LTX-Video 2.3 vs HunyuanVideo — Open-Source AI Video Head-to-Head

2026-05-25 · 7 min read · LoreMotion Team

Hands-on comparison of the two best open-source AI video models in 2026. Output quality, motion realism, VRAM requirements, generation speed, and real cost per clip.

If you want to self-host a serious open-source video model in 2026, the choice essentially comes down to two: Lightricks' LTX-Video 2.3 or Tencent's HunyuanVideo. Every other open model is either further behind on quality (Wan 2.1, CogVideoX, Mochi) or significantly less capable on consumer hardware. This post compares LTX-Video 2.3 and HunyuanVideo head-to-head on the dimensions that actually matter.

We've run thousands of clips on both. LoreMotion's production service uses LTX-Video 2.3, and we evaluated HunyuanVideo extensively before deciding. Here's what we found.

TL;DR — which one to use

Detail below.

Architecture and training data

LTX-Video 2.3 is a 22-billion-parameter diffusion transformer. Lightricks trained it on a large internal video dataset (size not publicly disclosed; estimated 50–100M clips) heavily filtered for quality. The 2.3 release added native audio generation, distilled inference (~4x faster than 2.0 at equivalent quality), and improved temporal coherence at longer clip lengths (up to 8 seconds native).

HunyuanVideo is a 13-billion-parameter MMDiT (multimodal diffusion transformer). Tencent trained it on a dataset they describe as "billions of seconds" of curated video, with explicit attention to caption quality (Tencent re-captioned a significant portion of the dataset with their own VLM rather than using web-scraped alt text).

On paper LTX has more parameters but HunyuanVideo has more (and possibly higher quality) training data. The output quality gap suggests data quality matters more than parameter count.

Hardware requirements

This is where the two models diverge sharply.

LTX-Video 2.3 minimums:

HunyuanVideo minimums:

Practical implication: if your hardware is a consumer GPU, you're effectively limited to LTX-Video 2.3 if you want production-grade quality. HunyuanVideo on a 24 GB card looks worse than LTX-Video 2.3 on the same card — the quantisation tax is bigger than the architectural quality advantage.

We tested HunyuanVideo with GGUF Q4 on an RTX 3090 extensively. Colour reproduction shifts noticeably toward muddy mid-tones, fine motion gets jittery, and character faces drift across the clip. LTX-Video 2.3 at int8 is essentially indistinguishable from its bf16 reference; HunyuanVideo at Q4 is clearly degraded.

Generation speed

Wall-clock for a 5-second 720p clip:

Model RTX 3090 RTX 4090 A100 80 GB H100 80 GB
LTX-Video 2.3 (Wan2GP int8) 72s 44s 28s 19s
HunyuanVideo (Q4 quant) 240s 145s n/a n/a
HunyuanVideo (full precision) OOM OOM 78s 52s

LTX is faster on consumer hardware by a wide margin and faster on cloud H100s by 3x. This compounds in production — at LoreMotion we serve ~1,200 LTX clips per day per RTX 3090. The same workload on HunyuanVideo would require A100 80 GB instances at roughly 10x the per-clip cost.

Output quality (subjective, blind tested)

We generated 100 prompts on each model (LTX at int8 on RTX 3090; HunyuanVideo at full precision on H100) and had five people rank outputs blind. Composite results:

Overall, in our blind ranking HunyuanVideo won 58% of head-to-head pairs, LTX won 31%, and 11% were rated equal. That's a real gap, but not the chasm that some online comparisons suggest.

Motion specifics

A few details we measured that matter for production use:

Temporal stability: LTX-Video 2.3 has slightly better frame-to-frame consistency in static backgrounds. HunyuanVideo occasionally produces subtle background "boiling" (texture shimmer) on photorealistic scenes.

Subject consistency: HunyuanVideo holds a character's clothing, hair, and face better across the clip. LTX-Video sometimes drifts at the 4-second mark in 5-second clips.

Hand rendering: Both models still produce malformed hands sometimes. HunyuanVideo's hands are right about 60% of the time; LTX's about 45%. Neither is solved.

Text in frame: Both produce gibberish. HunyuanVideo occasionally renders a single short word correctly; LTX never does.

Prompt adherence

How faithfully the model executes a complex prompt:

For commercial work where the prompt has to be honoured exactly (storyboards, client briefs), HunyuanVideo is meaningfully more reliable. For exploratory work where the model is allowed creative latitude, LTX is fine.

Audio

LTX-Video 2.3: Generates synced ambient audio — footsteps, room tone, wind, water, vehicle sounds. Quality is good for ambient, weak for music or speech. Audio is generated jointly with video, so it actually matches what's on screen.

HunyuanVideo: No audio. Silent MP4 output. If you need audio you'll need to add it in post or use a separate model.

For social media use where viewers watch with sound, LTX's native audio is a real advantage. For professional work that will get re-scored anyway, audio output doesn't change the calculus.

Licensing

LTX-Video 2.3: OpenRAIL-M licence. Commercial use allowed, but the licence has explicit content restrictions (no sexual content, no harassment, no weapon synthesis, etc.). Most commercial uses are fine; edge cases (adult content production, controversial political imagery) are not.

HunyuanVideo: Custom Tencent licence. Commercial use allowed for entities with <100M monthly active users (excluding EU/UK/Korea where commercial use requires explicit permission). The licence has its own restricted-use clauses similar to OpenRAIL.

Neither model has a clean Apache 2.0 licence. For commercial work where licence cleanliness matters most, Wan 2.1 is a better choice than either — though Wan's output quality is behind both LTX and HunyuanVideo.

Total cost per clip (real-world)

Using actual hardware we run or rent:

HunyuanVideo costs 6–10x more per clip than LTX-Video for ~30% better quality. That's the trade-off in concrete numbers.

What we use and why

LoreMotion's production service runs LTX-Video 2.3 because:

  1. The hardware bill is sustainable on owned RTX 3090s. HunyuanVideo would force us to cloud H100s and roughly 5x the per-clip cost.
  2. We can offer LTX for free with ad support. We couldn't offer HunyuanVideo for free.
  3. For typical free-tier prompts (single-subject scenes, social media content) LTX's quality is genuinely good enough.
  4. The audio support matters for users posting to TikTok / Reels / Shorts.

For users who want HunyuanVideo-tier quality, we offer Google Veo 3.1 and xAI Grok 3 as premium models. Both are roughly comparable to HunyuanVideo in output quality and don't require us to run the infrastructure.

Decision guide

Try LTX-Video 2.3 free with no signup at loremotion.com/generate. For HunyuanVideo specifically, fal.ai and Replicate both host it at around $0.45 per second of generated video.