ComfyUI vs MoneyPrinterTurbo
Two of the top image and video, side by side: score, setup, license, activity and what each review found.
ComfyUI
Node-graph engine for diffusion image, video, audio and 3D models
MoneyPrinterTurbo
Generates short videos from a topic with script, footage, voice and subtitles
| What we compare | ComfyUI | MoneyPrinterTurbo |
|---|---|---|
| Score parts, out of 100 | ||
| Adoption | 97, widely used | 89, widely used |
| Freshness | 100, active | 100, active |
| Maintenance | 77, fair | 95, healthy |
| Easy to run | 50, easy | 33, some setup |
| Agent-ready | 30, minimal | 0, none |
| Facts from GitHub and the README | ||
| Stars | 136.9k | 129.6k |
| License | GPL-3.0 (copyleft) | MIT (permissive) |
| Last commit | Oct 2026 | Oct 2026 |
| Last release | Oct 2026 | Oct 2026 |
| Language | Not stated | Not stated |
| Docker | No | Yes |
| GPU | Optional | Not needed |
| arm64 or Apple Silicon | Mentioned | Not stated |
ComfyUI
Builds generation pipelines as a visual node graph and runs them locally for image (SD 1.5, SDXL, SD3.5, Flux.1 and Flux.2, Qwen Image), video (Wan 2.x, LTX-Video, HunyuanVideo), audio (ACE-Step, Stable Audio) and 3D (Hunyuan3D) models, with a local API and an App Mode that exposes a workflow as a simple UI. Runs on NVIDIA, AMD, Intel, Apple Silicon and Ascend. For professionals who want control over every parameter.
Who it is for: Visual professionals running diffusion models locally
Strengths
- Asynchronous weight streaming runs large models on 4 GB VRAM plus 8 GB RAM
- Workflows saved as JSON and recoverable from generated media metadata
- Runs fully offline; --offline disables the paid API nodes
- Loads checkpoints, separate diffusion models, VAEs, text encoders, LoRAs, ControlNets
Weaknesses
- Commits outside stable tags can break many custom nodes; stable releases roughly biweekly
- GPL-3.0 license constrains embedding in proprietary products
- NVIDIA 20-series and newer require PyTorch built with CUDA 13.0 or above
- Paid partner and API nodes stay on unless --offline or --disable-partner-nodes is set
- RAM ≥ 8 GB
- GPU optional
- Models: Stable Diffusion 1.5, SDXL, SD3.5, Flux.1 and Flux.2, Qwen Image and Qwen Image Edit, Wan 2.1/2.2, LTX-Video 2
MoneyPrinterTurbo
Takes a topic or keywords, writes a script with an LLM (OpenAI, Claude, Gemini, DeepSeek, Qwen, Ollama), pulls stock clips from Pexels, Pixabay or Coverr or generates them via video APIs, adds TTS narration (Edge TTS needs no key; Azure, ElevenLabs, Kokoro), subtitles and music, then renders 9:16, 16:9 or 1:1 videos. Usable through a WebUI, REST API, CLI or an agent skill. For creators automating short-form content.
Who it is for: Creators automating short-form video production
Strengths
- Edge TTS works without any API key; many other TTS and LLM providers supported
- Four entry points: WebUI, API, CLI and an agent skill; batch generation and task history
- Runs on CPU; minimum spec is 4 cores and 4 GB RAM
- One-click publishing to TikTok, Instagram and YouTube Shorts
Weaknesses
- README is Chinese first; the English version is a separate file
- Default flow needs external LLM and stock-footage API keys
- README carries heavy sponsor advertising and affiliate links
- Local faster-whisper transcription and batch runs want a 4 GB+ VRAM GPU
- RAM ≥ 4 GB
- no GPU
- Docker + Compose
- Needs LLM API (OpenAI-compatible) or Ollama, Stock footage API (Pexels, Pixabay, Coverr) or a video generation API
- Models: OpenAI, Anthropic Claude, Google Gemini, DeepSeek, Qwen (DashScope)