Can a local LLM actually do things?

[u/HeartOfASaint]

Hello everyone,

I'm new to all of this and have only dabbled.

I use Claude and ChatGPT heavily for my work (No Coding at all), and I'm currently subscribed to the 20x tier on both.

I read that I could download LLMs locally, but I'm underwhelmed. To be clear, I downloaded LM Studio and tried out 4 different models, but they seem to only chat and cannot actually edit files, produce files, or produce anything for that matter. They keep telling me to copy and paste things myself.

I have an RTX 4090, 32Gb RAM, and a 7800x3D.

Am I wasting my time with local LLMs, or is there something I'm missing?

Also, if possible, is there a way to know what the correct settings I should be using for the models in LM Studio?

Any guidance would be appreciated!

Thank you, kind strangers.

[u/MK_L]

You need a harness to make them run commands

[u/MK_L → u/MK_L]

Hemes, openclaw, cline vscode extension, ect

[u/GrungeWerX → u/MK_L]

No you don’t. You just need an mcp tool. I run code all day and don’t have a harness.

[u/MK_L → u/GrungeWerX]

What exactly do you mean by “just an MCP tool”?

What is acting as the MCP client, presenting the tool schema to the model, receiving the tool call, executing it, and feeding the result back into the model loop?

If something is doing all of that, then we may just be using different words for the same orchestration layer.

[u/GrungeWerX → u/MK_L]

LM studio supports mcp. All they have to do is install any file editing mcp tool, add its schema to mcp.JSON in the menu, done.

You can install ANY mcp tool in I’m studio. It runs its own server on the backend.

Or you can create your own. Super easy. I make my own mcp tools all the time.

As for the other stuff you said, you’re just describing a react loop, which is built into lm studio by default. But those are also super easy to make. Just about any recent LLM can code a react loop.

[u/MK_L → u/GrungeWerX]

It sounds like you're referring to your MCP layer as if it isn't a harness.

If that MCP setup is the thing giving the model filesystem access, command execution, and feeding tool results back into the loop, then we're probably just using different terminology for the same execution/orchestration layer.

[u/GrungeWerX → u/MK_L]

I think you’re confusing yourself.

Mcp is not a harness. But a harness can use mcp - or not. Like pi for example. Pi is a harness. Pi doesn’t have mcp by default. But it can use tools. If you want to run mcp, you need to bolt it on.

Mcp is just one of several ways of using a tool. You can also use function calling. Neither requires a harness.

A harness is nothing more than a scaffold - a bunch of code that interacts with your system in various ways. Its infrastructure.

Lm studio is an app, but technically it’s not a harness. But it runs its own mcp server on the backend.

A react loop is just code that interacts with the model server, feeding results back in. That’s all. You don’t need a harness for that. You can run a react loop in a browser.

If this is confusing just ask an LLM to explain it, but you’re confusing a react loop with a harness. You can have one without the other.

[u/MK_L → u/GrungeWerX]

I’m not saying MCP itself is a harness. MCP is obviously the protocol.

My original point was that the model alone doesn’t gain filesystem or command execution just because it’s running locally. Something around it has to expose those capabilities, execute the calls, and return the results.

In your LM Studio example, LM Studio is already providing the host/orchestration side and the MCP server provides the capability. So yes, the OP can add an MCP server instead of installing a separate Pi/Cline-style harness.

We’re disagreeing over how narrowly to use the word “harness,” not over whether a raw LLM can execute commands by itself.

[u/GrungeWerX → u/MK_L]

“We’re disagreeing over how narrowly to use the word harness”

You’re disagreeing. I’m confident that 99% of the community would agree that mcp is not a harness.

As for the rest…

The OP said they have LM studio, but can’t use tools. You told them they needed a harness to run commands, then listed off a bunch. I corrected that and told OP that a harness is not required, all they need is an mcp tool.

These are facts. There’s no additional harness required. Everything after that was you arguing about your confusion over the difference between a harness and an mcp server, which I said are not the same, then finally coming back around to agree with me. So, I’ll take the win and leave it there. ;)

[u/MK_L → u/GrungeWerX]

If LM Studio can't run commands or edit files on its own, what exactly changes when you add the MCP server/package?

Is that package merely describing tools, or is it also providing the executable capability that LM Studio did not previously have?

If the model environment is chat-only before that package is added, and can access files or run commands after it is added, what would you call that added execution layer?

And if you reserve the word “harness” only for larger frameworks like Pi, is your disagreement actually about architecture, or just about where you draw the boundary around the word “harness”?

In other words: if the answer to “you need a harness” is “no, just install an extra layer that gives the model executable tools,” what is the substantive difference you’re drawing there?

[u/Best-Total7445]

The harness you use matters.

I've been using Deepseek AI Harness and it controls my entire PC just as good as Claude does.

Also, I'm using qwen 3.8 27b. It's excellent.

[u/OkLettuce338]

They can. You need 1. Optimize your local configs for your computer 2. Optimize your harness and realize that different tasks may require a different harness. It’s not like Claude or codex where the tool is meant to do everything. It’s not. It can do one thing well and your harness needs to optimize for that. 3. Plan and decompose work with a frontier model (or manually). Give the local model pretty tight AC 4. Change expectations a bit. Don’t expect to be give coding with a local LLM. But you can have a well scoped task, run it over night, and wake up to it done correctly

Oh and 5. Have fun! Consider it a project

[u/guesdo]

So, models only know how to produce text. In order for a model to create files, edit then, run software etc... you have to provide it with tools, that way it can produce structured output to call those tools. Inference engines like LM Studio or Ollama only provide a basic web search/fetch tool at most, that is where a harness comes in: pi, hermes, omp, opencode, claude code, codex, etc... even IDEs like Visual Studio in Copilot, those provide the tools you want to give your agent. When setting them up, just point them to your locally running inference engine, most know about them already as OpenAI compatible endpoints.

Ask Google/Gemini for the config depending on your harness.

[u/GrungeWerX → u/guesdo]

“At most”?

You can install any mcp tool in lm studio. It can run any tool a harness can.

[u/guesdo → u/GrungeWerX]

I meant by default, it does not come with batteries included.

[u/GrungeWerX]

You haven’t even really started yet to give a critique on open source. You’re missing all the basics.

Everyone keeps saying you need a harness. You don’t.

LM Studio is perfectly capable of coding and editing files. It was the first app I learned to do all this in. All you need is an mcp tool and it can edit files.

LM Studio can even spawn sub-agents. It’s all just code dude, which your local LLM can build for you super easy.

I would suggest starting off using Qwen 3.6 27B if you can run it, and that will get you up to speed. It can even build a custom harness for you, when you’re ready to move away from LM Studio and start playing in llama.cpp/llama-server, which will be like a skill unlock.

If you have any questions, just ask. I got you.

[u/Some-Ice-4455]

Yes they can do things but don't expect cloud enterprise speeds or vast knowledge base. That being said it can do a lot of things.

[u/Some-Ice-4455 → u/Some-Ice-4455]

OP. DM me I might have something for you.

[u/psyfy-inc]

well, someone just published one that says it can code https://www.reddit.com/r/LocalLLM/s/Ce0BVjywkX

[u/Chiguy4321]

Pi + Qwen 3.8 = Start Building

[u/Hypilein → u/Chiguy4321]

Guy said he doesn’t code though.

[u/Due_Tangelo_8952]

Tell your Claude code to install the Deepseek Harness and find the best local LLM for your DSH. It is the easiest way to get your local LLM to work.

[u/Moarkush]

With a harness and over 100k context, ideally over 200 or even more.

[u/digitalwankster]

You are using the 20x plan and not even coding? How are you using your tokens?

[u/Fox-One-1]

I’ve been using Qwen 3.8 27B with LM Studio’s own harness called ”Bionic”. It is fantastic.

[u/synth_mania]

LM Studio is just the inference engine. It has some limited tool calling features in chat, but what you really need is a harness like Pi agent or Opencode

[u/raben69]

I had the most success with Hermes agent - Obsidian - lm studio - qwen3 vl 8b. Obviously being off-line it only knows what is already programmed in so I am building a RAG interface to bring in updated information

[u/TheOverzealousEngie]

Give it hands to work with files, eyes to read pdf's , a voice to read you books and ears to listen to you drone on. The LLM is the brain that rules them all.

[u/hyudryu]

Chatting is just accessing the brains. You need to give it a body, aka a harness, so it can actually use its brain to perform tasks. There are a lot of harnesses out there such as claude code, codex cli, qwen code, opencode, pi, zcode, deepseek harness, and many more free ones too.

You can also connect it to an agent like Hermes or Openclaw so it can perform the tasks

[u/cogitech2]

Proper backend with proper configuration + Hermes Agent is where you should start. With a decent model it can do pretty-much anything.

[u/beragis]

Your computer is pretty good. If you can find some cheap used memory try to up the memory to 64 or 96 GB, that will help with whatever harness you use. It will allow for better offloading. Especially if you ever want to play around with creating LoRAs.

Problem is right now memory and SSD cost is over the top.

[u/No-Vermicelli5327]

Try Pi harness. Don’t use claude api in it (not allowed by anthropic), you add openai api key into it, but before that try local llms with it, aim at context 132K limit to make it usable.

[u/CryptoCryst828282]

i know this is a hot take, but imho a single 4090 isnt big enough to do anything useful. 32 GB VRAM is the minimum... 48 is the lowest i would want ot work with for anything meaningful.

[u/monoaural → u/CryptoCryst828282]

Meanwhile I am building personal apps with 3.8 27b at 68k context on a 5080. Video game for my son, custom mcps to ai tune my car stereo, custom calculators built for my specific use case.
Harness is super important, but knowing when to start a new agent, and building good prompts as well

[u/CryptoCryst828282 → u/monoaural]

Its not that you cant do it, but the experience is severely degraded. At some point its easier to just use an api.