Open Source Text to Video 2026: Open-Sora (29k Stars) vs Wan 2.1 vs HunyuanVideo - Run on Your GPU

Sora remains closed and expensive, but open-source video models have caught up fast. Four serious open models now generate 5-15 second clips on a single consumer GPU - here is how to pick and run one.

## The short answer In 2026 the four serious open-source text-to-video models are **Open-Sora** (29,230 stars, Apache-2.0, HPC-AI Tech), **Wan 2.1** (16,717 stars, Apache-2.0, Alibaba), **HunyuanVideo** (12,399 stars, Tencent) and **LTX-Video** (10,793 stars, Apache-2.0, Lightricks). All generate 5-15 second clips locally; Wan 2.1 leads on quality-per-VRAM, LTX-Video leads on speed. ## Model comparison (real data, Aug 2026) | Model | Stars | Best for | VRAM (fp16) | |:------|:-----:|:---------|:------------| | Open-Sora | 29,230 | Community + tooling | 24GB (1.1) | | Wan 2.1 | 16,717 | Quality at 14B / 480p | 8GB (T2V-1.3B) | | HunyuanVideo | 12,399 | Long clips, motion | 24GB (13B) | | LTX-Video | 10,793 | Speed (real-time-ish) | 12GB (2B) | ## Getting started All four ship as Python packages with a ComfyUI workflow. The fastest path: install ComfyUI and drag in the model's workflow JSON from its GitHub repo - no coding required. For Wan 2.1 via CLI: ```bash pip install modelscope # or huggingface_hub # download Wan2.1-T2V-1.3B weights, then run generate.py python generate.py --task t2v-1.3B --size 480p --ckpt_dir ./Wan2.1-T2V-1.3B --prompt "a cat astronaut walking on the moon" ``` ## Practical tips - **Prompt style**: motion verbs + camera terms beat adjectives: "slow dolly-in, hand pouring coffee, steam rising" works far better than "beautiful coffee". - **Resolution**: 480p first, then upscale (pair with Real-ESRGAN for free). - **Frame count**: 81 frames at 24fps (~3.4s) is the sweet spot for coherence on consumer GPUs; longer clips drift. - **LoRA support**: Wan and Hunyuan have LoRA ecosystems for consistent characters/styles. ## FAQ **Can I run these on my gaming GPU?** Wan 2.1's 1.3B T2V model runs in ~8GB VRAM; the 14B models need 24GB or quantized versions. **Are generations commercially usable?** Apache-2.0 models (Open-Sora, Wan 2.1, LTX-Video) permit commercial use; check each license for attribution requirements. **How long are the clips?** 3-15 seconds depending on model and VRAM; longer coherent clips remain a research frontier. ## Related - [Flux Schnell vs Dev 2026](/post/flux-schnell-vs-dev-2026) - [AI Video Editing Tools 2026](/post/ai-video-editing-tools-20260802)