This Wan 2.2 ComfyUI guide is for running Wan 2.2 video workflows on Runpod. WAN 2.2 is an open-source AI video generation model developed by Alibaba that supports text-to-video and image-to-video generation on consumer GPUs. It's the second generation of the WAN series, and one of the most capable open video models available today. This guide walks you through running WAN 2.2 on Runpod's GPU cloud using ComfyUI. No local environment setup, no driver headaches, no expensive hardware required. By the end, you'll have generated your first AI video from a text prompt or image.
What is WAN 2.2? WAN 2.2 is Alibaba's second-generation open-source AI video model, building directly on WAN 2.1's foundation. Where WAN 2.1 proved that open-source video generation was viable, WAN 2.2 makes it practical, with sharper temporal consistency, better motion quality, and improved image-to-video fidelity. The model uses a Mixture-of-Experts (MoE) architecture with two 14B parameter experts that activate selectively based on the signal-to-noise ratio during generation, delivering 14B-level output without running the full compute of both experts simultaneously. The model comes in several variants: T2V (text-to-video): Generate video clips from a text description; I2V (image-to-video): Animate a starting image into a moving scene; I2V-A14B: The 14B parameter image-to-video variant, optimized for high-fidelity output; TI2V-5B: A 5B hybrid model supporting both text and image input at 720p, runnable on a single RTX 4090. Like its predecessor, WAN 2.2 is compatible with ComfyUI workflows and runs on consumer-grade hardware. The lightweight TI2V-5B variant requires around 8 GB of VRAM. The 14B models deliver substantially better results but need 24 GB or more.
What is ComfyUI? ComfyUI is an open-source, node-based interface for building generative AI pipelines. Instead of writing code, you connect visual nodes, each representing a model, process, or output, into a workflow graph. It's the tool of choice for power users who want granular control over their generation pipeline without giving up accessibility. For running WAN 2.2, ComfyUI handles loading the model checkpoints, conditioning on your text or image input, running the diffusion sampler, and stitching frames into a video, all wired up in a pre-built workflow you don't need to configure from scratch.
Running a 14B video diffusion model locally means either owning a high-end GPU or waiting a very long time per generation. Runpod removes that constraint. With Runpod's GPU cloud, you select the GPU you need, deploy a pre-configured environment in seconds, and pay only for the time you use. There are no idle costs, no hardware to maintain, and no ceiling on the GPU tier you can access, from RTX 3080s for quick tests to A100s for high-res production runs. Runpod also offers public serverless endpoints for WAN 2.2 models you can use immediately without any setup: WAN 2.2 I2V 720p - Image-to-video generation at 720p resolution. Upload a reference image, add a prompt, and get a high-quality animated clip. WAN 2.2 T2V 720p LoRA - Text-to-video at 720p with LoRA support for fine-tuned style control. Useful if you want to steer generation toward a specific visual style or trained subject.
If you want full control over your workflow settings, step count, resolution, and frame count, the ComfyUI template approach below gives you that. The endpoints are the fastest way to generate a clip right now.
Wan 2.2 ComfyUI workflow on Runpod
The safest review path is to start from ComfyUI's official Wan2.2 native workflow examples, then run the workflow on a Runpod Pod with enough VRAM for the selected model variant.
GPU requirements for WAN 2.2
Choose your GPU based on which model variant you want to run and your target resolution:
- 8 GB VRAM (RTX 3070, RTX 3060 12GB): TI2V-5B only, 480p
- 16-24 GB VRAM (RTX 3090, RTX 4080): 14B models at 480p
- 24 GB VRAM (RTX 4090, A5000): 14B models at 480p, TI2V-5B at 720p
- 40-80 GB VRAM (A100, H100): 14B models at 720p, batched generation, production workloads
Templates for running WAN 2.2 on Runpod
These community templates are purpose-built for WAN workloads and get you into ComfyUI without any manual setup.
- One Click ComfyUI - Wan 2.1 / Wan 2.2 (CUDA 12.8) by HearmemanAI
- ComfyUI (Official Runpod template)
- WAN 2.2 AI Influencer by aiorbust
Step-by-step: Run WAN 2.2 on Runpod
Step 1: Sign up for Runpod. Go to runpod.io and create a free account. Once you're in, add credits or a payment method so you can deploy a GPU pod.
Step 2: Deploy a template. Head to the Pods section in the left-hand nav. This is where you select your GPU and configure your environment. Select a GPU. For most WAN 2.2 use cases, the RTX 4090 (24 GB VRAM) is the recommended starting point. It handles the 14B model at 480p comfortably and the TI2V-5B at 720p, with generation times that stay practical for iteration. If you're targeting 720p with the 14B model or running batch jobs, step up to an A100. Choose your template. Once you've selected a GPU, scroll down to the Template section and click Change Template. Search for or select one of the WAN 2.2 templates listed above. The HearmemanAI template is the best starting point for most users, covering the most workflow types and handling model downloads automatically. Configure environment variables. Before deploying the HearmemanAI template, set your environment variables to specify which models to download. At minimum, set download_480p_native_models to get the 1.3B T2V and 14B T2V/I2V 480p models. For 720p output, set download_720p_native_models instead. Set your disk size to at least 20 GB, then click Deploy. Initial setup takes 5-20 minutes depending on which models you've selected.
Step 3: Open ComfyUI. Once the pod shows a running state, click Connect, then select Open port 8188. This opens the ComfyUI interface in a new browser tab. If you're using the official Runpod ComfyUI template, wait until you see [ComfyUI-Manager] All startup tasks have been completed. in the pod logs before opening port 8188. You'll see a node graph canvas with the pre-built WAN 2.2 workflow already connected: model loader, text or image conditioning, sampler, VAE decoder, and video output. You don't need to wire anything yourself.
Step 4: Generate your first video. Enter a prompt in the text conditioning node (often labeled CLIP Text Encode). Example prompt: “A slow aerial shot over a misty mountain range at dawn, soft golden light breaking through the clouds.” Check your settings: Frames: 16-24, Resolution: 480x856, Steps: 20-30. Queue the prompt. ComfyUI will begin executing the graph. On a 4090, a 24-frame 480p generation takes roughly 1-2 minutes. For a full 5-second clip (81 frames) at 480p, expect around 4 minutes without quantization. Retrieve your output when complete; the video will appear in ComfyUI or be saved to /workspace/ComfyUI/output. Download files via the FileBrowser on port 8080 (login details may vary by template) or through Runpod file manager.
Step 5: Try image-to-video (I2V). WAN 2.2's I2V capability is strong. Switch to the I2V workflow tab in ComfyUI and upload a reference image via the image loader node. This anchors the first frame, and the model animates it forward based on your prompt. The I2V-A14B variant produces noticeably better results for character animation and fine detail. Use the WAN 2.2 I2V 720p endpoint on Runpod to run image-to-video directly without a ComfyUI setup.
Using LoRAs with WAN 2.2. WAN 2.2 supports LoRA fine-tuned weights to steer generation toward specific visual styles or trained subjects. The HearmemanAI template supports Civicomfy/CivitAI LoRA downloads via environment variable before deployment. LoRA weights appear as nodes in the ComfyUI workflow and can be applied at varying strengths. Runpod's WAN 2.2 T2V 720p LoRA endpoint also lets you test LoRA-guided text-to-video generation at 720p directly, without building a local workflow.
Pro tips. Reduce frames first, then scale up. If you hit memory limits or long generation times, drop to 16 frames before reducing resolution. Use frame interpolation to smooth output. Many WAN 2.2 templates include a frame interpolation workflow. Saving your workflows is recommended. When you dial in settings you like, export the workflow JSON from ComfyUI's menu. Attach a network volume if you're working regularly to keep outputs and custom workflows persistent. Stop your pod when you're done to avoid ongoing charges.
Wrapping up
WAN 2.2 is one of the most capable open-source AI video generation models available today, and Runpod is the fastest path to running it, whether through a serverless endpoint for quick generation or a full ComfyUI template for production workflows. The templates handle everything from model loading to workflow configuration, so you're generating video within minutes of deploying a pod. Ready to try it? Start with the WAN 2.2 I2V endpoint for an instant result, or deploy a ComfyUI template for full workflow control.
FAQ
- What hardware do I need to run WAN 2.2 on Runpod? The TI2V-5B model runs on 8 GB VRAM. For the 14B models at 480p, you need 16-24 GB. For 720p output with the 14B model, 40-80 GB is recommended. The RTX 4090 is the starting point for most users. On Runpod you can rent exactly the GPU you need, when you need it, with no long-term commitment.
- Can I run WAN 2.2 locally instead? If you have a 24 GB GPU, yes. But running locally means managing your own Python environment, ComfyUI installation, model downloads, and dependency conflicts. The Runpod templates handle all of that automatically, making the cloud the faster starting point for most users.
- What is WAN 2.2 animate? WAN 2.2 Animate (Wan2.2-Animate-14B) is a model variant released by Alibaba in September 2025, designed specifically for character animation and replacement. It replicates holistic movement and facial expressions from a reference video or image, making it well-suited for animating portraits, character art, and illustrations with realistic motion.
- What is WAN 2.2 LoRA? LoRA weights for WAN 2.2 are fine-tuned model additions that steer video generation toward specific styles or subjects. The Runpod templates include LoRA workflows and endpoints for testing LoRA-guided generation.
- Can I use WAN 2.2 as an API instead of a UI? Yes. Runpod's serverless GPU endpoints let you deploy any model as a REST API that autoscales in the cloud. You can containerize a ComfyUI workflow and deploy it to Runpod Serverless.
