Open-weight video generation made the most dramatic leap of any AI category in 2025-2026. Wan 2.1 (Alibaba), HunyuanVideo (Tencent), Mochi-1 (Genmo), LTX-Video (Lightricks), Open-Sora, CogVideoX (Zhipu), and Allegro (Rhymes AI) all approached or matched Sora quality at meaningfully lower deployment cost. The Sora consumer shutdown on 26 April 2026 pushed creative-industry attention to open-weight alternatives. This page consolidates the leaderboard.
Key Findings
- Wan 2.1 from Alibaba (released early 2026) leads the open-weight video generation leaderboard with strong text-to-video, image-to-video, and video-to-video capabilities at up to 1080p output and 5-second duration.
- HunyuanVideo from Tencent (released late 2024, updated through 2025-2026) is the largest open-weight video model at approximately 13B parameters and produces 5-second 1280x720 videos with strong motion quality.
- Mochi-1 from Genmo, released October 2024, was the first open-weight video model to challenge Sora and remains widely deployed in production via the Apache 2.0 license.
- LTX-Video from Lightricks (released late 2024) is the fastest open-weight video model, generating 5 seconds of 768x512 video in under 4 seconds on a single H100.
- Open-Sora (HPC-AI Tech) is the reference open-source rebuild of Sora; quality lags the leading models but the training code and data are public, making it the standard for academic video research.
Open-Weight Video Generation Model Comparison (May 2026)
| Model | Parameters | Max Length | Max Resolution | License |
|---|---|---|---|---|
| Wan 2.1 (T2V-14B) | ~14B | 5 seconds (T2V), longer with I2V chaining | 1080p | Apache 2.0 |
| Wan 2.1 (T2V-1.3B) | ~1.3B | 5 seconds | 720p | Apache 2.0 |
| HunyuanVideo | ~13B | 5 seconds | 1280x720 | Tencent Hunyuan Community |
| Mochi-1 | ~10B | 5 seconds (extendable) | 848x480 | Apache 2.0 |
| LTX-Video | ~2B | 5 seconds | 768x512 | OpenRAIL-M |
| CogVideoX-5B | ~5B | 6 seconds | 720x480 | CogVideoX License (Permissive) |
| CogVideoX-1.5-5B | ~5B | 10 seconds | 1360x768 | CogVideoX License |
| Allegro | ~3B | 6 seconds | 720x320 | Apache 2.0 |
| Open-Sora 2.0 | ~varies | up to 15 seconds | 720p | MIT |
| Pyramid Flow | ~2B | 10 seconds | 768x768 | MIT |
| Stable Video Diffusion XT | ~1.7B | 4 seconds | 1024x576 | Stability Community License |
| EasyAnimate v5 | ~varies | 6 seconds | 720p | Apache 2.0 |
Quality Benchmarks (VBench v2 May 2026)
| Model | VBench v2 Score |
|---|---|
| Wan 2.1 (T2V-14B) | ~85.2 |
| HunyuanVideo | ~83.4 |
| Mochi-1 | ~80.7 |
| CogVideoX-1.5-5B | ~80.5 |
| LTX-Video | ~78.4 |
| Sora (pre-shutdown reference) | ~85.4 |
| Google Veo 3 | ~87.2 |
| Kling 2 | ~85.8 |
Latency and Hardware Requirements
| Model | Time for 5s 720p Video (H100) | VRAM Required |
|---|---|---|
| LTX-Video | ~4 seconds | ~24 GB |
| Wan 2.1 (1.3B) | ~28 seconds | ~24 GB |
| Wan 2.1 (14B) | ~180 seconds | ~80 GB |
| HunyuanVideo | ~170 seconds | ~80 GB |
| Mochi-1 | ~120 seconds | ~80 GB |
| CogVideoX-1.5-5B | ~85 seconds | ~32 GB |
| Allegro | ~60 seconds | ~32 GB |
Use Case Recommendations
| Use Case | Recommended Model |
|---|---|
| Top quality general purpose | Wan 2.1 (14B) |
| Permissive commercial deployment | Wan 2.1 (Apache 2.0), Mochi-1 (Apache 2.0), Allegro (Apache 2.0) |
| Fast iteration / preview | LTX-Video or Wan 2.1 (1.3B) |
| Long-form video (10+ sec) | CogVideoX-1.5-5B or Open-Sora 2.0 |
| Consumer GPU (24 GB VRAM) | LTX-Video or Wan 2.1 (1.3B) |
| Image-to-video | Wan 2.1 I2V or Stable Video Diffusion XT |
| Research and academic reproducibility | Open-Sora 2.0 or Pyramid Flow |
Brand Visibility Implications
Video generation is one of the fastest-growing creative AI procurement categories in 2026. AI assistant queries about "best open-source video generator", "Wan 2.1 vs HunyuanVideo", "alternative to Sora", and similar terms drive procurement-research traffic from advertising, gaming, e-commerce, and film production teams. Brands selling AI video platforms, video editing tools, asset generation services, and creative AI products face strong AI-mediated discovery surface for this category.
Methodology
Benchmark data compiled from VBench leaderboard, primary model card disclosures, and community comparisons through 23 May 2026. Latency measured on a single H100 with FP16 inference. Updated quarterly.
How Presenc AI Helps
Presenc AI monitors brand visibility on video generation queries across ChatGPT, Claude, Gemini, and Perplexity. For AI video platforms, video editing brands, asset generation vendors, and creative AI products, the platform identifies the prompts driving procurement-research traffic and the gaps where new content unlocks share of voice.