u/Top_Power5877

Local AI for Mac Directory (https://bunnysoft.app/local-ai-mac-apps)

Hello friends! As a local LLM enthusiast, I've been very open to ways to increase my local AI usage. Previously, I've tried running local models via Ollama, llama.cpp, or vllm. I've even fine-tuned my own Gemma model

However, I've struggled to truly embrace local AI because I can't find durable use cases other than learning and tinkering. For my bread and butter - coding, I use Codex and Claude because I need to be as productive as possible. For everything else, my usage is so sporadic, I forget the proper llama.cpp launch commands when the time comes around.

With the release of Apple M5 and ultra compact local models more recently, I am becoming more confident about another possibility that we've been collectively sleeping on: the rise of local AI apps - products that package local models, workflows, and UI to serve a narrow purpose well. Apps remove the operational pain disproportionately felt during casual usage, and allow more of us to expand AI usage by covering diverse workflows with AI apps, instead of tokenmaxxing on narrow areas.

I made a directory site to survey the local AI apps landscape, and the results are surprisingly good: there are tons of options in LLM chat, transcription, OCR, Photo editing categories (50+ apps each), and some truly unique use cases such as wardrobe stylists and pet health assistants that I had no idea existed. There are 82 categories currently. Please check this out if you're interested! https://bunnysoft.app/local-ai-mac-apps

Limitations:
- Currently only covers the Mac App Store (since i need a reliable api to get data from)
- Data is collected on 6/24 so super new apps are not included. Planning on doing monthly updates
- If you see an app missing here, please let me know by submitting a nomination form

Methodology
- I scraped 20,435 apps from the app store api (513 search terms, plus crawling profiles of developers who build local AI Apps)
- Narrowed down to 2,259 apps that are actually local AI using deepseek v4 flash as classifier.
- Used a combination of scripts and LLM-as-a-judge for categorization and grading. The ranking rewards fully on-device apps. I've spot checked the big categories but for 2.3k apps there will be misses. If you find something incorrect, please call it out and I will fix it.
- see more here: https://bunnysoft.app/local-ai-mac-apps/how-we-rank

Here is the shameless plug: One of the apps on the site is built by me, you can't miss it if you visit the site 😂

Please let me know what you guys think about the future of local AI, apps, or the site 🙏

https://preview.redd.it/00o5xtaznf9h1.png?width=696&format=png&auto=webp&s=60a3306ea86a9b0d1f58c435b7dbb0a42761a415

Apple raised the prices across the product line this morning: https://www.reuters.com/world/asia-pacific/apple-raises-prices-macbooks-ipads-memory-costs-skyrocket-2026-06-25/

Beyond the base price, the cost of memory upgrade also doubled.

Some stores like bestbuy hasn't updated their prices yet, place your orders when you still can!

wondering what this means for the future of local AI？ 😢

Edit: bestbuy online prices has gone up a bit, costco still has the old prices

OpenAI rolled out ChatGPT Images 2.0 a few days ago and it's arguably the strongest image model on the market right now. After seeing some incredible results online, I decided to look into how best to leverage this model, starting with the simplest use case: creating portraits.

My findings? With a good prompt, you can create basically anything with this model.

Here is my abbreviated framework (Or you can find the complete guide here):

Don’t describe “a beautiful person.”
Describe a photo shoot.

A weak prompt usually looks like this:

“Make a realistic portrait of a beautiful model.”

The problem is that this leaves almost everything undecided: crop, lens, lighting, skin texture, styling, pose, setting, camera feel, and realism constraints.

The structure that works better for me is:

[Aspect ratio] photorealistic [crop] portrait of [adult subject], [portrait style].

Face:
[Face direction], expressive eyes, realistic slight asymmetry.

Skin and grooming:
[Skin style], natural texture, subtle pores, polished but not over-retouched.

Hair:
[Hair direction], realistic strands and natural flyaways.

Wardrobe:
[Wardrobe style], realistic fabric texture and natural drape.

Pose and expression:
[Pose], relaxed body language, natural hands.

Setting:
[Location], background details, foreground details if needed.

Photography:
[Camera feel], [lens], [lighting], [depth of field], [color grade], [texture].

Avoid:
Plastic skin, over-smoothed face, exaggerated anatomy, distorted hands, extra fingers, watermark, random text.

Example:

4:5 vertical photorealistic waist-up portrait of an adult model in her late 20s, soft natural beauty aesthetic.

Face:
Balanced facial proportions, expressive eyes, realistic slight asymmetry.

Skin and grooming:
Natural dewy skin texture, subtle pores, tiny imperfections, polished but not over-retouched.

Hair:
Soft loose waves with natural flyaways and realistic individual strands.

Wardrobe:
Oversized ivory cotton shirt, tailored neutral trousers, realistic fabric drape.

Pose:
Relaxed standing pose near a window, calm direct eye contact, subtle closed-mouth smile.

Setting:
Minimal bright apartment studio with white curtains and a pale textured wall.

Photography:
85mm portrait lens, soft diffused daylight from the left, shallow depth of field, pastel neutral color grade, subtle film grain.

Avoid:
Plastic skin, distorted hands, exaggerated anatomy, watermark, random text.

The main thing I’ve noticed: realism comes less from asking for “flawless” and more from asking for physical evidence — pores, flyaways, fabric wrinkles, catchlights, shadows, lens behavior, and slight asymmetry.

I’m turning this into a small visual guide + prompt builder called PromptPaper. I’m the maker, so disclosure: this is my project. The free guide/tool is here if you want to try it: https://www.trypromptpaper.com/portraits

Portraits are just the start. I am planning on doing more deep dives into more image generation use cases. Is the prompting guide helpful to you? What kind of content would you like to see? I am going to base off my next project on community feedback. Any suggestions are welcome!