LTX 2.3 vs HunyuanVideo vs Wan2.2: Which Open-Source Video Model Should You Use in 2026?

The open-source video generation landscape in 2026 has matured fast. Three models now dominate local inference pipelines: LTX 2.3 from Lightricks, HunyuanVideo from Tencent, and Wan2.2 from Alibaba. Each reflects a different philosophy — and choosing the wrong one for your workflow costs time and VRAM.

This comparison cuts through the noise with practical, hardware-grounded analysis.

At a Glance

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LTX 2.3 — The Multimodal Generalist

LTX 2.3 is the most ambitious of the three. Built on a Diffusion Transformer architecture with 22 billion parameters, it's the only model in this comparison that handles audio and video simultaneously — not as a post-processing step, but natively during generation.

What it does well

• Native audio sync: Audio is generated alongside video in the same pass, keeping lip movement and ambient sound naturally aligned
• New high-fidelity VAE: The rebuilt taeltx2_3.safetensors encoder produces noticeably sharper textures and edges compared to LTX 2.0/2.1 — fabric weaves, hairlines, and chrome surfaces hold detail across frames
• Two-stage upscaling: Spatial (x1.5, x2) and temporal upscalers let you generate at half resolution for speed, then upscale latents — a practical VRAM management strategy
• Portrait 9:16 native: No hacks required for vertical video, important for social content
• FP8 variants for 16GB: Kijai's quantized checkpoints make it accessible on RTX 4080/4090 class cards

Limitations

• Requires Gemma 3 12B text encoder (~13GB additional) — total disk footprint is large
• Strict frame count math (multiples of 8 + 1: 25, 121, 241...) and resolution rules (divisible by 32)
• LoRAs from LTX 2.0/2.1 are not compatible — you need to retrain or find LTX 2.3-specific weights

Best for

Creators who need audio-video sync, portrait format, or are building production pipelines on consumer GPUs (16–24GB VRAM).

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HunyuanVideo — The Texture Realism Champion

HunyuanVideo from Tencent was one of the first open-source models to demonstrate that local inference could approach closed-source quality. With 13B+ parameters and strong Diffusers integration, it became the most-discussed model in the ComfyUI community through early 2025.

What it does well

• Motion consistency: Backgrounds stay coherent across frames; fine details like snowflake patterns and fabric textures hold together better than most models at its release
• Ecosystem maturity: Deep Diffusers and ComfyUI integration, multiple popular fine-tunes (SkyReels V1 trained on film/TV clips)
• FP8 quantization: Official FP8 weights reduce memory pressure, though still demanding

Limitations

• High VRAM floor: Even with FP8, practical use requires 24GB+ for reasonable resolution and duration — places it out of reach for RTX 4080 users
• Photorealism bias: Stylistic prompts (anime, illustration, painterly) often default toward photorealism, limiting creative control
• No native audio: Audio must be added separately in post

Best for

Users with 24GB+ VRAM (RTX 3090, 4090, A6000) who prioritize texture realism and motion consistency over audio or stylistic flexibility.

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Wan2.2 — The Accessible Entry Point

Wan2.2 from Alibaba takes a different approach: two model sizes (5B and 14B) targeting a much wider hardware range. The 5B variant runs on 8GB VRAM, making it the only model here accessible on mid-range consumer GPUs.

What it does well

• Low VRAM entry: 5B model runs on 8–12GB cards — RTX 3070, 4070, and similar
• Portrait support: Native vertical video generation
• Speed: Smaller parameter count means faster inference, especially for iteration and prototyping
• Good prompt adherence: Strong text-to-video alignment for straightforward prompts

Limitations

• Quality ceiling: The 5B model shows more temporal artifacts and texture drift than LTX 2.3 or HunyuanVideo at equivalent settings
• 14B still needs 16GB+: The higher-quality variant has similar VRAM requirements to LTX 2.3 FP8, but without the audio capability
• No native audio: Like HunyuanVideo, audio is a separate step

Best for

Developers prototyping on mid-range hardware, or workflows where iteration speed matters more than final output quality.

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Head-to-Head: Key Decision Points

VRAM-constrained (8–16GB)

Wan2.2 5B for quick iteration → LTX 2.3 FP8 for final output. The FP8 v3 distilled checkpoint from Kijai runs on 16GB with the two-stage pipeline.

Audio-video sync required

LTX 2.3 is the only option. Neither HunyuanVideo nor Wan2.2 generate audio natively.

Maximum visual fidelity (24GB+)

HunyuanVideo still holds an edge for photorealistic texture consistency, particularly with fine-tuned variants like SkyReels. LTX 2.3 is competitive but the VAE architecture difference is noticeable in close-up shots.

ComfyUI workflow integration

All three have official nodes. LTX 2.3 requires the most setup (Gemma encoder, specific node versions, frame math), but the official workflows are well-documented.

LoRA fine-tuning

HunyuanVideo has the most mature fine-tuning ecosystem as of April 2026. LTX 2.3 LoRA support exists but the model change from 2.0 to 2.3 broke existing weights — new community LoRAs are still catching up.

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Which Should You Download?

If you're starting fresh in April 2026:

1. 16GB VRAM → Start with LTX 2.3 FP8 v3 + taeltx2_3.safetensors. Best capability-per-VRAM ratio.
2. 24GB+ VRAM → Try both LTX 2.3 full and HunyuanVideo. Use LTX 2.3 for audio projects, HunyuanVideo for photorealistic close-ups.
3. Under 16GB → Wan2.2 5B for prototyping, then render finals on a cloud GPU or upgrade.

All three models are free and open-source under Apache 2.0. You can download LTX 2.3 model files with direct links on our Models page.

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Sources

• Top open-source text-to-video AI models — Modal
• AI Video Generation in 2026: A Deep Technical Dissection — Spaisee
• LTX-2.3: What's New in Lightricks' 22B Video Model — WaveSpeedAI
• Open-Source Video Models Now Production-Ready — The Next Gen Tech Insider
• LTX-2.3 and LTX Desktop: Production-Ready Engine — ltx.io
• LTX-2 to LTX-2.3 Upgrade: Compatibility, LoRA Breaks & Migration — WaveSpeedAI