VideoMAE Base is Meta's masked autoencoder pre-trained on video — a powerful video representation learning model that serves as a foundation for downstream video understanding tasks.
VideoMAE Base is an AI model released 2022 by facebook, a leading organization in large language model research. Meta's VideoMAE — masked autoencoder for video understanding. Foundation for action recognition and video classification tasks. With a large number of parameters and a a large context window context window, VideoMAE Base 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.
VideoMAE Base uses a dense transformer architecture with a large number of parameters 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. facebook'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 VideoMAE Base's characteristic balance of capability, helpfulness, and safety.
As of 2026-10-16, VideoMAE Base by facebook demonstrates measurable performance on standard AI evaluation benchmarks. On Kinetics-400 Top-1 — which measures model performance on specialized evaluation tasks — it achieves 79.9%. These scores place VideoMAE Base 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 VideoMAE Base are: Self-supervised video pre-training — learns from unlabeled video data; Strong Kinetics-400 performance at base scale; CC-BY-NC 4.0. These make it particularly well-suited for Fine-tuning on custom video datasets, Research on video representation learning. Users working on complex, multi-step problems benefit most from VideoMAE Base's ability to maintain coherence across long inputs and produce structured, verifiable outputs.
Like all current AI systems, VideoMAE Base has limitations: Research model; Classification only. For production deployments, validating outputs against authoritative sources — especially for domain-specific or time-sensitive information — remains best practice. facebook continues to improve VideoMAE Base through ongoing research.
VideoMAE Base 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 VideoMAE Base accessible to students, researchers, developers, and early-stage teams globally.
As of 2026-10-16, VideoMAE Base by facebook demonstrates measurable performance on standard AI evaluation benchmarks. On Kinetics-400 Top-1 — which measures model performance on specialized evaluation tasks — it achieves 79.9%. These scores place VideoMAE Base 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.
Video Masked Autoencoders (VideoMAE) — self-supervised video representation learning
The training pipeline for VideoMAE Base 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. facebook's research team — based in China — has optimized VideoMAE Base for the specific capability profile described above.
Inference efficiency: VideoMAE Base is designed to deliver quality outputs at practical serving speeds. Its context capacity supports complex multi-turn conversations without quality degradation.
Getting started with VideoMAE Base on LITHOVEX AI takes under two minutes. Follow these steps:
For best results with VideoMAE Base: provide specific, context-rich prompts; include examples when generating code; specify output format when structure matters; break complex tasks into focused sub-questions.
Video representation learning for custom fine-tuning
Foundation for video classification on new domains
Research into self-supervised video understanding
Video feature extraction for downstream tasks
Transfer learning for specialized video classification
facebook 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. facebook'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: 2004, headquartered in China.
VideoMAE Base by facebook 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 VideoMAE Base 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.
VideoMAE Base is released under CC BY-NC 4.0, which means you can download and run it on your own hardware. Below are the quickest ways to get started.
LITHOVEX AI runs VideoMAE Base on cloud infrastructure, so you can use it instantly in your browser without downloading anything, configuring drivers, or managing VRAM. Create a free account and start in under 60 seconds.
VideoMAE's self-supervised pre-training approach makes it broadly valuable globally because it learns rich video representations without expensive labeled data — important for markets and domains where labeled video datasets are difficult to obtain.
VideoMAE Base by facebook has the following version history and notable updates:
For the complete changelog and latest release notes, visit the official facebook model page.