Tested on M1 Max: Floyd-Steinberg halftone + BLE pacing + a vendor-specific density command `1D 49 F0 nn` to print sharp photos on the Sugar YMP-01 thermal mini printer from Python.
Tested on M1 Max: switching a Python BLE client to RFCOMM (SPP Ch.2) cuts transfer from ~60s to 5.38s for a 140KB JPEG. Covers PyObjC quirks, macOS Bluetooth entitlement, and an isolation experiment confirming olie.xdev's 'possibly not required' steps.
Tested Klein 9B + 9B NSFW LoRA on M1 Max 64GB via mflux 0.17.5: 1m51s/512, 5m37s/1024 q4, 224/224 LoRA keys match, NSFW prompts uncensored, Japanese subjects work with helper tokens.
Investigated whether NSFW LoRAs for FLUX.2 Klein 9B can run on M1 Max 64GB. Covers model compatibility, LoRA application paths, RunPod verification strategy, and VRAM requirements for training your own LoRA with ai-toolkit.
Three local image generation engines (WAI-Anima, WAI-IL/SDXL, FLUX.2 Klein 4B) tied together by a thin FastAPI wrapper that takes Japanese prompts. Ollama (gemma3:12b) handles JP→EN, ComfyUI workflows are built on the fly in Python, FLUX.2 runs as an mflux subprocess, and the whole thing is reachable from an iPhone over Tailscale.
Hands-on benchmark of FLUX.2 Klein 4B on M1 Max 64GB using mflux (MLX) and iris.c (pure C + Metal). A counter to Pruna AI's H100-only tutorial — measuring how fast Apple Silicon actually gets there.
Set up the CLI version of NDLOCR-Lite on Apple Silicon Mac, then tested OCR result correction with Qwen 3.5 and Swallow. Includes experiments with direct image reading and the anchoring effect.
Went 0-for-13 trying to train an Illustrious-XL LoRA on a Mac Studio M1 Max 64GB. With help from multiple AI agents, pinpointed the root causes and finally succeeded on a RunPod RTX 4090. The full record: three fatal parameters and the sd-scripts trap.
A look at ACE-Step, the 'Stable Diffusion of music,' covering its architecture, features, installation, and expected performance on Apple Silicon before trying it on an M1 Max.
Overview of Black Forest Labs' FLUX.2 Klein 9B model and how it performs on M1/M2/M3/M4 Macs. Covers the key factors behind the CUDA vs MPS performance gap, including memory bandwidth and FP8 quantization.
A plan to build an internal help desk RAG system using a Mac mini M4 Pro and Dify. Highlights what's new in Dify circa 2025 and tips for running local LLMs.