AI Video Frame Interpolation: Smooth Slow Motion From AI Clips

AI video generators hand you short clips — often 5 to 10 seconds, sometimes at 24fps with visible choppiness on motion. You want slow motion. You want 60fps smoothness. You want a 4-second generation to stretch into a usable 8-second shot. Frame interpolation is the technique that makes this possible: synthesizing new frames between the real ones, turning choppy AI clips buttery. Done right, it’s invisible. Done wrong, it’s a smeary mess. This guide covers how interpolation works, which tools handle AI footage best, the settings that matter, and where it falls apart.

What AI video frame interpolation actually does

A 24fps clip shows 24 images per second. Frame interpolation creates images that were never captured — frame 1.5, frame 2.5 — by analyzing motion between real frames and synthesizing what the in-between moment should look like. Play the result at a higher frame rate and motion looks smoother; play it at the original rate and you’ve manufactured slow motion. Out of nothing, basically. Pretty wild when you think about it.

Optical flow: the core idea

Most interpolation starts with optical flow. The algorithm tracks how every pixel (or region) moves from frame A to frame B, building a motion map. Then it warps both frames along that motion map to synthesize the middle frame. When the motion map is accurate, the result is clean. When it’s wrong — complex motion, occlusions, morphing — you get the classic interpolation artifacts: ghosting, warping, smeared edges. You’ve seen these. They look like a bad dream.

RIFE and the AI generation

RIFE (Real-Time Intermediate Flow Estimation) is the open-source model that changed interpolation for creators. It’s a neural network trained specifically to estimate those in-between frames, and it’s dramatically better than old-school optical flow on difficult motion. RIFE is free, open-source, and embedded in several free tools — which means professional-quality interpolation no longer requires professional software budgets. Newer models keep pushing quality further, but RIFE remains the baseline everything is measured against.

The tools, compared

Topaz Video: Apollo, Chronos, Aion

Topaz Video (formerly Topaz Video AI) is the premium option, with three interpolation models for different jobs:

Apollo: best for clean frame-rate multiples (24→48, 30→60) and non-linear motion. The go-to for straightforward smoothing.
Chronos: best for arbitrary conversions (24→60) and stable footage. Handles non-exact multiples more gracefully.
Aion: the heavy model for difficult motion and 4K+ footage. Slowest, best quality on hard shots.

Topaz is subscription-only as of late 2025 — Personal starts around $299/year or $59/month, Pro higher (verify current pricing on Topaz’s site before buying; pricing has changed before). There’s a free trial, but exports are watermarked, so you can’t evaluate finished output without paying. For creators doing client work or heavy volumes, it’s the quality reference. For occasional use, the free options below get you most of the way there. Honestly, most of the way.

FlowFrames (free, RIFE-based)

FlowFrames is a free Windows GUI wrapping RIFE and other interpolation models. No subscription, no watermark, genuinely good results. The interface is less polished than Topaz and it’s Windows-only, but the output quality on typical AI footage is remarkably close to the paid tools. If you’re interpolating occasionally and running Windows, start here before spending money. Start here, full stop.

DaVinci Resolve (Optical Flow / Speed Warp)

Resolve has interpolation built into retiming: standard Optical Flow in the free version, and the higher-quality Speed Warp in the paid Studio version. For mild jobs — 24fps to 30fps, slight slow motion — Resolve’s built-in tools are convenient because there’s no round-trip to another app. For heavy slow motion (4x and beyond), dedicated tools usually win on quality.

SVFI and other free options

Smooth Video Frame Interpolation (SVFI) and similar free tools offer RIFE-based interpolation with simple interfaces. Worth trying if FlowFrames doesn’t suit your setup. The underlying model matters more than the wrapper — RIFE-based is RIFE-based.

The honest ranking for AI footage: Topaz Aion/Chronos for the hardest shots and client work; FlowFrames/RIFE for everything else at zero cost; Resolve built-in for quick mild retimes inside an existing edit. Most creators never need more than the free tier of this stack.

Best settings for AI footage specifically

AI footage interpolates differently than camera footage. The models were trained largely on real video; AI clips have their own quirks. So don’t just copy camera-footage settings and hope:

Start with the middle model, not the strongest. On Topaz, try Chronos before Aion; in FlowFrames, standard RIFE before the heavy variants. AI footage is often clean enough that the middle option is artifact-free, and stronger models cost more render time for no visible gain.
Keep slow-motion factors modest. 2x slow motion (24fps → 48fps played at 24) is safe on most AI clips. 4x works on clean, simple motion. Beyond 4x, you’re asking the model to invent a lot — artifacts multiply. If you need extreme slow motion, generate the clip with slow movement in the first place rather than stretching a fast clip.
Interpolate before upscaling, not after. If you’re also enhancing resolution, run interpolation on the smaller file first — it’s faster, and upscaling interpolated frames tends to look cleaner than interpolating upscaled frames (fewer pixels for the motion estimation to get confused by).
Watch the edges of morphing regions. AI clips often have subtly morphing textures (backgrounds that breathe, faces that shift). Interpolation treats morphing as motion and amplifies it. Preview these regions specifically.
Always preview 5 seconds before committing. Every tool above offers previews. Render a representative 5-second section, watch it at full speed, check moving edges and fine detail. Interpolation artifacts hide in stills and reveal themselves in motion.
Export to an intermediate codec. Export interpolated results to ProRes, DNxHR, or high-bitrate H.265 — not a low-bitrate H.264 you’ll then re-compress in the edit. Double compression on interpolated frames visibly degrades them.

When interpolation fails

Knowing the failure modes saves you from rendering for hours on shots that were never going to work. Hours. Gone:

Fast, chaotic motion. Whip pans, explosions, flailing limbs — motion too complex for the flow map. Result: smeared, melted frames. Fix: don’t interpolate these shots; cut around them or use them at native frame rate.
Morphing AI artifacts. If the source clip has morphing (a face subtly changing shape, a background crawling), interpolation reads the morph as motion and exaggerates it. Fix: pick a cleaner generation — interpolation can’t fix source problems, it magnifies them.
Flicker. AI clips with temporal flicker (brightness pulsing frame to frame) interpolate badly — the flicker becomes baked into the new frames. Fix: deflicker first (some tools have this; or stabilize brightness in the grade), then interpolate.
Occlusions. Objects passing behind other objects confuse motion estimation at the overlap boundary. Result: ghosting or tearing at the occlusion edge. Fix: mild factors only on occlusion-heavy shots, or mask the problem region.
Repeating patterns. Fences, fabrics, brick walls — fine repeating detail breaks optical flow. Result: shimmering, crawling patterns. Fix: these shots often look better uninterpolated.

The meta-rule: interpolation is a finishing technique, not a rescue technique. It makes good clips smoother. It makes flawed clips flawedly smoother. Remember that and you’ll save yourself a lot of render time.

The slow-motion workflow from short AI clips

The most common professional use: turning a 5-second AI generation into a 10-second slow-motion shot. Step by step:

Generate with slow motion in mind. Prompt for slow, deliberate movement (“slow graceful turn,” “gentle drift”). Fast action in the source becomes unusable mush when stretched — the source motion determines the ceiling.
Pick the cleanest generation. No morphing, no flicker, simple motion. Interpolation multiplies what’s there; start clean.
Trim to the usable section. Don’t interpolate the whole clip if only 3 seconds are good. Cut first, process second.
Interpolate at 2x. 24fps → 48fps (or 25→50). Preview 5 seconds, check edges and detail in motion.
Conform to timeline rate. Play the 48fps file at 24fps in your editor for true 2x slow motion — every frame is real (or synthesized-once), motion is smooth.
Grade after interpolation. Interpolation first, color second — grading changes pixel values the motion estimation would rather see clean.
Optional: push to 4x only if the 2x result is flawless and the shot needs it. Diminishing returns beyond this on AI footage.

Interpolation vs generating more frames

A reasonable question: why not just generate at higher frame rates or longer durations directly? Sometimes you should:

Generate longer when the motion is complex. If interpolation fails on a shot, a fresh generation with slower prompted motion often beats fighting the interpolation.
Interpolate when the clip is already good. Clean clip, simple motion, just needs smoothing or stretching — interpolation is faster and cheaper than re-rolling generations.
Watch the credit math. Re-generating costs generation credits; interpolation costs render time (free on local tools). For paid generators, interpolation is usually the cheaper path — check the cost guide for current credit economics.
Some generators now offer native higher fps. When choosing tools in the generator guide, note which ones output 30/60fps natively — native frames always beat synthesized ones.

Dialing in FlowFrames: a practical walkthrough

Since FlowFrames is the free starting point most creators should try first, here’s how to get good results from it without guesswork:

Import and set the target. Load your trimmed AI clip. Set the output frame rate — 48fps from 24fps source for 2x slow motion, 60fps for smooth high-frame-rate delivery.
Choose the RIFE model version. Newer RIFE versions generally handle complex motion better; older ones render faster. For AI footage, the difference is usually small — start with the default recent version.
Set the interpolation factor, not just fps. Think in multiples: 2x, 4x. Exact multiples (24→48) interpolate more cleanly than arbitrary targets (24→60) because every output frame maps evenly to synthesized positions.
Enable scene detection. AI clips sometimes have hard cuts or abrupt changes (especially stitched generations). Scene detection prevents the interpolator from trying to blend across a cut — which produces horrible smeared transition frames.
Render a test segment first. FlowFrames lets you process a portion. Pick the 5 seconds with the most motion — that’s where artifacts will appear if they’re going to.
Inspect at full speed, then frame-step the suspicious parts. Watch normally first (that’s how your audience sees it), then step through any section that looked odd to identify whether it’s ghosting, warping, or source morphing.

If the test is clean, run the full clip. If it’s not, don’t tweak endlessly — the usual fix is a cleaner source clip or a lower factor, not different settings. Seriously, don’t fall down the settings rabbit hole. Source first.

Interpolation for high-frame-rate delivery

Beyond slow motion, there’s a second use case: delivering at 60fps for platforms and audiences that expect it. Gaming content, sports-style edits, and smooth product showcases all benefit from 60fps delivery — but most AI generators output 24 or 30fps.

24→60 is harder than 24→48. Non-exact multiples force uneven frame synthesis. On Topaz, this is Chronos territory; in free tools, expect slightly more artifacts than exact-multiple conversions. Test before committing a whole project.
Consider 30→60 instead. If your generator offers 30fps output, generate at 30 and interpolate to 60 — the 2x multiple is cleaner than 24→60.
Not everything needs 60fps. Cinematic content at 24fps is a deliberate aesthetic. Reserve 60fps delivery for content where smoothness is the point — and keep in mind most viewers watch shorts on phones where the difference is subtle.
File sizes grow. 60fps files are substantially larger than 24fps. For long-form content, weigh the smoothness gain against upload times and platform re-compression (which can eat the benefit anyway).

Practical rules of thumb

2x is safe, 4x is conditional, 8x is a gamble — on typical AI footage with typical motion.
Preview everything. Five seconds now saves five hours later.
Fix the source first. Morphing, flicker, and chaos don’t interpolate — they amplify.
Free tools are genuinely good. Try FlowFrames/RIFE before buying Topaz; buy Topaz when free tools fail on shots that matter.
Build it into the pipeline. Interpolation sits after editing selects and before grading: generate → select → interpolate → grade → mix → export. Doing it in this order avoids re-rendering.
Plan slow motion at the prompt. The storyboard-first approach applies here too — shots planned for slow motion get slow-movement prompts, and everything downstream gets easier.

Frame interpolation is one of the highest-leverage techniques in AI video post-production: it doubles your usable clip lengths, smooths choppy generations, and manufactures slow motion from footage that was never shot for it. Learn which shots take it well, preview religiously, and keep the free tools in your pocket — most of what you need costs nothing but render time. Nothing but render time.