Yes, RealVideo is an open source project released under the Apache 2.0 license. You can download the code and models from GitHub and Hugging Face for free.

Can I run RealVideo on my laptop?

Likely not for real time performance. The system is optimized for enterprise grade GPUs (like NVIDIA H100s) to achieve the speed necessary for live streaming, though "quantized" versions may eventually run on consumer hardware.

How is this different from HeyGen?

HeyGen generates pre-rendered videos (you type a script, wait a few minutes, and get a video). RealVideo is "conversational," meaning it generates the video while you are talking to it, allowing for live, back-and-forth interaction.

Who created RealVideo?

It was created by the Z.ai organization (zai org), with key contributions from researchers like Yuxuan Zhang and Ke Ning.

RealVideo

A Real Time Streaming Conversational System Powered by Autoregressive Diffusion.

From Z.ai (zai-org)

Founder: Z.ai Team (Contributors: Yuxuan Zhang, Ke Ning, et al.)

Video & Animation

Dec 2025

10K+

Free

Pricing Model

Free

Starting Price

$0/Month

About This AI

RealVideo is an open-source, real time streaming conversational video system developed by Z.ai.

Unlike standard video generators that take minutes to render a clip, RealVideo is designed for instant interaction it listens to text or audio input and generates a high fidelity video avatar response in real time (streaming).

It achieves this by combining Large Language Models (GLM-4.5) for the brain/voice and a highly optimized “Autoregressive Diffusion” model for the visuals, allowing for seamless, low-latency video chats with AI characters.

AI Art Image To Video LLM Text To Video Video Generator

Pricing

Pricing Model

Free

Starting Price

$0/Month

Key Features

Real Time Streaming Generates video frames on the fly via WebSockets, allowing for instant, fluid conversation without long waiting times.
Autoregressive Diffusion Uses a specialized diffusion transformer (DiT) that predicts the next video chunk based on the previous one, ensuring smooth motion.
Audio Driven Lip Sync Perfectly synchronizes the avatar's lip movements with the generated audio response from the LLM.
Silence Handling Intelligently injects "natural noise" and subtle motion during silent pauses so the avatar doesn't freeze robotically.
Modular Architecture Integrates with various LLMs (like GLM-4.5 AirX) and TTS engines, allowing developers to swap out the "brain" or "voice" of the system.
Multi-GPU Support: Optimized for parallel processing on high end GPUs (H100) to maintain real time frame rates.

Pros

Enables true "video chat" with AI, not just text chat.
Completely free and open source (Apache 2.0).
Solves the "latency" problem of previous video avatars.
High visual fidelity compared to older GAN based avatars.
"Silence handling" adds a layer of realism often missed by other tools.

Cons

Extremely high hardware requirements (Recommends H100/H200 GPUs for real time speed).
Complex setup requiring Python, Docker, and ML knowledge.
Currently focuses on "talking head" avatars rather than full body action.
No consumer facing app (strictly a developer framework).

Best for AI Engineers, Researchers, and companies building next-generation customer service bots or interactive virtual companions who need real time video responses.

FAQs

Is RealVideo free?
Yes, RealVideo is an open source project released under the Apache 2.0 license. You can download the code and models from GitHub and Hugging Face for free.
Can I run RealVideo on my laptop?
Likely not for real time performance. The system is optimized for enterprise grade GPUs (like NVIDIA H100s) to achieve the speed necessary for live streaming, though “quantized” versions may eventually run on consumer hardware.
How is this different from HeyGen?
HeyGen generates pre-rendered videos (you type a script, wait a few minutes, and get a video). RealVideo is “conversational,” meaning it generates the video while you are talking to it, allowing for live, back-and-forth interaction.
Who created RealVideo?
It was created by the Z.ai organization (zai org), with key contributions from researchers like Yuxuan Zhang and Ke Ning.