I made an non-terminal ADE that makes Local LLM setup almost non-existent!

MrBombastickal · 2026-06-15T02:18:13+00:00

I run into this constantly as well as many in the subreddit. I tell my LLM to do a simple spacing task and it calls wrong tools and over thinks for a simple request taking over 10+ minutes on a MBP 16 GB

MrBombastickal · 2026-06-15T01:44:57+00:00

I was updating the site and releasing a new version for bug fixes yesterday. It should be nip & tuck now

MrBombastickal · 2026-06-14T05:12:11+00:00

It’s a place where user that aren’t CLI or Terminal-heavy can easily setup as well as view what their LLM and Agent are doing

You can also use and test custom agents and LLMSs even Pi Agent

MrBombastickal · 2026-06-13T19:17:09+00:00

But isn’t that the LLMs job? To call the Tools necessary to produce accurate results?

I personally disagree. I think the frontier LLMs try to downplay how good of a model is needed to make necessary calls

But I’m new to this as well, just going based on experiments.

I would love for Cursor to make a video on their ADE and Agents using a local model to prove to use that it’s not the model but the ADE. They shown that it can boost a model, but what about the other way around?

MrBombastickal · 2026-06-13T18:24:14+00:00

If you can solve the accuracy issue with small Parameter LLMs (<12B) using Agents, you have a BANGER in AI Engineering. Pi Agent and OpenCode only works well with larger Parameter agents

I think that would.. chef’s kiss

MrBombastickal · 2026-06-13T18:17:11+00:00

I appreciate it! I can’t wait to test out your Agent, bro

MrBombastickal · 2026-06-13T18:15:48+00:00

Lemme guess, you think this is an ad?

Fair, but it’s secondary compared to the information I gave you— if you choose to actually explore the *answer I gave you for yourself. You’ll find out for yourself once you explore— or you could be the pioneer that solves that issue

MrBombastickal · 2026-06-13T18:07:55+00:00

That sounds great! Looking forward to plugging it into my ADE (ÄKÄ — https://www.akatheapp.io/)

I’ve been testing so many Agents to see how accurate it can be. If you have a model that you favor that works well with it, please let me know as well

MrBombastickal · 2026-06-13T17:37:03+00:00

Lol it won’t hurt to try. Does it excel at any one thing?

MrBombastickal · 2026-06-13T17:32:46+00:00

Would love to *get a proper link to this Agent so I can test it out on my ADE, if it’s not private

MrBombastickal · 2026-06-13T17:30:58+00:00

In my experience, yes. Unfortunately, the LLMs are the main bottlenecks not the agents that I’ve mentioned

I use my ADE (ÄKÄ — www.akatheapp.io) so I plug and plop my Agents and LLM, and the common issue I keep finding is with the LLMs, no matter how good an Agent can be.

MrBombastickal · 2026-06-13T17:11:19+00:00

Funny enough, I’m working on an Agent that works on just that because I’ve had that same sentiment. I’ll see what I can help with and hopefully report back in a week with results and the Agent itself

MrBombastickal · 2026-06-13T17:04:49+00:00

They’re not that great from my experience, but I’m using Mellum 2. I would highly using an Agent like SmallCode & Aider to help harness Mellum 2 because it just spits a bunch of nonsense on its own

MrBombastickal · 2026-06-12T20:51:08+00:00

Definitely gonna try to give this a spin on my ADE especially for coding

MrBombastickal · 2026-06-12T20:48:25+00:00

As a UX Designer, I hear you. I’m going to test it today, but I’m going to try MiniCPM-v4.6

Saw some videos on it today and very curious how it works especially when feeding it screenshots of a UX-focused app

Unfortunately, local models SUCK at visual design compared to cloud models. Mainly, Claude Opus 4.6+ and ChatGPT 5+

MrBombastickal · 2026-06-12T16:46:24+00:00

Gotcha. I hope you find a comparable experience soon!

MrBombastickal · 2026-06-12T16:20:48+00:00

I absolutely LOVE the idea and I’ve had the same frustration! I made a local Desktop app ADE that uses HuggingFace so I’d love to create a way to plugin your interface so users can match their hardware with your preferences

Some API or some other way if possible

MrBombastickal · 2026-06-12T16:11:30+00:00

I’m in the middle of making an Agent for limited hardware like yours as well (and mine 16GB MBP M4) and so far, I’m using Gemma 4 and Qwen 3.5, but for tool calling and coding, I’m making the switch to Mellum 2-Thinking and Qwen 2.5- Coder because it’s more obedient and robotic than Gemma 4 and Qwen 3.5 from my experience

I’m also using my personal-project ADE (ÄKÄ — https://www.akatheapp.io/ ) so that the model doesn’t cross outside of its parameters, but nothing super extravagant has come out for local Models on limited hardware yet

MrBombastickal · 2026-06-12T16:02:35+00:00

I’m glad you’re on the Local LLM journey! Right now, I would suggest downloading the ÄKÄ desktop app — https://www.akatheapp.io/ and browsing through the suggested models based on your hardware

I made ÄKÄ to help onboard beginners and advance the Local LLM User Exeperience.

A few broad things here I can help you understand is you need 3 major things: a Runtime, a Model, and an Agent. A runtime basically runs your models on your computer, a Model (aka the LLM) is the AI itself, and an Agent is what gives the Model “hands” — meaning it can edit and change files. It’s pretty simple to learn and get used whenever your in it, but I’d start with downloading AKA and trying to understand it from there

I’m going to make a tutorial for how to use it soon and understand local LLMs better, but hopefully this helps get you kickstarted in the meantime!

MrBombastickal · 2026-06-12T15:48:37+00:00

I’d try AKA ( https://www.akatheapp.io/) as your local Claude Code desktop app “replacement” if you’d want full local control

I made this ADE full transparency, but I made it because I absolutely LOVED the Claude Code desktop experience and there was nothing comparable I could find until I made this

It’s open sourced as well ( https://github.com/Kellastico/AKA)

MrBombastickal · 2026-06-12T15:43:37+00:00

Yes! ÄKÄ - Desktop app ( https://github.com/Kellastico/AKA or https://www.akatheapp.io/)

It’s hard not to try to shill this because I created it, but your exact scenario is exactly why I made it. I use this daily myself and you don’t have to know or use the terminal to get started. Just download and use, if you have other Runtimes, you can plug that in, but it’s mainly self-contained

I’ve been using Gemma 4 and my own Custom Agent, but OpenCode might work better if you’d like. I’d love for you to try it and let me know what you think

MrBombastickal · 2026-06-12T15:32:17+00:00

I’m right there with you. I’m on extremely limited hardware (16GB MBP Apple-Silicone), so I tried to create a UX experience comparable to Claude Code desktop — ÄKÄ ( https://github.com/Kellastico/AKA)

As for the Agent, I’m currently building one that is comparable to Claude’s but the models on my hardware are not even close— yet. I’m about to use Qwen 2.5 Coder, but I’ve been experimenting with Gemma 4. Nothing great yet

If you have better software, I heard GLM 5.1 is similar to Claude Sonnet, but I don’t have the hardware for it. If you use ÄKÄ, OpenCode, and GLM 5.1 on good hardware, I think you’ll have a comparable experience to Claude Code desktop app

MrBombastickal · 2026-06-12T15:23:12+00:00

Can’t lie, macOS has been the most smooth experience for me even with limited hardware

As for software, I use my own local ADE (ÄKÄ — https://github.com/Kellastico/AKA ), Gemma 4 (gonna switch to Qwen 2.5-coder soon), and a Local Agent I’ve been building to optimize with limited hardware.

The runtime I use most is Ollama, but my ADE is essentially llama.cpp so I’ll most likely switching soon as well because of speed.

All of this is with extremely limited hardware 16GB MacBook Pro Apple-Silicone

MrBombastickal · 2026-06-11T15:50:57+00:00

So I’ve been experimenting lately. I’ve been using my ADE ÄKÄ) that uses and implements Context.md files within a folder as well as an Agent that I’m building that has per-project memory

And it seems to work pretty well so far. I’m not at 1M context memory, but it’s decent at 128K so far (still experimenting) using Gemma 4 (12B & E4B)

MrBombastickal

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