Best Wan 2.2 LoRAs (2026): Speed, Motion, Camera and Style LoRAs for ComfyUI

Wan 2.2 is still the most popular open video model for ComfyUI, and most of its power comes from LoRAs: small add-on files that make it faster, fix its motion, move the camera in a precise way or give it a new look. The problem is that Wan 2.2 14B has two experts (high noise and low noise), most LoRAs come in pairs, many were trained for Wan 2.1, and the Hugging Face and Civitai lists are full of junk. This guide is my curated list of the best Wan 2.2 LoRAs in November 2026, grouped by job (speed, motion, camera, style, consistency), with the exact file names, which expert each file goes on, strengths, trigger words and where every file goes in ComfyUI.

How LoRAs Work on Wan 2.2 (High and Low Noise)

Wan 2.2 A14B is really two 14B models that take turns. The high-noise expert runs the first part of sampling and decides the layout, motion and camera path. The low-noise expert runs the second part and adds texture, faces and fine detail. Only one is in VRAM at a time, which is how a 14B video model fits on 16 GB.

That split matters for LoRAs:

• A LoRA that changes motion or camera mostly needs the high-noise file. Several of the best camera and transition LoRAs below only ship a high-noise file, and their authors say so.
• A LoRA that changes look or detail needs the low-noise file, and usually both.
• When a LoRA ships as a pair, always load both files, each on its own expert. Putting the high file on the low model (or loading only one of a pair) is the number one reason a LoRA “does nothing”.
• I2V and T2V LoRAs are different. The I2V and T2V experts have different weights, so an I2V LoRA on a T2V model often gives noise or no effect. Each entry below says which one it is for.

The 5B TI2V model is a single model, and it does not use these 14B LoRAs at all. If you have not set Wan 2.2 up yet, start with my Wan 2.2 ComfyUI setup for 8-16 GB, which covers the GGUF experts, text encoder and VAE.

Where Wan 2.2 LoRAs Go and How to Load Them

1. Download the .safetensors files and put them in ComfyUI/models/loras/. A subfolder such as ComfyUI/models/loras/wan22/ keeps things tidy; ComfyUI shows it as wan22/filename in the list.
2. Press R in ComfyUI (or restart) so the new files appear.
3. In your Wan 2.2 workflow, find the two model loaders (Load Diffusion Model or Unet Loader (GGUF)). After each one, add a LoraLoaderModelOnly node.
4. Pick the _high file on the high-noise branch and the _low file on the low-noise branch. Set strength.
5. Connect each LoRA output to the next LoRA (for stacks) and finally to ModelSamplingSD3 or the KSampler (Advanced) for that expert.

With more than two LoRAs per expert, use Power Lora Loader (rgthree) from rgthree-comfy: one node per expert with an on/off toggle and strength for each LoRA. It makes A/B testing much faster. I cover it and other useful packs in my must-have ComfyUI custom nodes list.

LoRAs work the same with GGUF experts. Loading a LoRA adds a little VRAM (roughly its file size during patching), so on 16 GB cards keep big stacks to 2-3 LoRAs per expert.

Quick List: Best Wan 2.2 LoRAs

Best Speed LoRAs (4-Step and 2-Step)

1. LightX2V Wan2.2 Distill LoRAs: the standard

Repo: lightx2v/Wan2.2-Distill-Loras (the most-liked Wan 2.2 adapter on Hugging Face, over 90,000 downloads).

Settings: strength 1.0 on both, 4 steps total (2 on the high expert, 2 on the low expert in the usual ComfyUI template), CFG 1.0, sampler euler or lcm with the simple scheduler. At CFG 1 the negative prompt is mostly ignored, which is normal. The repo also includes a ready workflow, wan2.2_i2v_scale_fp8_comfyui_with_lora.json.

The official ComfyUI templates use Comfy-Org’s renamed copies of earlier versions (wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors and the T2V v1.1 files). They work, but the dated 1022 and 1217 releases are newer.

2. Wan2.2-Lightning (Seko): the older alternative

Repo: lightx2v/Wan2.2-Lightning. This is LightX2V’s earlier family, sorted in folders such as Wan2.2-T2V-A14B-4steps-lora-rank64-Seko-V2.0, ...Seko-V1.1, Wan2.2-I2V-A14B-4steps-lora-rank64-Seko-V1 and a 250928-dyno T2V build. Some people prefer the look of Seko V2.0 for T2V, so keep it in mind if the 1217 files feel too smooth. Apache 2.0.

3. LightX2V 2-Step (I2V): fastest previews

Repo: rzgar/Wan2.2_I2V_LightX2V_2Step. Files Wan2.2_I2V_LightX2V_2step_high_noise.safetensors and Wan2.2_I2V_LightX2V_2step_low_noise.safetensors, strength 1.0, 2 steps on each expert. The author recommends dpmpp_2m_sde, dpmpp_2m_sde_heun or sa_solver_pece with the sgm_uniform scheduler; euler/simple works but fails more often. In the author’s test at 512×848 a clip took about 37 seconds versus about 89 seconds with a 4+4 LightX2V setup, with 6 of 9 test clips clean. Use it to hunt seeds and test prompts, then render the keeper with the 4-step pair.

Best Motion Fix and Quality LoRAs

4. LightX2V Slow-Mo Fix (I2V)

Repo: rzgar/Wan2.2_I2V_LightX2V_Slow-Mo_Fix (Apache 2.0). The 4-step speed LoRAs have a known side effect on I2V: everything moves as if in slow motion. This pair, wan2.2_i2v_lightx2v_motion_fix_high.safetensors and wan2.2_i2v_lightx2v_motion_fix_low.safetensors, is a reworked 4-step pair aimed at natural speed. Use it instead of the normal I2V speed pair, at 1.0 and 4 steps. The newest upload is a 4-step build in the folder Wan_2_2_I2V_lightx2v_Distill_260412_rank_128_fp16, extracted from LightX2V’s distilled models.

5. Wan 2.2 Fun Reward LoRAs (HPS2.1 and MPS)

Repo: alibaba-pai/Wan2.2-Fun-Reward-LoRAs. Alibaba PAI trained these with reward models (HPS v2.1 and MPS) to push results toward what people rate as more attractive and closer to the prompt. Files (858 MB each): Wan2.2-Fun-A14B-InP-high-noise-HPS2.1.safetensors, ...-low-noise-HPS2.1.safetensors, and the same two with MPS. They are trained for the Wan 2.2 Fun A14B InP (inpaint / first-last frame) models. On the standard I2V model, test them at 0.5 first; use one reward type at a time.

Best Camera LoRAs

Wan follows camera words in prompts reasonably well, but a camera LoRA makes a move reliable. For full control of the path, also look at the Fun Camera model in my Wan 2.2 setup guide.

6. Orbit Shot (ostris, I2V)

Repo: ostris/wan22_i2v_14b_orbit_shot_lora, Apache 2.0, trained with Ostris AI Toolkit. Trigger: orbit 360 (the example prompt also uses “orbit 180 around an astronaut on the moon”, so both phrasings work as a camera instruction). Great for product shots, characters and landscapes. Grab the file names from the repo’s Files tab and start at 1.0.

7. 360 Rotation (artificialguybr, I2V)

Repo: artificialguybr/360Rotation-Redmond-WAN2-I2V-14B, CC0. Files [WAN2.2]360Rotation_Redmond_high_noise.safetensors and [WAN2.2]360Rotation_Redmond_low_noise.safetensors. Trigger 360 Rotation, strength 0.8-1.0. Turns a still into a turntable spin, perfect for product pages and character sheets.

8. FollowCam (artificialguybr, T2V)

Repo: artificialguybr/FollowCam-Redmond-WAN2-T2V-14B, CC0. File [WAN2.2]Followcam_Redmond_high_noise.safetensors (high-noise only). Start prompts with FollowCam and describe a continuous tracking shot: “FollowCam, the camera follows a cyclist through narrow old-town streets at sunrise”. Strength 0.8-1.0.

The same creator has more T2V camera and lens LoRAs worth trying: FishEye, AxialView, WindowSeat (view from a moving vehicle) and SplitScreen, all under artificialguybr/...-Redmond-WAN2-T2V-14B.

9. Reshoot-Anything (Morphic, advanced)

Repo: morphic/reshoot-anything, Apache 2.0. Give it a finished video and a new camera path and it re-films the same scene from the new angle. It is a pair of very large rank-512 LoRAs (about 9.8 GB each) for the I2V model, and the official usage is Morphic’s own generate.py script, not a ComfyUI workflow. It is here because it is the most powerful camera LoRA for Wan 2.2, but it is for people comfortable with Python and a 24 GB+ GPU.

Best Style LoRAs

• Technically Color (renderartist/technically-color-wan): the rich, saturated look of classic three-strip film. Trigger t3chnic4lly, high and low files. The v1 was trained on 100 stills, so the author says it is best for Wan-as-image-generator and may be weak for video. CreativeML OpenRAIL-M.
• Vintage Cinematic (artificialguybr/Vintage-Cinematic-Redmond-Wan22): old-film colour and grain for T2V.
• 1980s Horror Movies and 1950s Sci-Fi (neph1/1980s_horror_movies_wan2.2, neph1/1950s_scifi_wan2.2_t2v), plus neph1/80s_fantasy_movies_wan_2.2: era looks for T2V. Great for retro trailers.
• Yarnwoven, Spectramatic, Microverse and Metalcification (artificialguybr): knitted-yarn, prism-light, tiny-world and liquid-metal effects. Metalcification is I2V, the others T2V.

Style LoRAs on Wan are strongest on the low-noise expert. If a style overpowers motion, lower only the high-noise strength (for example 0.4 high, 0.9 low).

Best Effect, Editing and Transition LoRAs

• Kinestasis concept (Cseti/wan2.2-14B-Kinestasis_concept-lora-v1, T2V): a sequence of fast scene transitions while the subject stays still (instruments dissolving into sound waves, masks peeling away). High-noise only, strength 0.8-1.0. It is very sensitive to prompt structure; use the author’s phrases Banostasis concept, Sequence of quick scene transitions of and The sequence of changes includes the transitions.
• Cinematic Quick Cuts (neph1/cinematic_quick_cuts_wan, I2V, also tested on T2V): packs a whole mini-scene into one clip with cuts. Write the prompt as a series of bracketed shots: “[wide-angle shot of …] [close-up shot of …] [extreme close-up shot of …]”. Only the high-noise stage needs it; the author notes the full 81 frames can weaken the effect.
• Frames-to-Video interpolation (morphic/Wan2.2-frames-to-video, I2V, Apache 2.0): lora_interpolation_high_noise_final.safetensors generates a transition between a start and an end image, or through several key frames at chosen timestamps. Official usage is Morphic’s script; in ComfyUI people pair it with a first-last-frame workflow, which is unofficial.
• Attack Sprite Animation (Teluv/Wan_Video_Attack_Sprite_Animation, I2V, Apache 2.0): side-view character attack animations for 2D games, used together with the LightX2V 4-step pair. The author labels it experimental.
• Kung Fu (starsfriday/Wan2.2-I2V-KungFu) and Fly (joyfox/Wan2.2-I2V-Fly): fun action LoRAs that make a still subject fight or take off.
• Explosion (artificialguybr/Explosion-Redmond-WAN2-I2V-14B): adds an explosion effect to an I2V shot.

Product and Character Consistency LoRAs

• Cloth Consistency (drnighthan/ClothConsistency-Wan2.2-I2V-ConsistencyLoRA2): start from a product photo of a garment on white, and it generates a model wearing that exact garment. Begin the prompt with clothing consistency. and name the garment (coat, skirt, shirt, jacket, dress or pants). Author’s strengths: high 0.7, low 0.9, and the low-noise lightning LoRA at 1.0.
• Car Consistency (drnighthan/CarConsistency-Wan2.2-I2V-ConsistencyLoRA1): the same idea for car product shots.
• Animate Relight (wan2.2_animate_14B_relight_lora_bf16.safetensors in Comfy-Org/Wan-2.2): for Wan Animate character replacement, matches the new character’s lighting to the scene.

For long, multi-shot character work, Wan is no longer the best tool. MiniMax H3’s reference-to-video does it natively; see my best MiniMax H3 LoRAs and H3 reference-to-video workflow.

How to Stack Wan 2.2 LoRAs

1. Speed LoRA first (LightX2V 4-step or Slow-Mo Fix), at 1.0 on both experts.
2. Motion or camera LoRA next (Orbit, 360 Rotation, FollowCam), 0.8-1.0, mainly on the high expert.
3. Style LoRA last, 0.6-1.0, mainly on the low expert.
4. Limit: two or three LoRAs per expert. Beyond that, effects fight each other and you get flicker or mush.
5. Change one thing at a time with a fixed seed. rgthree’s Power Lora Loader toggles make this quick.

Example I2V stack for a product spin on 16 GB: high expert = Slow-Mo Fix high (1.0) + 360 Rotation high (0.9); low expert = Slow-Mo Fix low (1.0) + 360 Rotation low (0.9); 4 steps, CFG 1, 832×480, 81 frames. Then upscale and interpolate with my RIFE + SeedVR2 workflow (it works on any video, not only H3).

Do Wan 2.1 LoRAs Work on Wan 2.2?

Partly. Wan 2.2’s experts were trained from Wan 2.1, so many 2.1 LoRAs load without errors. In practice:

• They usually work best on the low-noise expert (style, faces, detail).
• On the high-noise expert they are hit and miss; motion LoRAs from 2.1 often do little.
• Wan 2.1 speed LoRAs (CausVid, the original LightX2V T2V 14B) are replaced by the Wan 2.2 pairs above. Do not mix generations.
• Merged 2.1 checkpoints such as FusionX are built on Wan 2.1 14B, not 2.2.

If a LoRA page lists the base model as Wan-AI/Wan2.2-I2V-A14B or Wan2.2-T2V-A14B, it was trained for 2.2. Prefer those.

How to Find Good Wan 2.2 LoRAs (and Avoid Bad Ones)

• Hugging Face: open the base model page (Wan-AI/Wan2.2-I2V-A14B or Wan-AI/Wan2.2-T2V-A14B) and click “Adapters” in the model tree. Sort by likes.
• Civitai: filter Base Model by “Wan Video 2.2 I2V-A14B” or “T2V-A14B” and type LoRA. Check that both high and low files are included when the author says it is a pair.
• Read the card. Good LoRAs list trigger words, strength, which expert and example videos. If a card has none of that, skip it.
• Licence: CC0, Apache 2.0 and MIT are the safest for commercial work.
• Skip real-person LoRAs. Several popular uploads are trained on celebrities. Using a real person’s likeness without consent is a legal and ethical problem, and many platforms ban it.

Troubleshooting

• LoRA has no effect: wrong expert (high file on low model), only one file of a pair loaded, missing trigger word, or an I2V LoRA on a T2V model.
• “lora key not loaded” warnings in the console: the LoRA was made for a different model (often Wan 2.1 or the 5B). A few warnings are harmless; hundreds mean it does not fit this model.
• Slow-motion movement: switch to the Slow-Mo Fix pair or try the T2V 1217 / I2V 1022 files.
• Burned or over-saturated colours: CFG above 1 with a speed LoRA. Set CFG 1.0.
• Flicker or melting after adding a style LoRA: lower the high-noise strength of that LoRA to 0.3-0.5.
• Out of memory after adding LoRAs: use fewer LoRAs, a smaller GGUF expert, or launch with --reserve-vram 1 (see ComfyUI launch flags). Other errors: ComfyUI errors and fixes.

Frequently Asked Questions

What is the best Wan 2.2 LoRA?

The LightX2V 4-step distill LoRAs (I2V 1022 and T2V 1217) are the most useful because they cut a clip from about 20-40 steps to 4. After that, the best LoRA depends on the job: Slow-Mo Fix for natural I2V motion, Orbit Shot or 360 Rotation for camera moves, and style LoRAs such as Technically Color for looks.

Where do I put Wan 2.2 LoRAs in ComfyUI?

In ComfyUI/models/loras/. Load them with LoraLoaderModelOnly or Power Lora Loader after each Wan 2.2 model loader, with the high file on the high-noise model and the low file on the low-noise model.

Do I need both high and low noise LoRA files?

If the LoRA ships as a pair, yes, load both on their matching experts. Some camera and transition LoRAs only have a high-noise file, which is enough because the high-noise expert controls motion.

Can I use Wan 2.1 LoRAs with Wan 2.2?

Many load and work on the low-noise expert, but results on the high-noise expert are unreliable. Prefer LoRAs trained for Wan2.2-I2V-A14B or Wan2.2-T2V-A14B.

What strength should I use for Wan 2.2 LoRAs?

1.0 for speed LoRAs, 0.8-1.0 for camera and motion LoRAs, and 0.6-1.0 for style LoRAs. Lower the high-noise strength if a style LoRA breaks motion.

Do Wan 2.2 LoRAs work with GGUF models?

Yes. Connect the Unet Loader (GGUF) output to a LoraLoaderModelOnly node as usual.

Do Wan 2.2 14B LoRAs work on the 5B model?

No. The TI2V 5B model has a different architecture and needs LoRAs trained for it.

Final Thoughts

Start with the LightX2V 4-step pair, add the Slow-Mo Fix if your I2V clips look sluggish, and then add one camera or style LoRA at a time. That gets you 90% of what Wan 2.2 LoRAs can do without a messy stack. Keep everything in ComfyUI/models/loras/, always match high to high and low to low, and use Power Lora Loader so testing is quick.

Next: set up the base model with my Wan 2.2 8-16 GB guide, compare Wan with newer models in the best local AI video models, or try LTX-2.5 with my LTX-2.5 16 GB setup.

Sources

• lightx2v/Wan2.2-Distill-Loras and lightx2v/Wan2.2-Lightning
• rzgar Slow-Mo Fix and rzgar 2-Step
• alibaba-pai/Wan2.2-Fun-Reward-LoRAs
• ostris Orbit Shot, 360 Rotation, FollowCam
• morphic/reshoot-anything and morphic/Wan2.2-frames-to-video
• renderartist/technically-color-wan, Cseti Kinestasis, neph1 Quick Cuts
• Teluv Attack Sprite Animation, drnighthan Cloth Consistency
• Hugging Face: Wan2.2-I2V-A14B adapters by likes