How to Get Better Quality AI Video: Practical Techniques for Runway, Pika, and Kling

Generating AI video at a quality level that’s actually useful for content creation requires more than writing a prompt and hoping for the best. The good news is that a handful of specific techniques move the needle significantly, and most of them don’t require expensive hardware or subscriptions. This guide covers what actually works for improving output quality across the three most widely used tools: Runway Gen-3 Alpha, Pika 1.5, and Kling 1.0.

Prompt-Level Quality Improvements

The single highest-leverage change you can make is adding cinematographic language to your prompts. AI video models are trained on video datasets that include film, television, and professional photography — they respond to the same vocabulary that DPs and directors use.

Quality descriptors that work:

Arri Alexa cinema camera or Red Dragon cinema camera — these signal professional-grade footage
shallow depth of field — encourages natural background bokeh
anamorphic lens — produces the characteristic wide-screen oval bokeh seen in cinematic content
8K, photorealistic, ultra-detailed — general quality boosters that tend to increase output fidelity
natural film grain — paradoxically makes AI video look more real by introducing organic texture

Lighting descriptors that improve output:

golden hour sunlight / magic hour — warm directional light that models handle well
Rembrandt lighting — classic portrait lighting with one highlighted side
diffused overcast light — soft, shadowless lighting that avoids the model struggling with hard shadows
neon reflections on wet pavement — AI models have learned this specific look from film and photography training data, and it often produces striking results

Camera movement language:

Most users don’t specify camera movement, which means the model defaults to a generic drifting pan or static shot. Specifying movement improves coherence significantly:

slow dolly push-in — camera moves steadily toward the subject
orbit around subject — camera circles the subject (works better in Runway than Pika)
crane shot looking down — top-down perspective
handheld camera, slight motion — natural, documentary-style movement

Platform-Specific Techniques

Runway Gen-3: Using Motion Brush

Runway Gen-3 has a Motion Brush feature that lets you specify motion for particular regions of an image before generating. This is the best way to control what moves and what stays still. For example: upload a landscape image, paint the sky region with an upward brush stroke, and generate — you’ll get a stable foreground with moving clouds.

To access it: start an image-to-video generation, then click “Motion Brush” before submitting. You can add up to 5 different motion regions. Use broad strokes for natural motion (wind, water) and more precise strokes for object-level control.

For Runway specifically: multiple short regenerations often beat a single long one. If you need a 10-second clip, it’s often better quality to generate two 5-second clips and combine them in editing than to let Runway generate 10 seconds directly. Quality tends to degrade in the latter half of longer Runway generations.

Pika 1.5: Negative Prompts

Pika supports negative prompts — descriptions of what you don’t want — and for this platform they’re more impactful than on Runway. Common negative prompts that improve output:

blurry, low quality, watermark — basic quality filter
distorted faces, deformed hands, extra fingers — reduces the common human figure artifacts
fast motion, jittery, shaky — forces slower, more stable motion
text, words, letters — prevents the model from generating garbled text in the scene

Access negative prompts in Pika by expanding the “Advanced Options” section of the generation interface.

Kling 1.0: Professional Mode

Kling offers a Professional Mode that generates at higher fidelity at the cost of longer processing time and higher credit consumption. For final outputs intended for publication, always use Professional Mode. Standard mode is appropriate for quick iteration, but the quality difference is visible.

Kling also responds well to Chinese-language prompts if you’re generating content with cultural elements in that context — the training data skews toward Chinese-language descriptions, and some users report better results for specific content types when prompting in Mandarin.

Fixing the Most Common Quality Problems

Problem: Temporal Inconsistency (Objects Flicker or Warp)

This is the most common and frustrating failure mode. A rock disappears between frames, a person’s shirt changes colour, a building’s window arrangement shifts.

Fix: Reduce clip duration. Generating 4 seconds instead of 8 dramatically reduces temporal drift. Additionally, remove any description of the scene changing or evolving — e.g., replace “clouds move across the sky” with “light clouds, slow drift” for a more stable result.

Problem: Human Faces Look Wrong

AI video models still struggle significantly with human facial detail in extended clips. Close-up portrait shots often degrade over the course of a clip, particularly around eyes and mouth.

Fix 1: Avoid close-up shots of faces in text-to-video mode. Use image-to-video instead, where the model has a concrete reference for the face.

Fix 2: For avatar-style content featuring speaking characters, specialised tools like HeyGen or Synthesia are significantly better than general-purpose video generators. HeyGen starts at $29/month and is purpose-built for lip-synced avatar videos.

Problem: Low Resolution or Blurry Output

Fix 1: Enable the HD/1080p option in Runway or Kling professional mode. This is the most straightforward fix.

Fix 2: For clips that are already generated at 720p or below, Topaz Video AI ($199 one-time license, available at topazlabs.com) is the industry-standard upscaling tool. Its Veai models can upscale a 720p AI video clip to a clean 4K output, and it includes motion-aware denoising that removes the specific noise patterns AI video introduces. The results are significantly better than any online upscaler.

Problem: Artifacts at the Edges of the Frame

Many AI video tools produce visible artifacts (warping, colour bleeding, soft edges) at the frame borders. This is a known characteristic of the underlying diffusion architecture.

Fix: In your editing software, apply a very slight crop (2–3%) to all four sides of the frame. This removes the worst edge artifacts while preserving the central image. In DaVinci Resolve, this is a single click in the Transform menu.

Post-Processing Workflow

For creators using AI video professionally, a lightweight post-processing pipeline makes a significant difference to the perceived quality of final output:

Upscale to 1080p or 4K using Topaz Video AI if generating at lower resolutions
Apply gentle sharpening — AI video tends to be slightly soft; 0.3–0.5 sharpening in Resolve or Premiere is usually enough
Apply a LUT (Look Up Table) for colour grading — free LUTs from sites like Ground Control or Lutify.me add a consistent, professional colour treatment across multiple clips
Add film grain as a compositing step — a small amount of natural grain (10–15%) blends AI video with natural footage and reduces the “perfect” look that reads as synthetic

DaVinci Resolve (free version) handles all four steps and is the most widely used tool in this workflow among professional AI video creators.