Wan 2.5 vs Runway Gen-4: Open vs. Closed AI Video — LiliDi Blog
Explore the technical differences between Wan 2.5 and Runway Gen-4. Compare open-source model flexibility with closed-source performance for AI video generatio…
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Wan 2.5 vs Runway Gen 4: Open vs. Closed AI Video TL;DR Wan 2.5 is the open weights option: flexible, cheap to iterate on, strong at motion when prompted carefully. Runway Gen 4 is the closed studio option: more consistent characters, stronger scene control, higher cost per second. On Lilidi both sit in one credit wallet, so you can benchmark the same prompt on both before standardising. Choosing between an open weights video model and a closed studio model is not really a quality argument any more. Both families produce broadcast usable clips in 2026. The decision is about control, cost per usable second, and how much of your workflow you want to own. This guide compares Wan 2.5 and Runway Gen 4 on the axes that change your output, and shows how to test both without buying two subscriptions. The short version: what each model is for Wan 2.5 comes from the open weights lineage. Its
advantage is iteration economics — you can run many variations cheaply, tune prompts aggressively, and it responds well to detailed camera and lighting direction. Its weakness is consistency: characters drift across shots more than a closed model, and text inside frame is unreliable. Runway Gen 4 is a closed, hosted system tuned end to end. It holds character and scene identity across shots better than almost anything open, and its motion is smoother out of the box. You pay for that with higher cost per second and less control over the underlying weights. Head to head comparison Axis Wan 2.5 Runway Gen 4 Model access Open weights, many hosts Closed, single vendor Character consistency Moderate — needs reference frames Strong across shots Motion smoothness Good, prompt sensitive Very good by default Prompt control High, rewards detail High, more abstracted Cost per second on Lilidi Lower
tier, from 54 credits/s equivalent Premium tier, up to 200 credits/s (Fast: 50) Typical wait, 5 s clip 2 4 min 2 5 min Best use Volume social, concepting, style tests Hero shots, narrative, client work Treat the credit figures as the shape of the gap rather than a fixed quote: exact per model costs are always displayed in the Lilidi picker before you render, and are listed in the models catalogue. Cost per usable second is the only honest metric Comparing list prices is misleading because the two models fail differently. Open models need more attempts; closed models need fewer but cost more each. Budget realistically: Wan 2.5: assume three attempts per keeper. A 5 second keeper is therefore roughly 810 credits at 54 credits per second. Runway Gen 4: assume two attempts per keeper at a premium tier. A 5 second keeper lands in a similar band, sometimes higher. The result surprises people:
for hero shots, the closed model is often no more expensive in practice, while for volume social content the open model wins clearly because you are not chasing perfection. Where the open model wins 1. Style exploration. Twenty cheap variants beat three expensive ones when you do not yet know what the shot should look like. 2. Prompt level control. Wan 2.5 responds precisely to lens, movement and lighting language, so directors who write specific prompts get more of what they asked for. 3. Volume output. Social calendars that need thirty clips a month are an economics problem before they are a quality problem. 4. No vendor lock in. Open weights mean the same model stays available across hosts. Where the closed model wins 1. Character continuity. If the same person must appear in shots three, seven and eleven, Gen 4 drifts less. 2. Default polish. Fewer artefacts on hands, faces and fast
motion without extra prompt engineering. 3. Client facing reliability. Less variance per render means fewer surprises in an approval cycle. 4. Scene control tooling. Reference driven controls are more mature in the closed ecosystem. A practical workflow that uses both The teams getting the best results do not choose. They stage: 1. Concept on the open model. Cheap variants until the shot list is locked. 2. Lock references. Export the best frame as a start frame for continuity. 3. Render heroes on the closed model. Three to five shots that carry the piece. 4. Fill the sequence on the open model. Cutaways, textures, B roll. 5. Unify in the grade. A consistent colour pass hides most model to model differences. On Lilidi this is a single project in a single wallet: switch models in the picker, keep the same prompt, and compare renders side by side in your library. Prompting differences that
actually matter Wan 2.5 rewards mechanical specificity — focal length, camera move, lighting direction, shutter feel. Gen 4 rewards intent — describe the moment and the emotional register, and let the model resolve the mechanics. Copying a prompt straight across usually underperforms; rewriting it for the model's temperament takes a minute and saves several renders. Negative prompts help both. Ruling out warping, extra limbs, jitter and text artefacts costs nothing and measurably reduces re rolls. Which should you standardise on? Solo creator, high volume: Wan 2.5. Iteration economics dominate. Agency with client approvals: Runway Gen 4 for deliverables, open model for internal exploration. Product and e commerce: test both on your actual product; results vary more by subject than by benchmark. Narrative and character work: closed model, every time, until open character consistency
closes the gap. FAQ Q: Is Wan 2.5 worse than Runway Gen 4? No — it is different. On single shot motion quality the gap is small. On multi shot character consistency the closed model is clearly ahead today. Q: How much does a 5 second clip cost? On Lilidi, video is priced per second: 54 credits per second on the value tier and up to 200 credits per second on premium (Fast: 50). A 5 second clip is therefore roughly 270 to 1,000 credits, always shown before you render. Q: Can I use both models on one project? Yes. One Lilidi wallet covers every model, so you can concept on one and finish on another without separate subscriptions. Q: Do open weights models have commercial restrictions? Licences vary by model and by host. Check the licence for the exact model you use; on Lilidi the terms are surfaced per model in the catalogue. Q: Which handles text on screen better? Neither is reliable for
in frame typography. Render text in an editor or generate it as a still with a text capable image model and composite it. Q: How long does a render take? Two to five minutes for a 5 second clip on either family, depending on queue depth and resolution tier. Renders run in the background, so you can queue several at once. Related on Lilidi AI video prompt engineering: 2026 guide A realistic look at the best AI video generators Negative prompts for AI video All models and live credit costs Head to head comparisons Use cases by workflow Try it on Lilidi Open the video studio, run the same prompt through both families, and compare the credit cost and the result before you commit a project to either.