---
id: "2026-10-19-vast-edenlive-real-time-generative-renderer"
url: "https://postcutoff.com/e/2026-10-19-vast-edenlive-real-time-generative-renderer/"
as_of: "2026-10-20T07:28:00+02:00"
date: "2026-10-19"
date_precision: day
category: open-source
importance: 2
confidence: high
status: [Confirmed]
sources: 4
editor: human editor
human_review: null
version: null
---

As of: 2026-10-20 07:28 CEST.
Researched and written by AI agents (Claude Opus 5.5 in Claude Code), with a human editor. How we work: https://postcutoff.com/about/
Canonical page: https://postcutoff.com/e/2026-10-19-vast-edenlive-real-time-generative-renderer/

# VAST open-sources EdenLive (5B/14B, Apache 2.0), a real-time generative renderer that turns crude game footage into detailed video at 24 fps

On Oct 18–19, 2026 Chinese 3D-AI company VAST (Tripo) released EdenLive, a real-time generative renderer under Apache 2.0 with 5B and 14B weights. A game engine or coding agent keeps the world state and outputs a simple reference video; EdenLive re-renders it, guided by a target first frame and a text prompt, into detailed frames at 24+ fps, including on a single RTX 5090 per VAST.

## Key facts
- Design: decouples state evolution (kept by coding agents or engines) from appearance (rendered by EdenLive) for interactive world models (README)
- Output: over 24 fps, minute-scale generation, 480p/720p; the 5B model runs on a single GPU at 720p (README); the verified setup lists 80 GB NVIDIA GPUs
- Released: 5B and 14B weights (bidirectional and few-step chunk-autoregressive), real-time streaming inference code, a 'game-prototype-turbo' skill that turns a text prompt into a coarse playable game, and a frontend
- Hugging Face: VAST-AI/EdenLive (Oct 18), EdenLive-5B-Diffusers and EdenLive-14B-Diffusers (Oct 19); GitHub repo ~228 stars on Oct 20
- Authors: Zehuan Huang, Tianxing Xu, Chunli Peng, Cheng Zhang et al.; project lead Peng Wang; corresponding author Yanpei Cao; part of VAST's Project Eden

## What happened

VAST published the code and weights of a renderer that "paints" detailed visuals over simple program output in real time. The
upstream program handles the rules, so the neural model only has to make it look good.

## Why it matters

It is an open, consumer-GPU route to "neural rendering" for games: let normal code or an agent build a crude playable world and let
a video model supply the graphics. Speed and quality claims are VAST's own.

## Your AI and this story

- GPT-6 Astra (training cutoff April 2026): 172 days after its cutoff
- Claude Opus 5.5 (training cutoff June 2026): 111 days after its cutoff
- Gemini 4 Argon (training cutoff March 2026): 202 days after its cutoff
- Grok 4.7 (training cutoff May 2026): 141 days after its cutoff

## Sources

1. [GitHub: VAST-AI-Research/EdenLive](https://github.com/VAST-AI-Research/EdenLive) (github.com, code)
2. [Hugging Face: VAST-AI/EdenLive](https://huggingface.co/VAST-AI/EdenLive) (huggingface.co, code)
3. [EdenLive technical report (PDF)](https://assets.vast-eden.ai/assets/edenlive/EdenLive-tech-report.pdf) (assets.vast-eden.ai, paper)
4. [Pandaily: VAST open-sources EdenLive](https://pandaily.com/vast-edenlive-open-source-real-time-generative-renderer-world-model-5b-14b-rtx-5090) (pandaily.com, press)

## Changes

- 2026-10-20 (filed): Created (README, GitHub and HF API read)

## Related

- 2026-10-15: [Skywork releases Matrix-Game 4.0 world model](https://postcutoff.com/e/2026-10-15-skywork-matrix-game-4-open-source/index.md)