Adobe shipping an image-to-video generator inside Firefly did something the open-source scene had failed to do for two years: it put “upload a photo, get a moving clip” in front of people who had never touched a diffusion model. The awkward part is that Firefly is one of the more conservative options. We spent weeks feeding the same set of stills to local models and hosted services to work out which of the best apps for AI image-to-video actually earn a slot on a desktop machine. Eight made the cut, split between tools that run on your own GPU and browser services you drive from a desktop workflow. This list is about generating motion from a still, not editing footage you already have.
What to look for in a desktop AI image-to-video app
The marketing in this category is mostly noise. Six things decide whether a tool fits your machine and your work:
- Your hardware floor. Local video generation is far hungrier than image generation. Some tools want 16GB of VRAM, others squeeze onto 6GB by offloading to system RAM at the cost of speed.
- First-frame fidelity. Good image-to-video keeps your still recognisable in frame one. Weaker models redraw faces and text on the way in, which ruins product shots and portraits.
- Motion control. Some tools take a prompt and nothing else. Others give you a brush to mark what moves, camera controls, or a second image as the end frame.
- Clip length and extension. Most models top out around 5 to 10 seconds per generation. What matters is whether the tool can extend a clip without the subject drifting.
- Licensing of the output. Adobe trains on licensed and public domain content and covers commercial use. Open weights vary, and community LoRAs vary more.
- Where the image goes. Local tools never upload your source still. Hosted services do, which decides the question for anyone working under an NDA.
Quick comparison
| App | Best for | Runs on | Free | Cost | Hardware floor |
|---|---|---|---|---|---|
| ComfyUI | Full control over local models | Windows, macOS, Linux | Yes | Free (GPL-3) | 8GB VRAM, more for video |
| LTX Desktop | Local generation without a node graph | Windows, macOS, Linux | Yes | Free (Apache-2.0) | 16GB VRAM, or Apple Silicon |
| Wan2GP | Modest GPUs | Windows, macOS, Linux, Docker | Yes | Free | 6GB VRAM |
| Adobe Firefly | Commercially cleared output | Browser, Creative Cloud apps | Limited credits | Subscription with credits | Any modern machine |
| Runway | Directing the shot | Browser | One-time credits | Monthly subscription | Any modern machine |
| Kling AI | Realistic physical motion | Browser | Daily credits | Monthly subscription | Any modern machine |
| Luma Dream Machine | Keyframed transitions | Browser | Limited free tier | Monthly subscription | Any modern machine |
| FramePack | Long clips on a small GPU | Windows, Linux | Yes | Free (Apache-2.0) | 6GB VRAM |
The apps
1. ComfyUI: best for full control over local image-to-video
ComfyUI is a node graph that wires a still image, a text prompt, and a video model into one runnable pipeline, and it is where the open video models land first. Wan 2.2, LTX-Video, and LTX-2 all run in it, usually within days of release. The desktop installer bundles Python, the model manager, and the frontend, so ComfyUI for image-to-video no longer means building an environment by hand. Workflows are JSON files, and dragging one onto the canvas rebuilds the whole graph, which is how most people start: grab a working first-frame-to-video graph from someone else, then swap in your own image.
Where it falls short: The graph is a real learning curve if you have only used prompt boxes. Video checkpoints are large, so expect tens of gigabytes of downloads before the first render. Node packs from the community break across ComfyUI updates more often than they should.
Pricing:
- Free: the app and the desktop installer, open source under GPL-3
- Paid: optional API nodes that call hosted models on credits, for anything your GPU cannot run
Platforms: Windows, macOS (Apple Silicon), Linux
Bottom line: Take this if you want every knob and you are willing to spend an evening learning the graph.
2. LTX Desktop: best local option without a node graph
Lightricks open-sourced a desktop app for its own LTX models, and it is the shortest route to local image-to-video for people who bounced off ComfyUI. LTX Desktop gives you a timeline rather than a graph: drop in a still, describe the motion, generate, then keep building the sequence in the same window. It is Apache-2.0 licensed and runs on Windows 10 and 11, Ubuntu 22.04 or newer, and macOS 13 or newer.
Where it falls short: The hardware ask is steep. On Windows and Linux it wants an Nvidia card with at least 16GB of VRAM, 16GB of system RAM (32GB is the comfortable number), and roughly 160GB of free disk for weights. On Apple Silicon it runs locally only if you have about 15GB of RAM free, and Intel Macs fall back to API mode, which routes generation to Lightricks’ hosted service instead of your machine. You also get LTX models only, with no path to Wan or Hunyuan.
Pricing:
- Free: the app and local generation
- Paid: API mode, which bills against a Lightricks account when your hardware cannot run the model
Platforms: Windows, macOS, Linux
Download: GitHub
Bottom line: The best free local pick if you have a 16GB card or a well-specced Apple Silicon Mac and no interest in wiring nodes.
3. Wan2GP: best for a 6GB or 8GB graphics card
Wan2GP (the app calls itself WanGP) exists for machines that every other local tool writes off. It is a browser front end that runs on localhost, downloads and configures models for you, and offloads aggressively to system RAM so that Wan 2.1 and 2.2, LTX-2, and Hunyuan Video generate on cards with as little as 6GB of VRAM. Using Wan2GP for image-to-video is a matter of picking a model from a dropdown, dropping in your still, and waiting. AMD owners get real support here too, covering RDNA 2 through RDNA 4, which is rare in this category.
Where it falls short: Offloading buys you access, not speed, so a five-second clip on a small card is measured in minutes rather than seconds. The settings sprawl is heavy, with quantisation, offload profiles, and per-model quirks all exposed at once. Documentation is a fast-moving changelog rather than a manual.
Pricing:
- Free: open source, no accounts, no credits
- Paid: none
Platforms: Windows, macOS, Linux, Docker
Download: GitHub
Bottom line: If your GPU has 6GB or 8GB of VRAM, this is the one that will actually run.
4. Adobe Firefly: best for work you have to license
Firefly’s image-to-video generator is the reason a lot of people are reading about this category at all. You upload a still, Firefly treats it as the first frame, you describe the motion and pick a resolution, and it returns an MP4 that drops straight into Premiere Pro. The pull is not the model quality. It is that Adobe trains Firefly on licensed and public domain content and stands behind commercial use, so Adobe Firefly for image-to-video is the option you can put in front of a client without a legal conversation.
Where it falls short: Motion is noticeably more cautious than Kling or Runway, with less camera movement and less willingness to animate anything complicated. Higher resolutions consume more generative credits, and credits go quickly once you start iterating. It is browser-first, so on desktop it reaches you through Creative Cloud rather than as a standalone app.
Pricing:
- Free: a small monthly generative credit allowance on a free Adobe account
- Paid: a monthly subscription, either a Firefly plan or a Creative Cloud plan that includes credits
Platforms: Browser, plus Creative Cloud apps on Windows and macOS
Download: firefly.adobe.com · adobe.com
Bottom line: Pick it for client and campaign work where the licence matters more than the last 10 percent of motion quality.
5. Runway: best for directing what moves
Runway gives you more say over the shot than anything else on this list. Its Gen-4 image-to-video model is strong on its own, but the reason people pay is the control layer around it: a motion brush that lets you paint which region of the still should move, and camera controls for pans, zooms, and orbits that behave like actual camera moves rather than prompt suggestions. For multi-shot sequences that need to look like they came from the same scene, Runway holds consistency better than the cheaper services.
Where it falls short: Credits at video rates disappear fast, and the free allowance is a one-time grant rather than a monthly refill, so the free tier is a demo and nothing more. There is no local option, no offline mode, and no native desktop app, so it lives in a browser tab alongside your editor.
Pricing:
- Free: a one-time credit grant, enough for a handful of clips
- Paid: monthly subscription tiers, with credit allowances that scale by tier and annual billing discounts
Platforms: Browser
Download: runway.com
Bottom line: Worth the subscription if you are producing shots to a brief and need to control the motion, not just request it.
6. Kling AI: best for motion that obeys physics
Kling AI is the one that keeps winning side-by-side tests on physical realism. Hand it a still and cloth falls, water behaves, and people carry weight in a way the other hosted models still fumble. It generates up to around 15 seconds of native 1080p from one image, and a video extension feature grows a clip well past that when the subject is simple enough to hold together. Kling AI for image-to-video is the fastest way to get a convincing single shot out of a single photograph.
Where it falls short: The free tier queues behind paying users and marks its output, so it is fine for testing and not for delivery. Extension is where quality drops, with faces and clothing drifting the further past the original clip you push. Like Runway, it is browser only.
Pricing:
- Free: a daily credit allowance, watermarked
- Paid: monthly subscription tiers with larger credit pools and unmarked output
Platforms: Browser
Download: kling.ai
Bottom line: The hosted pick when the shot has to look physically real and you only need one of them.
7. Luma Dream Machine: best for motion between two images
Luma Dream Machine takes a different angle on image-to-video. Alongside the usual single-still input, it accepts keyframes, meaning you can hand it a start image and an end image and let the Ray models invent the transition. That is the feature to reach for when you have two product photos, two poses, or two frames of a storyboard and want the movement between them rather than an open-ended prompt. Extend, loop, and reframe round it out, and looping is handled better here than in most rivals.
Where it falls short: Longer generations lose consistency sooner than Kling, particularly with faces. The free tier is thin and the credit maths is easy to misjudge on a first session. Nothing runs locally.
Pricing:
- Free: a limited monthly generation allowance
- Paid: monthly subscription tiers priced by generation volume
Platforms: Browser
Download: lumalabs.ai
Bottom line: Choose it when you know both ends of the shot and want the middle filled in.
8. FramePack: the odd one that generates a full minute on 6GB
FramePack is the pick most lists skip, and it does something none of the others manage. It predicts the next frame while compressing its context to a fixed length, which means VRAM use stays flat no matter how long the clip gets. A 6GB laptop GPU can produce a minute of 30fps video from one still and a motion prompt, where other local tools would run out of memory at five seconds. Apache-2.0, Windows and Linux, Nvidia RTX 30, 40, and 50 series.
Where it falls short: Development has slowed a lot since the P1 release, so it is a stable tool rather than an advancing one. The TeaCache speedup is not lossless and can change the result noticeably. There is no macOS build, and quality drifts over a very long generation, so the honest ceiling is shorter than the headline number.
Pricing:
- Free: open source, runs entirely on your machine
- Paid: none
Platforms: Windows, Linux
Download: GitHub
Bottom line: Install it if you have a small Nvidia GPU and want length rather than polish.
How to pick the right one
If you want the most capable local setup and do not mind learning a graph: ComfyUI. It runs every open video model worth running.
If you have a 16GB Nvidia card or a Mac with plenty of free RAM and want a normal app: LTX Desktop.
If your GPU has 6GB or 8GB of VRAM: Wan2GP, or FramePack when you specifically need clips longer than a few seconds.
If the output is going to a client, a campaign, or anything with a legal review: Adobe Firefly, because of the licensing rather than the model.
If you need to control exactly which part of the image moves and where the camera goes: Runway.
If you want one photograph to become one convincing shot with no fuss: Kling AI.
If you have a start image and an end image: Luma Dream Machine.
If you tried Runway and found the credits gone before the shot was right: move the iteration local. Generate variations in ComfyUI or Wan2GP where each attempt costs electricity instead of credits, then spend hosted credits only on the final render.
FAQ
What is the best free AI image-to-video app for desktop? ComfyUI if you are comfortable with a node graph, LTX Desktop if you want a normal app window and have a 16GB Nvidia card or a well-specced Apple Silicon Mac. Both are genuinely free and run entirely on your machine. Wan2GP is the free option for smaller graphics cards.
How much VRAM do I need for local image-to-video? Six gigabytes is the practical floor, using Wan2GP or FramePack, and expect minutes per clip at that level. Sixteen gigabytes is where the experience becomes comfortable and where LTX Desktop starts. System RAM matters more than people expect, because these tools offload heavily, so 32GB is a better target than 16GB.
Can I turn an image into a video without a GPU? Not locally, in any practical sense. Use a hosted service instead: Adobe Firefly, Runway, Kling AI, and Luma Dream Machine all run in a browser and ask nothing of your hardware. LTX Desktop also has an API mode that shifts generation off your machine when the local check fails.
Is Adobe Firefly image-to-video safe for commercial use? Adobe trains its Firefly models on licensed and public domain content and states that output is cleared for commercial work, provided the image you upload does not itself infringe someone’s copyright, trademark, or likeness rights. That last condition is the one people miss, since generating from a photo you do not own does not launder it.
Which AI image-to-video tool gives the most realistic motion? Kling AI, in most direct comparisons, particularly for physical behaviour like fabric, liquid, and body weight. Runway is stronger when you need several shots to match each other or need precise control over the camera. Locally, Wan 2.2 and LTX-2 through ComfyUI get closest to hosted quality if your GPU can carry them.
How long can a clip generated from one image be? Most models produce 5 to 10 seconds per generation. Kling AI reaches around 15 seconds natively and extends further, and FramePack can run to a minute locally because its memory use does not grow with length. Extension always costs consistency, so treat anything past 10 seconds as a shot that will need review.
