Three LLMs converted the same 10 Japanese scene briefs into Anima (Qwen-DiT) prompts, generated as 60 fixed-seed images on an M1 Max with a merged 3-character LoRA. The Qwen-to-Qwen affinity hypothesis did not survive; a strict formatter brief with character-count locks is what actually moved the results, and two failure modes survive any prompt.
Tested on an M1 Max, NumPy only: Qwen maps a prompt to a JSON of knobs, and a 2D Kuramoto oscillator field renders it. No objects, but composition, color, and motion change with the prompt.
Un-0 swaps neural-net weighted sums for Kuramoto coupled-oscillator physics, hitting FID 6.74 on ImageNet-64. Still GPU-simulated, and the 1000x energy claim is unproven — no chip yet.
Fujitsu's PHOTON claims up to 475x over Transformers, but that's tokens/s/GiB (multi-query memory throughput), not faster single responses. What the 1.2B paper tables, the quality drop, and 9-query integration really show.
Merged kei, kana, and koharu into a single Anima (Qwen-DiT) LoRA and ran my first training on Blackwell (RTX 5090, sm_120). Hands-on log: the cu128 / torch2.8 / SDPA stack swap from the 4090, why the weakest character gets absorbed (caption asymmetry, not rank), and how trigger-only prompts separate three close-packed characters at ep143 without ControlNet.
Tested local Wan video gen on a Radeon 8060S (Strix Halo, 48GB UMA, Windows). ZLUDA can't run stock PyTorch; AMD's TheRock gfx1151 wheel gives native ROCm. FastWan 1.3B in 4min, Wan 14B I2V in 13.6min — VAE decode and 16GB-RAM Segfaults are the real limits.
Tested FramePack F1 on an RTX 4060 Laptop (8GB VRAM, 32GB RAM): VRAM peaked at 5.75GB, but the 26GB model overflowed RAM into the pagefile and a 5s clip took 56 min. The real bottleneck for local video gen on a laptop is RAM, not VRAM.
Tested Krea 2 Raw and Turbo on M1 Max 64GB ComfyUI. Turbo bf16 runs ~3.5 min/image, fp8 is rejected on MPS, and Raw's 52-step+CFG NaNs to a black image after 47 min. Plus quality, NSFW behavior, and license.
Sakana Fugu trains no base model: a learned conductor routes GPT-5.5/Claude/Gemini. How it compares to PLaMo (scratch, closed) and LLM-jp (fully open), how it differs from OpenRouter, and its biggest risk.
Tested Boogu-Image-0.1 on an M1 Max 64GB ComfyUI: the fp8 build is rejected by MPS, so bf16 is mandatory, and Turbo runs ~70s per 1024px image. Notes on photoreal vs anime, bilingual text, and where NSFW stops.
After a US order pulled Claude Fable 5, which Chinese models drop into Claude Code? Kimi K2.7 Code, Qwen3.7 Max, DeepSeek V4 and GLM-5.1 — constraints, VRAM, benchmark caveats.
AWS WAF can now return 402 to AI bots and collect x402 USDC. For a small Vercel blog the math is rough: ~15,000 paid requests just to clear the $15/mo WAF + Bot Control floor.
