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The Best Wan 2.1 Prompts: Open-Source AI Video That Works

A data-grounded guide to the best Wan 2.1 video prompts on Wikiprompt: what the open-source model does well, the prompt patterns that work, and 10 templates to steal.

Wan 2.1 is the model that proved open-source AI video is real. Released by Alibaba's Tongyi lab in February 2025 with open weights, it runs text-to-video and image-to-video on consumer GPUs (the 1.3B variant fits in 8 GB of VRAM) and quickly became the default local video model for the Stable Diffusion crowd. Wikiprompt hosts 420+ Wan 2.1 prompts with their generated results, most of them paired with human preference scores. This guide picks the ones worth stealing.

What Wan 2.1 is good at

Reading the metadata across the whole Wan 2.1 corpus, three strengths repeat:

Nature and atmosphere. The most common keywords in the corpus are vibrant, nature, cinematic, serene and landscape. Misty lakes, alpine forests, underwater reefs: this is where Wan's motion looks most believable.

Water and particle motion. Rain, waves, fog and drifting particles hold together well across frames, which is why storm and ocean prompts score high on wow.

Single-subject camera follows. A leopard prowling, a dancer turning, a surfer riding: one subject plus one described camera move is the reliable recipe. Multi-subject choreography is where it breaks.

Patterns that work

The high-scoring prompts share a structure worth copying:

Open with the shot, not the story. "A snow leopard prowls gracefully through a misty alpine forest at dawn" reads like a shot list, not a synopsis.

One explicit camera instruction. The best results say what the camera does: follows, glides, pans. Wan respects simple moves and ignores complicated ones.

Name the light. Golden sunrise, neon reflections on wet streets, sunlight filtering through water. Light words do more for coherence than style words.

Keep it under ~80 words. The corpus shows no quality gain past that; long lore-heavy prompts score the same or worse.

The best Wan 2.1 prompts

Mountain Thunderstorm Cinematic Prompt - lightning, lashing rain and dark clouds; the most reusable template of the set (swap the mountain for any dramatic location).

Neon Motorcycle Night Ride - the cyberpunk classic done right: wet-street reflections are Wan's party trick.

Snow Leopard in Misty Alpine Forest - a camera-follow wildlife shot with dawn light; swap the animal and biome.

Ballet dancer at misty riverbank dawn - single-performer motion with a flowing red dress, the fabric physics sell it.

Misty Lake Fishermen at Sunrise - golden-hour water scene, pure atmosphere.

Phoenix over Bamboo Forest at Sunrise - fantasy subject, realistic light; a good test of how far you can push non-real subjects.

Vibrant Underwater Coral Reef Panorama - fish schools and light shafts; underwater is a Wan sweet spot.

Lone Surfer at Dawn - silhouette against sunrise on a towering wave.

Serene Mermaid in Coral Reefs - the underwater strength applied to a fantasy subject.

Generational Starship Voyage Montage - an ambitious montage brief; useful as a template for evolution-over-time videos.

A starter recipe

Copy this skeleton and fill the brackets:

[SUBJECT] [does one action] in [location] at [time of day]. The camera [follows / glides / pans] as [one secondary detail]. [Light description]. Cinematic, realistic.

Example: "A red fox trots across a frozen lake at dusk. The camera glides low beside it as snow begins to fall. The last orange light catches the ice. Cinematic, realistic."

Where these prompts come from

Most of the Wan 2.1 corpus on Wikiprompt comes from Rapidata's open human-preference datasets: each prompt was rendered by multiple video models and scored by thousands of human raters, so the results you see are the actual Wan 2.1 outputs, not cherry-picked marketing clips. Every prompt page links its source.

Explore the full set at Wan 2.1 prompts, compare models side by side in the Prompt Arena, or check how Wan stacks up against Veo, Kling and Seedance on the video leaderboards.