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Best text-to-video models to run locally on a 16GB graphics card

A leaderboard of the best text-to-video models you can run locally on a 16GB graphics card (with 32GB of system RAM). HunyuanVideo 1.5 is #1 right now, followed by Wan 2.2 A14B and Wan 2.1 14B. Models are ranked on human votes and video generation tests. Each model shows the download that fits and the command to run it.

30 models · scores combine 25 benchmarks · updated how it works · find a leaderboard · benchmark your machine

Scores use reviewed text to video evaluations only. Compare scores within this task. Models without task measurements are excluded.

Models for 32GB RAM · 16GB graphics card → ~16GB fast · local only · reset
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Score vs memory to run

#modeltask score↓where↓speed↓RAM↓get itsources
36HunyuanVideo 1.5 · fp16 720p T2V + Qwen2.5-VL q8_0 (sd.cpp) Tencent54±2local (slow)~34GBhow to run › LMArena leaderboard datasetCosmos 3: Omnimodal World Models for Physical AI (arXiv:2606.02800v4)WorldJen: An End-to-End Multi-Dimensional Benchmark for Generative Video ModelsSci-VBench: Evaluating Knowledge- and Reasoning-Intensive Video Generation in Science DomainsHumanScore: Benchmarking Human Motions in Generated Videos
42Wan 2.2 A14B · gguf-q4_k_m ×2 experts + umt5 q8_0 (sd.cpp) Alibaba52±2local (slow)~31GBhow to run › LMArena leaderboard datasetCosmos 3: Omnimodal World Models for Physical AI (arXiv:2606.02800v4)WorldJen: An End-to-End Multi-Dimensional Benchmark for Generative Video ModelsVideoVerse: Does Your T2V Generator Have World Model Capability to Synthesize Videos?
44Wan 2.1 14B · bf16 Alibaba50±2local (slow)~34GBhow to run › VideoPhy / VideoPhy-2 official repository leaderboardsSkyReels-V2: Infinite-length Film Generative ModelCosmos 3: Omnimodal World Models for Physical AI (arXiv:2606.02800v4)T2VPhysBench: A First-Principles Benchmark for Physical Consistency in Text-to-Video GenerationAlibaba Wan technical report (arXiv:2503.20314v2), VBench table (own models)
46Kandinsky 5.0 T2V Lite · bf16 Sber49±2*local (slow)~29GBhow to run › LMArena leaderboard dataset
48Cosmos-1.0-Diffusion-7B-Text2World · bf16 NVIDIA48±3local (slow)~30GBhow to run › VideoPhy / VideoPhy-2 official repository leaderboardsCosmos World Foundation Model Platform for Physical AI (arXiv:2501.03575v3)
52Wan 2.2 TI2V 5B · bf16 Alibaba47±4local~13GBhow to run › Cosmos 3: Omnimodal World Models for Physical AI (arXiv:2606.02800v4)VABench: A Comprehensive Benchmark for Audio-Video Generation (arXiv:2512.09299v2)Sci-VBench: Evaluating Knowledge- and Reasoning-Intensive Video Generation in Science Domains
53CogVideoX-5B · bf16 Zhipu AI (THUDM)47±2local~13GBhow to run › VideoPhy / VideoPhy-2 official repository leaderboardsGenAI-Arena (TIGER-Lab) text-to-video leaderboardHumanScore: Benchmarking Human Motions in Generated Videos
57Pyramid Flow (SD3) · bf16 Peking University / Kuaishou45±3*local~8GBhow to run › GenAI-Arena (TIGER-Lab) text-to-video leaderboard
58T2V-Turbo-v2 · fp32 UC Santa Barbara45±7*†local~9.4GBhow to run › T2V-Turbo-v2: Enhancing Video Generation Model Post-Training through Data, Reward, and Conditional Guidance Design (arXiv 2410.05677v3)
61Wan 2.1 T2V 1.3B · fp16 + umt5 q8_0 (sd.cpp) Alibaba43±4local~12GBhow to run › WorldJen: An End-to-End Multi-Dimensional Benchmark for Generative Video ModelsAlibaba Wan technical report (arXiv:2503.20314v2), VBench table (own models)Training-Free Efficient Video Generation via Dynamic Token Carving
62LTX-2.3 · gguf-ud-q4_k_m 22B dev + Gemma 3 12B q4 (sd.cpp) Lightricks43±7*local (slow)~34GBhow to run › Sci-VBench: Evaluating Knowledge- and Reasoning-Intensive Video Generation in Science Domains
63Mochi 1 · default Genmo42±2local~6.5GBhow to run › LMArena leaderboard datasetGenAI-Arena (TIGER-Lab) text-to-video leaderboardVideoPhy / VideoPhy-2 official repository leaderboardsT2VPhysBench: A First-Principles Benchmark for Physical Consistency in Text-to-Video Generation
65HunyuanVideo · bf16 Tencent41±3local (slow)~32GBhow to run › VideoPhy / VideoPhy-2 official repository leaderboardsSkyReels-V2: Infinite-length Film Generative ModelVideoVerse: Does Your T2V Generator Have World Model Capability to Synthesize Videos?Training-Free Efficient Video Generation via Dynamic Token Carving
68T2V-Turbo (VC2) · fp32 UC Santa Barbara41±3†local~9.4GBhow to run › GenAI-Arena (TIGER-Lab) text-to-video leaderboardT2V-Turbo-v2: Enhancing Video Generation Model Post-Training through Data, Reward, and Conditional Guidance Design (arXiv 2410.05677v3)T2V-Turbo: Breaking the Quality Bottleneck of Video Consistency Model with Mixed Reward Feedback (arXiv:2405.18750v2)
70CogVideoX-2B · fp16 Zhipu AI (THUDM)39±2local~5.3GBhow to run › VideoPhy / VideoPhy-2 official repository leaderboardsGenAI-Arena (TIGER-Lab) text-to-video leaderboardChronoMagic-Bench: A Benchmark for Metamorphic Evaluation of Text-to-Time-lapse Video Generation
71CogVideoX1.5-5B · bf16 + sequential CPU offload Zhipu AI (THUDM)38±3local (slow)~38GBhow to run › LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation (AIGVE-60K)VideoVerse: Does Your T2V Generator Have World Model Capability to Synthesize Videos?SkyReels-V2: Infinite-length Film Generative ModelSci-VBench: Evaluating Knowledge- and Reasoning-Intensive Video Generation in Science Domains
72Allegro · bf16 Rhymes AI38±2local~9.3GBhow to run › LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation (AIGVE-60K)GenAI-Arena (TIGER-Lab) text-to-video leaderboard
73VideoCrafter2 · fp32 Tencent AI Lab37±2local~9.4GBhow to run › VideoPhy / VideoPhy-2 official repository leaderboardsLOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation (AIGVE-60K)GenAI-Arena (TIGER-Lab) text-to-video leaderboardChronoMagic-Bench: A Benchmark for Metamorphic Evaluation of Text-to-Time-lapse Video Generation
76LaVie (base T2V) · fp16 Shanghai AI Lab (Vchitect)35±2local~4.9GBhow to run › LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation (AIGVE-60K)VideoPhy / VideoPhy-2 official repository leaderboardsGenAI-Arena (TIGER-Lab) text-to-video leaderboardChronoMagic-Bench: A Benchmark for Metamorphic Evaluation of Text-to-Time-lapse Video Generation
77LTX-Video 0.9 (2B) · bf16 Lightricks35±3*local~5.3GBhow to run › GenAI-Arena (TIGER-Lab) text-to-video leaderboard
79Open-Sora 1.1 · bf16 HPC-AI Tech34±6*local~14GBhow to run › ChronoMagic-Bench: A Benchmark for Metamorphic Evaluation of Text-to-Time-lapse Video Generation
81NOVA-0.6B T2V · fp16 BAAI32±3*local~9.3GBhow to run › LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation (AIGVE-60K)
82Hotshot-XL · fp16 Hotshot31±2local~10GBhow to run › EvalCrafter: original 2023 text-to-video evaluationsLOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation (AIGVE-60K)
85ZeroScope v2 576w · fp16 cerspense30±3local~7.9GBhow to run › VideoPhy / VideoPhy-2 official repository leaderboardsChronoMagic-Bench: A Benchmark for Metamorphic Evaluation of Text-to-Time-lapse Video GenerationFETV: A Benchmark for Fine-Grained Evaluation of Open-Domain Text-to-Video Generation (arXiv:2311.01813v3)
87VideoCrafter1 T2V · official script (checkpoint as stored) Tencent AI Lab / HKUST29±2local~8.1GBhow to run › EvalCrafter: original 2023 text-to-video evaluations
90ModelScope T2V 1.7B · fp16 Alibaba DAMO Academy28±2local~4.6GBhow to run › EvalCrafter: original 2023 text-to-video evaluationsLOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation (AIGVE-60K)GenAI-Arena (TIGER-Lab) text-to-video leaderboardChronoMagic-Bench: A Benchmark for Metamorphic Evaluation of Text-to-Time-lapse Video GenerationFETV: A Benchmark for Fine-Grained Evaluation of Open-Domain Text-to-Video Generation (arXiv:2311.01813v3)
91LVDM (text-to-video) · fp32 HKUST / Tencent AI Lab28±3*local~6.1GBhow to run › LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation (AIGVE-60K)
93ZeroScope v2 XL (576w → XL pipeline) · fp16 + model CPU offload (576w base, then XL vid2vid) cerspense27±2local~15GBhow to run › EvalCrafter: original 2023 text-to-video evaluations
—Kandinsky 6.0 Video Lite · bf16 + model CPU offload Sbernot yet calibratedlocal (slow)~34GBhow to run › Kandinsky 6.0 Video: Foundation Models for Synchronized Video and Audio Generation (arXiv:2610.05608v1)
—LTX-2.5 · fp8 Lightricksnot yet calibratedlocal~14GBhow to run › Kandinsky 6.0 Video: Foundation Models for Synchronized Video and Audio Generation (arXiv:2610.05608v1)

+ 67 more don't fit your machine or budget · show them

97 of 97 catalogue models listed here · sources and licences

* new or thinly tested: ranked on too few benchmark results · † only the maker’s own numbers so far · ~RAM is estimated; full context may need more memory