Tested WAI-Anima v1, Anima preview3-base, and WAI-Illustrious v160 side by side on M1 Max 64GB ComfyUI with same seed/prompt. WAI-Anima inherits Anima's atmospheric lighting and natural running poses but still loses to WAI-Illustrious on tag control and character consistency. Includes i2i pipeline test (denoise 0.5), ~275s generation times, and how the Anima derivative ecosystem (WAI-Anima, CottonAnima, Kirazuri, RDBT) expanded in two months.
Based on EE Times' interview with AMD AI Software VP Anush Elangovan, we assess the ROCm vs CUDA ecosystem gap. Includes hands-on experience with ROCm breaking four times on Strix Halo, plus practical guidance on choosing between NVIDIA, AMD, and Apple Silicon.
Tested 5 approaches including Qwen Image Edit, JS color reduction, and Illustrious i2i + LoRA. Illustrious i2i alone turned out to be the fastest and lightest solution for pixel art conversion.
I tested local Vision LLMs (Gemma 3, Qwen2.5-VL, Llama 3.2 Vision, Gemma 4) to see if they could look at character illustrations and pixel art and generate RPG-style stats in JSON format.
SwiftLM, an Apple Silicon–only MLX inference server, provides a native Metal implementation of TurboQuant V2+V3 hybrid KV‑cache compression and NVMe SSD expert streaming.
Ollama 0.19 switches the Apple Silicon backend to MLX, achieving 1,810 tokens/s prefill and 112 tokens/s decode. NVFP4 quantization support and cache improvements landed at the same time.
An update switched Qwen Image Edit inference from FP16 to BF16, and M1-M3 Macs emulate BF16 at half speed. Benchmarks of the 80s to 10min regression, why --force-fp16 gives black images, and the --fp16-vae --fp16-unet config that lands at 2:30.
Hypura breaks away from llama.cpp’s mmap design and streams even dense models with a three-tier NVMe placement, while TurboQuant eliminates quantization-constant overhead via a polar-coordinate transform. Includes a design comparison with Flash‑MoE and a review of scenarios where KV‑cache compression actually helps.
Local video generation test on M1 Max 64GB MacBook Pro. FP8 models don't work on Metal — switching to GGUF got Wan 2.2 running at 82 minutes for a 2-second clip. LTX-2 produced NaN or unusable KSampler output under MPS. Specs, failed configs, and the working setup.
Upscaling images loaded via the Load Image node was producing garbled output. Fixed it by addressing the non-contiguous tensor issue — a one-line patch to comfy/utils.py. Added a 2026-04-29 follow-up after a ComfyUI update wiped the patch and the bug came back, with the upstream PyTorch issue and a recurrence-detection snippet.
