-host free; cloud, VPC, or on-prem | Desktop app; multi-user on Docker | Desktop app for macOS, Windows, and Linux |
| Where agents and config live | Files in one git repo you own | In the app, per workspace | On your own computer |
| Review gate | Session work reaches main through a change request a person approves | No review gate; answers stay in the app | No review gate; configuration stays on the machine |

_In the repo_

## One agent and its reach, declared in kortix.yaml

`kortix.yaml`

```yaml
agents:
  support-triage:
    file: agents/support-triage.md
    connectors: all
```

Source: https://github.com/kortix-ai/suna

An agent is markdown plus a `kortix.yaml` block. Connector credentials are brokered server-side and never enter the machine.

## What each tool is

AnythingLLM is an open-source, local-first app for chatting with your own documents. It runs on your own machine, ingests PDFs and other files into a workspace, and ships a no-code agent builder, MCP compatibility, and multi-user support on its Docker deployment ([anythingllm.com](https://anythingllm.com/)).

LM Studio is a closed-source desktop application for running local large language models on macOS, Windows, or Linux. It downloads model weights, serves them on an OpenAI-like local endpoint, and can attach documents to a chat for offline reading ([LM Studio docs](https://lmstudio.ai/docs/app)). It is built for one machine.

Kortix is the open-source AI Operating System: your agents, their skills, your company memory, and every connector live in one git repo you own, and each session runs on its own cloud computer ([Kortix docs](https://kortix.com/docs)).

## What separates them is scope and governance

Both AnythingLLM and LM Studio run any model you choose, and both can read your documents, so the model runtime is common ground. The difference is what each one keeps and who can review it.

AnythingLLM keeps its state inside the app, scoped to a workspace, so what one workspace learns stays there. LM Studio keeps its models, prompts, and configurations on one computer. Kortix keeps the agents, the skills, the company memory, and the connector rules as files in a git repo the team owns, so a change to how the team works arrives as a diff a person reviews.

## When to pick each one

Pick LM Studio when you want to try a model on your own hardware: download an LLM, chat with it, and serve it on a local endpoint for your own scripts.

Pick AnythingLLM when the job is document chat and retrieval, on one machine or one Docker host, and you want to start in minutes.

Pick Kortix when the work has to be shared and governed across a team. Each session runs on its own cloud computer, session work reaches `main` through a change request a person approves, and connectors reach 3,000+ apps plus MCP, OpenAPI, GraphQL, and raw HTTP. Connector credentials are brokered server-side and never enter the machine.

## What the open-source split means here

AnythingLLM and Kortix are open source, so you can read, fork, and audit the code. LM Studio is not; it ships as a desktop app with no repository to read or fork ([LM Studio docs](https://lmstudio.ai/docs/app)).

For one person, that difference is small. For a team, it decides what you keep. With an open-source system, the agent definitions, the memory, and the connector rules are files you can diff and roll back, and a new teammate clones the repo to get the whole setup. The [open-source AnythingLLM alternatives](/best-anythingllm-alternatives) page lists the wider field, and the [Kortix vs AnythingLLM](/kortix-vs-anythingllm) page covers the pair directly. Kortix also has a longer write-up on its blog ([Kortix](https://kortix.com/blog/kortix-vs-anythingllm)).

Rival details are from each project's own website and repository, checked October 2026.

## AnythingLLM and LM Studio questions, answered

The details the comparison does not cover.

### Can AnythingLLM use LM Studio as its model?

Yes. AnythingLLM connects to local and cloud providers, and its repository lists LM Studio among the local providers it supports ([AnythingLLM on GitHub](https://github.com/Mintplex-Labs/anything-llm)).

### Does LM Studio have a shared team mode or a review gate?

No. LM Studio is a desktop app for one machine, and its documentation covers local models, a chat interface, and a local API, with no shared deployments or approvals ([LM Studio docs](https://lmstudio.ai/docs/app)).

### Can Kortix run local models?

Kortix takes any model provider with your own keys, chosen per agent, per session, or per message, and you can also sign in with the ChatGPT plan you already pay for ([Kortix docs](https://kortix.com/docs)).

### What do the two tools cost?

LM Studio and AnythingLLM are free to download. Kortix self-host is free; on Kortix Cloud, Free is $0 with 200 credits per month and 1 project, and the team plan is $40 per seat per month with 2,500 credits per month per seat, pooled ([Kortix pricing](https://kortix.com/pricing)).

## Run a team's agents from one repo you own

Kortix is open source. Any model, your keys, self-host for free or use Kortix Cloud.

[Try Kortix](https://kortix.com) · [Read the docs](https://kortix.com/docs)

Open source · Any model, your keys · Self-host, VPC, or on-prem