How do these times scale to other GPUs?

Roughly linearly with VRAM against a 16 GB reference: a 12 GB card is about 1.3x slower, an 8 GB card about 2x slower. With no CUDA GPU the same work is roughly 8x slower. Non-GPU styles such as stock footage do not scale at all.

Benchmark

AI video render times, measured on a real RTX 5060 Ti

Q: How long does it take to render a 10-minute AI video?

On a 16 GB RTX 5060 Ti: about 3 minutes with free cloud stills, 9-10 minutes with local FLUX or SDXL stills, 16 minutes with LTX-Video in fast mode, 33 minutes with LTX in quality mode, and 3.5-5.5 hours with Wan 2.2. A 10-minute video is roughly 40 scenes.

Q: Which local AI video model is fastest?

Of the real motion models, LTX-Video is by far the fastest: 24 seconds per scene in fast mode versus 332 seconds for Wan 2.2 - about 14x faster. AnimateDiff sits between them at 38 seconds per scene.

Q: Is Wan 2.2 worth the render time?

Only for short hero clips. Wan 2.2 produces the best quality of the local options, but at 332-480 seconds per scene a full 10-minute video takes 3.5-5.5 hours on a 16 GB card. LTX is the practical daily driver.

Every "AI video generator" comparison online quotes marketing numbers. These are ours, measured on one card, in one pipeline — with the method and the caveats attached.

Measured 2026 · NVIDIA RTX 5060 Ti · 16 GB VRAM · 31 GB RAM · Windows · ComfyUI backend

Seconds per scene, by engine

A "scene" is one shot: one image or one short generated clip, roughly 11 seconds of finished video. Every number below is wall-clock time on the same machine, measured inside ReelForge's render pipeline.

Engine	What it makes	Quality mode	Fast mode	Needs GPU
Stock footage (Pexels)	Real video clips	2 s	2 s	no
Free cloud stills (Pollinations)	AI images	5 s	5 s	no
Code-drawn cards	Doodle / gradient	1 s	1 s	no
FLUX.1	AI images (local)	14 s	14 s	yes
SDXL	AI images (local)	15 s	15 s	yes
LTX-Video	Real motion	50 s	24 s	yes
AnimateDiff + upscale	Stylized motion	90 s	38 s	yes
Wan 2.2 (5B)	Cinematic motion	480 s	332 s	yes

The headline: LTX-Video is roughly 14× faster than Wan 2.2 in fast mode (24 s vs 332 s per scene) — for motion that is still genuinely good. That single ratio decides whether a faceless channel is practical or not.

What that means for a 10-minute video

A 10-minute video works out to about 40 scenes (~11 s each). Multiply the numbers above and the picture changes completely:

Engine	Fast mode	Quality mode	Verdict
Code-drawn cards	40 s	40 s	instant
Stock footage	1.3 min	1.3 min	instant
Free cloud stills	3.3 min	3.3 min	instant
FLUX stills	9.3 min	9.3 min	easy daily
SDXL stills	10 min	10 min	easy daily
LTX-Video	16 min	33 min	daily driver
AnimateDiff	25 min	60 min	stylized only
Wan 2.2	3 h 41 m	5 h 20 m	hero clips only

This is the number nobody publishes, and it is the one that matters. Wan 2.2 makes the best-looking output of the local models — genuinely film-grade, volumetric light and all — but a daily faceless channel on Wan means your GPU is busy for five hours per upload. LTX gets you 80% of the way in 16 minutes.

How this scales to your GPU

GPU-bound engines scale roughly with VRAM against the 16 GB reference. The multiplier we use is 16 ÷ your VRAM, clamped between 0.5× and 3.5×; with no CUDA GPU, expect about 8×. Non-GPU styles (stock, free cloud stills, code-drawn cards) do not scale — they are network- or CPU-bound and take the same time on any machine.

Your GPU	Multiplier	LTX fast, 10-min video	Wan fast, 10-min video
24 GB (e.g. 4090)	0.7×	~11 min	~2 h 30 m
16 GB (reference)	1.0×	16 min	3 h 41 m
12 GB	1.3×	~21 min	~4 h 55 m
8 GB	2.0×	~32 min	won't run
No CUDA GPU	8.0×	~2 h 8 m	won't run

Honest caveat: this is a linear approximation, not a benchmark suite. Real scaling is not purely linear — once a model no longer fits in VRAM it offloads to system RAM and falls off a cliff far worse than the multiplier suggests. That is exactly what happens with Wan 2.2 on 16 GB: the model plus its text encoder is ~16 GB, so even our "reference" number is already an offloading number.

Method, so you can argue with it

One machine: RTX 5060 Ti 16 GB (Blackwell, sm_120), i5-14400F, 31 GB RAM, Windows, torch 2.11 + CUDA 12.8, ComfyUI backend.
Wall clock, per scene, inside the real pipeline — not synthetic model benchmarks. Includes prompt handling, VAE decode and file write.
Fast vs quality = fewer frames and fewer steps. LTX: 49 frames/12 steps vs 65/20. AnimateDiff quality includes a RealESRGAN upscale pass, which is most of its 90 s.
Warm runs. The first generation after launch pays a model-load penalty (tens of seconds to minutes) that these numbers exclude.
Not included: script generation, voiceover and the final ffmpeg mux. Those are seconds-to-a-minute and are not GPU-bound.

If your numbers differ, they should — different card, different driver, different steps. The ratios are the durable part: LTX ≈ 14× faster than Wan, stills ≈ 2× faster than LTX, non-GPU styles ≈ instant.

What we actually run

Given the table: LTX-Video in fast mode for everyday videos, FLUX stills when a video does not need real motion, and Wan 2.2 only for a hero shot or two. The mixed approach — motion on the hook and a few accents, Ken Burns stills for the rest — lands a 10-minute video in well under half an hour on a 16 GB card.

FAQ

How long does it take to render a 10-minute AI video?

On a 16 GB RTX 5060 Ti: ~3 minutes with free cloud stills, ~9-10 minutes with local FLUX or SDXL stills, 16 minutes with LTX-Video fast, 33 minutes with LTX quality, and 3.5-5.5 hours with Wan 2.2. A 10-minute video is about 40 scenes.

Which local AI video model is fastest?

LTX-Video, clearly: 24 s per scene in fast mode against 332 s for Wan 2.2 — about 14× faster. AnimateDiff sits between at 38 s but is only convincing on stylized content.

Is Wan 2.2 worth the render time?

For short hero clips, yes — it is the best-looking local model we tested. For a daily channel, no: five hours of GPU per upload is not a workflow.

Do I need a GPU at all?

No. Stock footage, free cloud stills and code-drawn cards need no GPU and render a 10-minute video in 1-3 minutes. You only need a GPU for local AI images or real motion. See the GPU guide.

Why is AnimateDiff quality mode so much slower than fast?

Quality mode adds a RealESRGAN upscale pass on every frame. That pass, not the diffusion, is most of the 90 s.

What GPU do you need for AI video?VRAM tiers and what each one actually unlocks What a faceless channel really costsThe render bill nobody adds up

These numbers come from a tool you can run

ReelForge renders on your own machine — it shows this estimate before you commit a single minute.

See ReelForge