Llama 3.3 70B vs Llama 4

Last of one generation, first of the next

Llama 3.3 70B, released by Meta on December 6, 2024, was the final model of the Llama 3 generation. Llama 4, released on April 5, 2025, started a new one, with two models: Scout and Maverick. The jump between them is bigger than the version numbers suggest. Llama 4 changed the architecture, added images, extended context and refreshed training data. Yet Llama 3.3 70B is still widely used, and it is one of the four models in our chat. Here is how they compare.

Llama 3.3 vs Llama 4 at a glance

Prices are OpenRouter list price, Oct 2026.

Dense vs mixture of experts

Llama 3.3 70B is a dense model: all 70 billion parameters work on every token. Llama 4 uses a mixture of experts: the model contains many expert sub-networks, and only some of them, about 17 billion parameters, are used for each token. The result is that Llama 4 holds much more knowledge in total (109 billion parameters for Scout, 400 billion for Maverick) while doing less work per token than Llama 3.3. Meta presented Maverick as offering higher quality than Llama 3.3 70B at a lower cost to serve.

For you as a user, this mostly means Llama 4 answers tend to be richer, and the models are efficient for providers to run.

Images, languages and knowledge

The clearest practical difference is images. Llama 3.3 70B reads text only. Both Llama 4 models accept images natively, so you can ask about photos, charts, screenshots and documents. In our chat, attaching an image while Llama 3.3 is selected switches the conversation to Maverick.

Llama 4 also widened official language support from eight languages (English, German, French, Italian, Portuguese, Hindi, Spanish and Thai) to twelve, adding Arabic, Indonesian, Tagalog and Vietnamese. And its training data runs to August 2024, eight months later than Llama 3.3's December 2023 cut-off. Neither can search the web in our chat.

Where Llama 3.3 still makes sense

Llama 3.3 70B is a mature, well-understood text model that has been available since late 2024, so plenty of apps, prompts and guides already assume it. Its license situation is simpler in one respect: it is not a multimodal model, so the EU restriction that applies to Llama 4's multimodal models does not apply to it. And as a dense model, all of its 70 billion parameters work on every token, so its memory needs and behavior are straightforward to plan for.

Its API price is also low: $0.10 input and $0.32 output per million tokens on OpenRouter, essentially the same as Scout and about half of Maverick's $0.1875 and $0.6525 (OpenRouter list price, Oct 2026). So despite Meta's claim about serving cost, Maverick is the more expensive of the two at this provider.

Running them yourself

A 70B dense model needs a powerful workstation; Ollama lists the comparable Llama 3.1 70B at 43 GB. Llama 4 Scout is a 67 GB download and Maverick 245 GB. Meta notes Scout fits a single H100 GPU with Int4 quantization. For typical home hardware, none of them is easy; Llama 3.1 8B is the light option. See run Llama locally.

Licensing is similar for both. Llama 3.3 comes under the Llama 3.3 Community License and Llama 4 under the Llama 4 Community License; both allow commercial use, require "Built with Llama" attribution and apply Meta's acceptable use policy. Our license guide covers the details.

Trying them side by side

All three models are in our chat, so the easiest way to compare is to ask the same question to each. A few prompts that show the differences well:

• A writing task in your own style, such as a short email or product description. Compare tone and wording.
• An explanation, for example how a mortgage works or what a mixture-of-experts model is. Compare clarity and structure.
• A question in one of the four languages Llama 4 added, such as Vietnamese or Indonesian. Llama 4 is officially supported there; Llama 3.3 is not.
• A photo or screenshot. Only Llama 4 can answer; with Llama 3.3 selected, the chat switches to Maverick.
• Something from 2024, such as an event from spring 2024. Llama 4's training data covers it; Llama 3.3's does not. Neither knows about later events.

Pick the model in the menu, ask, then switch and ask again. Your history stays in your browser, and our chat does not store message text.

Choose Llama 3.3 if…

• you work only with text;
• you want to avoid the EU clause for multimodal models;
• you prefer a dense model for your own deployment;
• your existing app or prompts were built around it.

Chat with Llama 3.3 70B

Choose Llama 4 if…

• you want to ask about images;
• you need one of the four added languages;
• you want more recent training data;
• you need long context through an API or your own hardware.

Chat with Llama 4 Maverick

Within Llama 4, read Maverick vs Scout. For the whole family, see Llama history and the model pages for Llama 3.3 70B and Llama 4 Maverick.

FAQ

Is Llama 4 better than Llama 3.3?

For most tasks, yes: Llama 4 is newer, reads images and supports more languages. Llama 3.3 remains a solid text model.

Is there a Llama 3.3 8B?

Meta's Llama 3.3 model card covers the 70B model. For a small model, use Llama 3.1 8B.

Can I switch between them in your chat?

Yes. All three are in our model menu: Llama 3.3 70B, Llama 4 Scout and Llama 4 Maverick.

Does Llama 3.3 know newer events than Llama 4?

No. Llama 3.3's training data ends in December 2023; Llama 4's ends in August 2024.