Wan 2.7 Blog

Apple rebranded its assistant as Siri AI at WWDC 2026. Here is what it does differently — conversational experience, onscreen awareness, personal context, App Intents, release date, compatible devices, and how it compares to ChatGPT and Gemini.

Wan 2.2 Remix v3 workflow guide with practical tips. Learn how Remix differs from I2V and T2V, which NSFW checkpoint to download (5B vs 14B), what safetensors naming conventions mean, and the prompt adjustments that actually improve Remix output — based on 300+ test generations.

What is Nemotron 3 Ultra? A complete guide to NVIDIA's 550B-parameter Mixture-of-Experts model with 55B active parameters. Specs, architecture (Hybrid Mamba-Transformer, LatentMoE, NVFP4, multi-token prediction), benchmark claims, access methods, and when to use it for agentic reasoning, coding, and enterprise orchestration.

How to train Wan 2.2 LoRAs for character consistency in I2V and T2V workflows. Covers T2V vs I2V LoRA differences, AI Toolkit training settings for 12GB VRAM, face drift causes and fixes, and when to train a LoRA instead of relying on prompts or reference images.

A complete breakdown of Wan 2.7 credit costs per generation type — text-to-video, image-to-video, 9-grid, reference-to-video, and editing. Learn how credits work, what each mode costs, and how to minimize your spend.

Discover 15 practical Wan 2.7 tips and lesser-known features — from prompt expansion tricks and seed locking to ComfyUI optimization, credit-saving workflows, and multi-reference techniques that experienced users rely on.