None of this was us. Day 1 (and the first 48 hours) belonged to the open-source community: Generate with it @ComfyUI — native support + official quantized builds, Day 0 Diffusers — the reference Python pipeline, Day 0 @deepbeepmeep — WanGP v12.41, the 5-6 GB ultra-low VRAM path, Day 1 @pipenetwork — Phosphene + MiniMax-H3-MLX (one-click Mac app + MLX engine), Day 1 @blizaine — Maestro v1.5.5 (one-click GUI + prompt enhancer), Day 2 @ModelScope2022 — DiffSynth-Studio NF4, drops floor to 7-8 GB, Day 2 Serve it @sgl_project — SGLang Diffusion, official cookbook (2×5090 / RTX 6000), Day 0 @vllm_project — vLLM-Omni, OpenAI-compatible video endpoint, Day 0 Train it @ostrisai — AI Toolkit, first trainer (T2V + I2V) 14 h after release, Day 1 @ModelScope2022 — DiffSynth-Studio training scripts (NF4 low-memory), Day 2 @kohya_tech — Musubi Tuner, third trainer (48 GB → shrinking), Day 2 the first community LoRAs running on pruned INT8, Day 2 Speed it up @nvidia SANA team — Sol Engine, 3.95× end-to-end, no quality trade-off, Day 1 sol-attn · sage-attn · EasyCache — 20-35 % each on consumer cards (and they stack), Day 1 Spectrum acceleration — ~34 % Euler sampling time in ComfyUI, Day 2 @AMD — Day 0 support on Instinct MI300X / MI355X (ROCm + SGLang) Extend what it can do Multishot workflow — chains past the 15 s limit up to 30 s with audio, Day 2 Or just run it without installing @MiniMax_AI offical API @fal · @OpenRouter · official API — hosted from launch, $0.13/s for 2K, Day 0 @wavespeed_ai · @runpod — $0.07-0.15 per clip on rented 5090s, Day 2 And everyone who benchmarked, quantized (rockerBOO NVFP4, joeygambino GGUF…), and shared numbers: @umiyuki_ai @luta_ai @onigirikila @ivanfioravanti @Spectromachina and many more 🤗 This is what open weights are for.