Use ModelScope Text→Video 1.7B for Free

ModelScope Text→Video 1.7B is an AI model released 2023 by ali-vilab, a leading organization in large language model research. Alibaba's ModelScope T2V 1.7B — generates short video clips from text prompts. The original open-source text-to-video model. With 1.7B and a a large context window context window, ModelScope Text→Video 1.7B is designed to excel across a range of demanding tasks — from software engineering and mathematical problem-solving to multilingual content generation and long-document analysis.

ModelScope Text→Video 1.7B uses a dense transformer architecture with 1.7B of parameters, all of which are active for every input token. Dense architectures provide predictable, consistent behavior across diverse task types — there are no "cold" experts to warm up, and quality is uniform across prompts. ali-vilab's training pipeline combined large-scale pretraining on a large-scale multilingual pretraining dataset with supervised fine-tuning and alignment techniques (RLHF or DPO), producing ModelScope Text→Video 1.7B's characteristic balance of capability, helpfulness, and safety.

As of 2026-10-16, ModelScope Text→Video 1.7B by ali-vilab demonstrates measurable performance on standard AI evaluation benchmarks. On FVD (UCF-101) — which measures model performance on specialized evaluation tasks — it achieves 292.4. These scores place ModelScope Text→Video 1.7B — at 1.7B of parameters — in a competitive position within its model class. Note that benchmark scores reflect controlled evaluation conditions; real-world performance varies by task, prompt design, and domain specificity.

The primary strengths of ModelScope Text→Video 1.7B are: One of the first open text-to-video models; Apache 2.0 — free commercial use. These make it particularly well-suited for Research on text-to-video architectures, Quick video concept prototyping. Users working on complex, multi-step problems benefit most from ModelScope Text→Video 1.7B's ability to maintain coherence across long inputs and produce structured, verifiable outputs.

Like all current AI systems, ModelScope Text→Video 1.7B has limitations: Short clips only (4-8 seconds); Quality significantly below commercial models. For production deployments, validating outputs against authoritative sources — especially for domain-specific or time-sensitive information — remains best practice. ali-vilab continues to improve ModelScope Text→Video 1.7B through ongoing research.

ModelScope Text→Video 1.7B is available on LITHOVEX AI with a free account. Unlike direct API access — which requires billing setup, API key management, and per-token charges — LITHOVEX AI provides a seamless browser interface with no setup required, making ModelScope Text→Video 1.7B accessible to students, researchers, developers, and early-stage teams globally.

As of 2026-10-16, ModelScope Text→Video 1.7B by ali-vilab demonstrates measurable performance on standard AI evaluation benchmarks. On FVD (UCF-101) — which measures model performance on specialized evaluation tasks — it achieves 292.4. These scores place ModelScope Text→Video 1.7B — at 1.7B of parameters — in a competitive position within its model class. Note that benchmark scores reflect controlled evaluation conditions; real-world performance varies by task, prompt design, and domain specificity.

Diffusion-based video generation, 1.7B parameters

The training pipeline for ModelScope Text→Video 1.7B involves multiple stages: large-scale pretraining on diverse multilingual text and code corpora to develop broad world knowledge, followed by supervised fine-tuning on instruction-response pairs, and alignment techniques such as RLHF or DPO. Each stage refines the model's helpfulness, accuracy, and safety. ali-vilab's research team — based in China — has optimized ModelScope Text→Video 1.7B for the specific capability profile described above.

Inference efficiency: ModelScope Text→Video 1.7B at 1.7B is designed to deliver quality outputs at practical serving speeds. Its context capacity supports complex multi-turn conversations without quality degradation.

Getting started with ModelScope Text→Video 1.7B on LITHOVEX AI takes under two minutes. Follow these steps:

For best results with ModelScope Text→Video 1.7B: provide specific, context-rich prompts; include examples when generating code; specify output format when structure matters; break complex tasks into focused sub-questions.

ali-vilab is a leading organization in AI research and large language model development. Their team has built expertise across natural language processing, model architecture design, and alignment research. ali-vilab's models are used by researchers, developers, and enterprises worldwide. Their commitment to advancing AI capability while maintaining responsible deployment practices has made them a respected contributor to the global AI ecosystem. The organization continues to publish research and release models that push the boundaries of what AI systems can achieve.

Founded: 2022, headquartered in China.

Visit the official ali-vilab website →

ModelScope Text→Video 1.7B by ali-vilab competes in a field with several strong alternatives. Below is a detailed side-by-side comparison against commonly listed alternatives, using benchmark data and capability profiles in the catalog.

Both ModelScope Text→Video 1.7B and the models above are available free on LITHOVEX AI — test them side by side on your real tasks before committing to a subscription with any provider.

ModelScope Text→Video 1.7B is released under Apache 2.0, which means you can download and run it on your own hardware. Below are the quickest ways to get started.

Text-to-video generation is transforming global creative industries — advertising agencies, game developers, social media creators, and filmmakers worldwide are experimenting with AI video. ModelScope 1.7B was an early accessible open model that demonstrated the concept to the global developer community.

ModelScope Text→Video 1.7B by ali-vilab has the following version history and notable updates:

For the complete changelog and latest release notes, visit the official ali-vilab model page.