Llama 4 is Meta's family of open-weight language models: you can download them, fine-tune them and run them on your own hardware. Picasso IA runs Llama 4 Scout and Maverick for you beside 488 models for image, video, voice and 3D, with free credits to start and nothing to install.
Picasso IA and Llama 4 are not two products of the same kind, and that is the first thing worth getting straight. Llama 4 is a family of language models from Meta whose weights are published, which means you can download the files, load them on a server you control, adjust them with your own data and build them into your own software. Picasso IA is a hosted studio: 488 models behind one account, including Llama 4 Scout and Llama 4 Maverick, so the question for most readers is not which model is better but where they want to use it.
If you are the person who owns a GPU budget, a compliance requirement or a product that has to ship its own model, run it yourself. Self-hosting gives you things no hosted service can: the files on your own disk, a model version that never changes under you, a setup you can run with no outside service involved, and the freedom to retrain it. If you are the person who wants to type a prompt into Llama today, compare it with other language models in the same tab and then generate an image, a clip or a voiceover from the same account, using it through Picasso IA is the shorter road.
Nothing here is a contest between a good option and a bad one. One path trades convenience for control, the other trades control for convenience, and most of this page is about which trade matches the job in front of you. Where running Llama 4 on your own machines is simply the better answer, which is more often than a comparison written by a hosted service tends to admit, the page says so in plain words.
Eleven rows. The first seven are yes or no questions with a certain answer for both sides, the last four need a short phrase because a mark cannot describe them fairly.
| Feature | Picasso IA | Llama 4 |
|---|---|---|
| Chat and text generation with a large language model | Yes | Yes |
| Downloadable weights you can run on your own hardware | No | Yes |
| Fine-tuning the language model on your own data | No | Yes |
| Image generation from a text prompt | Yes | No |
| Video generation from a text prompt | Yes | No |
| Voice and text-to-speech generation | Yes | No |
| Language models from many different labs in one place | Yes | No |
| Models in the catalog | 488 models, twelve categories | One open-weight model family |
| First step to use it | Open a model page, write a prompt | Download weights or choose a host |
| Who runs the hardware | We run it for you | You, or a host you pick |
| Where your prompts are processed | On our service, in your account | Wherever you deploy it |
Picasso IA leads on 4 rows, the open model leads on 2, and the other 5 come down to what you need.
Look at why the rows fall where they do before you trust the tally. The four rows we win are about formats and variety, and a language model is not supposed to draw or speak, so nobody should call that a defect in Llama 4. The two rows the open model wins are the ones that decide most self-hosting projects: having the weights and being allowed to retrain them. If either of those is on your requirements list, no catalog of any size on our side replaces it.
A new Picasso IA account starts with free credits that work on the same catalog everyone else uses, Llama 4 Scout and Llama 4 Maverick included. Each has its own model page where you write a system prompt, set the controls the page shows (temperature, top-p, top-k, output length, stop sequences, repetition penalties) and read the answer in the same screen. You can also browse the collection and the effects gallery without paying, which is a quick way to see what the other eleven categories produce before you spend anything.
With Llama 4, the free part is the weights. Meta publishes them, you can download them, and nobody charges you per question once they are on your machine. What is not free is everything around them: a GPU or a rented one, the storage, the time to set up a serving stack, the patience to keep it updated and the person who gets paged when it falls over. For a developer who already has the hardware and the habit, that is close to nothing. For someone who simply wanted to try the model for an afternoon, it is the whole afternoon and then some.
Meta publishes the weights under its own license, which has its own conditions, so read it before building anything on top. The honest split: if you want to be talking to Llama within a minute and have no machine to run it on, start in the browser. If you have the machine and want the model to be yours, start with the download and ignore a hosted service entirely.
On Picasso IA, paying buys credits, and a credit is what every generation spends. The cost depends on the model and the settings you choose, a short text reply from a language model is a different size of job from a video clip, and the current plans and numbers live on the pricing page because a figure printed in an article goes stale. Nothing about a subscription changes what Llama is; it changes how much you can run in a month.
With Llama 4, there is no plan to buy from Meta for the weights themselves, so paying moves to your side of the table. You pay for the machines (owned or rented), for whoever maintains them, or for a third-party host that serves the model for you, in which case that host sets its own terms and you should read them rather than assume they match ours. The bill tends to look the opposite way round: expensive to start, cheap per request once the hardware is busy, and awkward when it sits idle.
How to pick: if your use is occasional, bursty or exploratory, credits on a hosted account usually match the shape of the work. If your use is constant, high-volume and predictable, owning the serving path is where self-hosting earns its keep. Work out your own volume before you decide, because that single number settles the argument more often than any feature list does.
This is the section where the open model is genuinely, specifically better, so it gets the most room on the page.
Start with control. When you run Llama 4 yourself, you decide everything about how it answers: the serving software, the precision it runs at, the system prompt baked into your product, the maximum length, the sampling settings, the guardrails around it. You can pin one exact copy of the weights and know that the model answering in a year is the model answering today, which matters when a product has been tested against one set of behaviors and cannot afford a surprise. A hosted catalog, ours included, exposes the controls the model page shows and nothing deeper. You cannot reach into the weights from a browser tab.
Then privacy. If the text you feed the model is a customer contract, a patient note, source code or anything your own rules say must not leave your network, a model running on machines you control is the straightforward answer: the prompt never travels to a service. A hosted studio can tell you how it treats your data, and you can read it, but it cannot make the question disappear the way a server in your own rack does. For regulated work, this alone often ends the discussion.
Then fine-tuning. Open weights can be trained further on your own examples: your support tickets, your house style, your product vocabulary, your legal clauses. The result is a model that answers like your organization, and you own that file. Picasso IA does not offer language model fine-tuning. What we offer is choice among finished models and a system prompt, which gets you surprisingly far for tone and format but is not the same as changing the model itself. If a specialized model that behaves your way is the goal, self-hosting an open model is the proper route, and our comparison with ComfyUI describes a similar split for image work.
Then independence. A model on your own hardware keeps working when a service has an outage, when a provider changes its catalog or retires a model you depended on, or when you are on a plane. It can sit behind a firewall with no outside connection at all. It can be quantized, batched, cached and wired into your own pipeline in ways a shared service has no reason to offer.
Picasso IA makes the other bet. You do not set up anything, and the model sits next to many others. Llama 4 Scout and Llama 4 Maverick are in the catalog beside language models from other labs, among them GPT-5, Claude Sonnet 5, Gemini 3 Pro, DeepSeek R1 and Grok 4, so you can send one prompt to several and see which answer suits the job, something that would take a separate deployment per model on your own hardware. When a new model arrives it appears as another entry, no download needed. And the same account that answered your text prompt can make an image, a clip or a voice track, which a self-hosted language model cannot do on its own.
Llama 4 is a language model, so its output is text. It writes, summarizes, answers, rewrites, extracts and reasons through problems in words, and it can be the brain of a larger system. Out of the box it does not draw a picture, render a video clip, speak a sentence or build a 3D mesh. Anyone who wants those things around a self-hosted Llama assembles them from other models and pipelines, which is doable and which plenty of teams enjoy, but it is a project, not a feature.
Picasso IA covers the other formats directly. Image generation runs through families such as FLUX and Seedream, edits that keep the rest of a picture intact through nano banana, video through engines including Kling and Veo, music, text-to-speech voices and speech-to-text, and 3D model generation, all in one account and all priced in the same credits. You pick the model in the toolkit or open its page, write a prompt or attach files, and generate. If a clip needs narration, the text to speech API route and the toolkit use the same voices.
There is also a middle path that suits a lot of people. A language model writes the prompt, the script or the shot list, and a different model renders it. Inside Picasso IA you can do that without leaving the catalog: ask Llama for ten variations of a product scene, copy the best into an image model, then send the result to a video model. Supercomputer, our agent in a chat, goes one step further and plans a job like that for you from a plain description, picking models and showing the result, which is covered in the creative agent page.
The fair summary: for text alone, the two are the same family of model with a very different setup. For everything that is not text, Picasso IA covers formats Llama does not, and that is a statement about scope, not about quality.
For a language model, editing means editing words: tightening a paragraph, changing tone, fixing grammar, translating, reformatting notes into a table. Llama 4 does that well, and a self-hosted copy can be tuned to a house style until it edits like your own team. That is a real strength and one of the strongest reasons companies choose to train an open model.
Editing an image, a photo or a video is a different job, and Llama 4 does not do it. There is no background remover, upscaler or retouch step inside a language model. To get those on a self-hosted setup you would add separate image models and wire them in yourself.
On Picasso IA, the editing tools are models like any other and accept pictures made anywhere. A background remover cuts out a subject from a phone photo, an upscaler such as Real-ESRGAN adds resolution to a small image, and instruction-driven editors change a detail while leaving the rest of the picture alone. If you do this at volume, the background removal API lets you send images from code. Testing one on a real file is a small experiment, and new accounts start with free credits.
Speed with a self-hosted Llama depends entirely on the machine under it, and that is both the advantage and the burden. A well-sized GPU with a tuned serving stack can answer quickly and consistently, and you decide how many people share it. An under-sized one is slow, and you will be the first to hear about it. On Picasso IA, speed depends on the model and the settings: a text reply is a lighter job than a video clip, which takes longer. There is no hardware for you to size or maintain.
Limits differ in kind. A model you host has the limits you give it: the context and output length your setup allows, the number of concurrent users your hardware carries, the guardrails you add or remove. On Picasso IA, the limits are those of each model page and of your credits, with the controls laid out on screen. If you need a behavior that no setting exposes, the self-hosted route is where you get it.
Commercial use needs reading on both sides. Meta publishes the Llama weights under its own license with its own conditions, and you are responsible for following them in whatever product you build, which is worth a careful read before you ship. On Picasso IA, each model has its own license from its maker and the platform has its own rules, so check the model page and the terms for the one your business depends on. In both cases, what a model writes can echo existing text, and a person should review anything that goes out under your name.
Eight reasons, four for each side, pulling together everything above. If your real alternative to a hosted catalog is a visual node graph or open image models rather than a language model, the ComfyUI comparison and the Stable Diffusion comparison are closer to your decision than this page is.
Choose Picasso IA instead when you want to try Llama 4 right now with nothing to install, when you want to compare it against other language models in the same place, or when your work also needs images, video, voice or 3D from the same account without assembling a stack of separate tools.
Many people who care about this question end up using both: a self-hosted model for work that must stay private, and a hosted catalog for everything else. So treat the steps below as adding a tool beside what you run, not replacing it.
It is an alternative for the part of the job that is convenience, and not for the part that is control. If you want to use Llama 4 in a browser tab with nothing to install, compare it with other language models and generate images, video or voice from the same account, Picasso IA is a good fit. If you need the weights, your own fine-tuning or text that never leaves your network, running it yourself is the better answer and we do not try to replace it.
Yes. The catalog includes Llama 4 Scout Instruct and Llama 4 Maverick Instruct in the large language models category, each with its own page where you write a system prompt, set the controls and read the reply. They are also reachable like any other model through the toolkit, and through the API, where you name the model and its inputs and use the same credits as everything else.
No. Picasso IA runs the models for you, so you use them through the browser, the toolkit or the API, and the weights are not something we hand out. If you want the files, the place to get them is Meta, under Meta's own license, which is worth reading in full before you build a product on it.
Two instruct models: Scout and Maverick. In Meta's own positioning, Scout is the lighter, faster-to-run member of the family and Maverick is the larger, more capable general model, so Maverick is usually the first one to try for harder writing and reasoning. Because both are one click apart, the simplest way to choose is to send the same prompt to each and keep the answer you prefer.
Not by itself. Llama 4 is a language model, so its output is text, and the other formats come from other models. In Picasso IA you can get them in the same account: image models, video models, text-to-speech voices, music and 3D generation are all in the catalog, so a script written by Llama can become a clip or a voiceover without leaving the site.
The two are shaped differently, so we do not print numbers for either. On Picasso IA you spend credits, the cost depends on the model and settings; the current plans are on the pricing page. Running Llama 4 yourself has no fee for the weights, but you pay for hardware, power and maintenance, or for a third-party host whose terms are its own.
Check before you ship, on both sides. On Picasso IA, each model comes with its own license from its maker and the platform has its own rules, so read the page of the model you rely on and the terms. For Llama 4, Meta publishes the weights under its own license with its own conditions, and following them is up to you. Whichever you use, a person should review text before it goes out under your name.
If the machines are yours and the model is not connected to anything outside, yes, and that is one of its strongest points: the prompt never reaches a third party. On a hosted service your prompt travels to that service, which has its own rules about data, and you should read them for anything sensitive. For confidential material, self-hosting is the cleaner answer.
No. There is no partnership, no affiliate arrangement and no payment in either direction between Picasso IA and Meta, Llama 4 or any product named on this page. Llama 4 appears here because people choosing between a hosted catalog and a self-hosted open model look for this comparison, and the most useful thing we can offer them is an even-handed answer.
Yes, and this page has tried to say so all the way through. Releasing capable language models with downloadable weights gave developers, researchers and companies something they could run, inspect, adapt and own, which a hosted-only model cannot offer. For anyone who needs control, privacy or a model trained on their own material, it is a strong choice, and a hosted catalog was never meant to take that place.
Both paths reward knowing what you need this week, and the quickest way to find out is to run the same prompt in each place. Open the toolkit, pick Llama 4 Maverick, try a prompt you already use, and see whether the hosted version is enough or the case for running it yourself just got clearer.
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