Leonardo AI alternatives: 5 open-source picks
Leonardo AI costs $12/mo — $144 a year. These 5 alternatives replace it for $0, led by ComfyUI, InvokeAI and SwarmUI. All 5 are open source. License, stars and last commit checked by hand on 2026-08-29. No trials, no crippled tiers.
The canonical local workflow engine, complete with saved graphs, queues and every knob Leonardo hides.
licenseGPL-3.0
runsyour machine or their cloud
installWindows or macOS desktop installer, Windows portable archive, or manual Python install on Windows, macOS, or Linux
enginesLocal and downloadable image, video, audio, 3D, and text models including Stable Diffusion/SDXL/SD3.5, FLUX, Wan, LTX-Video, HunyuanVideo, CogVideoX, and Mochi; optional API nodes connect to hosted providers
dataModels, inputs, outputs, and workflow JSON live in the local ComfyUI data tree; generated media can embed workflow and seed metadata, while API nodes transmit selected inputs to their provider
the catch vs Leonardo AIIt has deeper parameter control, but no Leonardo-style hosted asset library, team workspace, polished model-training flow, or instant cloud capacity.
setupA compatible GPU, enough VRAM and disk for multi-gigabyte models, and a working model/workflow must be chosen before useful output appears
facts verified 2026-08-10
Organized boards, rich metadata, masks and reusable workflows for local and API-backed image models.
licenseApache-2.0
runsyour machine or their cloud
installInstall through Invoke's launcher on Windows, macOS, or Linux, or deploy the documented Docker setup
enginesLocal models including Stable Diffusion, SDXL, SD3.5, FLUX, CogView, Z-Image, Krea, Anima, Qwen Image, Ideogram, and segmentation models; selected hosted models such as GPT Image, Gemini/Nano Banana, and Wan use API credentials
dataModels, images, boards, canvas state, prompts, metadata, and a SQLite database live in the local Invoke data directory; API-backed nodes send only the selected prompt and image context to their provider
the catch vs Leonardo AIIt has excellent boards and workflows, but team collaboration, hosted asset sharing, and Leonardo's turnkey training and generation infrastructure are not included.
setupThe launcher is straightforward, but the user still needs a compatible GPU, a large model download, and sometimes a gated-model login or provider API key
facts verified 2026-08-10
A clean Generate tab, history, grids and the full workflow graph; parameters survive every rerun.
licenseMIT
runsyour server
installRun the Windows installer script, the Linux launch script, or install .NET/Python/Homebrew prerequisites and run launch-macos.sh on macOS; Docker is optional
enginesUses ComfyUI as its main backend for Stable Diffusion, SDXL, FLUX, Wan, LTX, MiniMax, ACE-Step, and other image/video/audio workflows; an Automatic1111-compatible backend is optional
dataConfiguration, users, models, workflows, generated media, and history live in the local SwarmUI installation and configured model/output directories
the catch vs Leonardo AIIt saves settings and history, but its asset organization and collaboration are thinner than Leonardo's cloud workspace.
setupThe backend and models still have to be downloaded, and non-Windows installs require command-line prerequisites such as .NET, Python, and Git
facts verified 2026-08-10
A native workflow app for local and BYOK image models, with projects and results kept on your machine.
licenseAGPL-3.0
runsyour machine or their cloud
installInstall the macOS .dmg, signed Windows .exe, or Linux AppImage; Docker Compose is available for self-hosting
enginesLocal Ollama, llama.cpp/GGUF, MLX, Nunchaku, Hugging Face, and diffusion/media models, plus BYOK providers such as OpenAI, Anthropic, Gemini, FAL, Replicate, KIE, ElevenLabs, and Hugging Face
dataWorkflows, projects, assets, files, provider settings, and vector indexes live locally in YAML, SQLite/SQLite-vec, and application storage; optional S3 or Supabase storage is supported, and cloud nodes transmit their inputs
the catch vs Leonardo AIIt retains local workflows and results, but the user supplies compute and providers and gets no Leonardo-style shared asset catalog or managed training.
setupNo useful model or provider is bundled: the user must add an API key or download a multi-gigabyte local model, and some local backends add a large Python/Conda environment
facts verified 2026-08-10
Open video generation models from Lightricks that produce high-fidelity video with synchronized audio, including local weights and a trainer.
licenseApache-2.0
runsyour server
setupnot verified by us yet — check the repo README
facts verified 2026-08-29
What each one is, in full: ComfyUI · LTX
last updated 2026-08-29 · no votes, no pay-to-list · just what's real
how to choose a Leonardo AI alternative
Easiest to get running
ComfyUI — a one-click install, no server to maintain.
Most proven
ComfyUI, with 124,207 GitHub stars — the largest community of the 5, which usually means more answers when something breaks.
Needs real ops to self-host
LTX is capable but expects someone to run a server, updates and backups. Budget for that before choosing it.
what you give up by leaving Leonardo AI
- proprietary models, hosted GPU capacity, training tools, and asset ecosystem
- frontier proprietary models
- hosted GPU capacity
- licensed training data
- moderation and fast global delivery
None of the picks above covers all of it. The full verdict says which gaps matter.
Leonardo AI alternatives at a glance
| tool | license | running it | platforms | stars | active |
|---|---|---|---|---|---|
| ComfyUI | GPL-3.0 | one-click install | web, macos, windows, linux, self-hosted | 124,207 | 2026-08 |
| InvokeAI | Apache-2.0 | one-click install | web, macos, windows, linux, self-hosted | 27,776 | 2026-08 |
| SwarmUI | MIT | one-click install | web, macos, windows, linux, self-hosted | 4,423 | 2026-08 |
| NodeTool | AGPL-3.0 | one-click install | web, macos, windows, linux, self-hosted, cli | 450 | 2026-08 |
| LTX | Apache-2.0 | self-host, real ops | self-hosted, web | 11,000 | 2026-08 |
why people still pay for Leonardo AI
People still pay for Leonardo AI because the product value is the model and compute fleet, not the prompt box around it. The recurring cost buys GPU procurement, model licensing, safety filters, queueing, storage, and rapid model replacement, not just the visible interface. If none of that applies to you, any pick above saves $144 a year.
questions about switching from Leonardo AI
Is there an open-source alternative to Leonardo AI?
Yes: ComfyUI, InvokeAI, SwarmUI and 2 more. Every tool on this page is open source: no trials, no crippled tiers.
Can open source really replace Leonardo AI?
Our verdict is YES. ComfyUI (124k stars), InvokeAI (28k stars), LTX (11k stars) are mature open-source replacements for Leonardo AI — self-host in one command and stop paying $12/mo. The full verdict, and what you give up by switching, is at caniopensourceit.online/leonardo-ai.
What is the easiest open-source Leonardo AI alternative to set up?
ComfyUI — a one-click install, no server to maintain.
What is the most popular open-source Leonardo AI alternative?
By GitHub stars, ComfyUI (124,207). InvokeAI is next with 27,776.
