Grok vs Llama

A fresh closed model vs an older open family

Comparing Grok with Llama in 2026 means comparing two quite different things. Grok is xAI's actively developed, closed assistant, with a new flagship, Grok 4.7, released in September 2026. Llama is Meta's family of open-weight models; its latest generation, Llama 4 Scout and Llama 4 Maverick, came out in April 2025 and is still widely used because anyone can download and run it. Meta's newer assistant models carry a different name, Muse, and are not Llama models.

Grok.Online is an independent site that runs Grok models only; Llama is not in our chat.

Comparison table

OpenRouter list price, Oct 2026. Llama prices differ between hosting companies.

Age matters

Llama 4 is about eighteen months older than Grok 4.7, and in AI that is a long time. Grok 4.7's training data runs to May 2026, so it knows about far more recent events, software versions and research. If you need an assistant that is as capable as possible for hard reasoning, long agent tasks or difficult code, a current flagship like Grok 4.7 is the stronger pick. We do not quote benchmark scores, since both makers' own numbers measure different things, but the gap between a 2025 open model and a late-2026 flagship is usually easy to notice on demanding tasks.

Openness and control

Llama's big advantage is that you can have it. The weights for Scout and Maverick can be downloaded, run on your own hardware or cloud, fine-tuned on your own data and built into products, as long as you follow Meta's community license, which includes some conditions for very large companies. Scout, with 109 billion parameters in total, is the smaller of the two. Because many providers host Llama, the price per token is very low.

With Grok you rely on xAI or a reseller such as OpenRouter. xAI has published weights only for old models: Grok-1 in 2024 under Apache 2.0, and Grok 2.5 in 2025 under its own community license. Those are interesting for research, but they are far behind today's Grok.

Using them day to day

Most people will meet Grok on grok.com, in the Grok apps, on X, or on a site like ours. Its official apps add web and X search, voice and Grok Imagine for pictures and video. Llama has no single home: it runs inside other people's apps and tools, on hosting services and on enthusiasts' own computers, so what you get depends on who runs it.

Meta's own assistant, Meta AI, has moved on to Meta's newer Muse models, so Llama today is mainly a model for developers and tinkerers rather than a consumer product.

Cost

For bulk work through an API, Llama is much cheaper: Scout costs $0.10 per million input tokens, compared with $1.25 for Grok 4.20, the cheapest Grok model in our chat. If your task is simple, such as classifying text or extracting fields, that difference adds up quickly. For harder tasks, a stronger model that gets it right the first time can work out cheaper overall. Running Llama on your own servers changes the maths again: there is no per-token bill, but you pay for the GPUs, electricity and the people who keep the setup running, which only makes sense at steady, high volume or when data must stay in-house. On our site, all three Grok models are free to try, with 30 messages a day.

Scout or Maverick?

If you do pick Llama, you still have to choose between the two Llama 4 models. Both activate 17 billion parameters per token and both read images, so they feel quick for their quality.

• Llama 4 Scout uses 16 experts and 109 billion parameters in total. It is the lighter of the pair, the easier one to host, and on OpenRouter it has the longer window, about 1.3 million tokens.
• Llama 4 Maverick uses 128 experts, which makes it much larger overall and generally the stronger of the two, with a window of about 524,000 tokens on OpenRouter.

Hosting either yourself still needs data-centre GPUs, not a home PC. People who want a model on their own laptop usually choose much smaller open models. If what you really want is a capable assistant to talk to, a hosted model is the simpler route, and you can try Grok 4.20 in our chat in seconds.

Choose Grok if…

• you want a current flagship model with knowledge into 2026;
• your work involves hard reasoning, coding or long tasks;
• you prefer a managed service to running your own model;
• you want to try it right away: chat with Grok 4.7 for free.

Choose Llama if…

• you need to run a model on your own hardware or private cloud;
• you want to fine-tune a model on your data;
• very low cost per token matters more than top-end quality;
• your project needs open weights for legal, privacy or research reasons.

Comparing open models more broadly? See Grok vs DeepSeek, or read about the history of Grok, including its open releases.

FAQ

Is Llama better than Grok?

For running a model yourself, Llama is the practical choice because its weights are open. For the best answers today, a current model like Grok 4.7 is stronger.

Is there a newer Llama than Llama 4?

Not under the Llama name, as of October 2026. Meta's newer models are called Muse.

Is Grok open source like Llama?

Only partly. Grok-1 and Grok 2.5 have public weights, but the current Grok models do not.

Can I use Llama on Grok.Online?

No. Every model in our chat comes from xAI; Meta's Llama is not among them.