Llama vs Gemini

Meta's open models and Google's AI

Llama is Meta's family of open-weight AI models: you can download them, run them on your own hardware and build them into products. Gemini is Google's family of closed AI models, used in Google's Gemini app and products and offered to developers through Google's APIs. Google also has its own open-weight family, Gemma, which is the closer match to Llama. This page compares all three angles as of October 2026.

Our site runs Llama models only. Gemini and Gemma are not available in our chat.

Llama vs Gemini at a glance

Prices are OpenRouter list price, Oct 2026.

Gemini: Google's closed models

Google has released a steady stream of Gemini 3.x models. On OpenRouter, Gemini 3.8 Flash from September 2026 is described as Google's most intelligent Flash model, Gemini 3.1 Pro Preview from February 2026 as its frontier reasoning model, and Gemini 3.5 Flash Lite as a high-efficiency option. They accept text, images, video, audio and files, and are listed with a context window of 1,048,576 tokens. You use them through Google's apps and APIs; the weights are not available.

Compared with Llama 4, Gemini's current models are much newer and handle more kinds of input, especially video and audio. For demanding reasoning, research and multimodal work, Gemini is usually the stronger choice. Llama's advantages are openness and control: you can run it anywhere, fine-tune it and keep data on your own machines.

Gemma 4: Google's open alternative

If you are choosing an open model, the fairer comparison is Llama 4 against Gemma 4, which Google released on April 2, 2026. According to Google's announcement, Gemma 4 comes in four sizes: Effective 2B (E2B), Effective 4B (E4B), a 26B mixture-of-experts model that activates 3.8 billion parameters during inference, and a 31B dense model. All of them process images and video, and the two small models also take audio input. Google says the family was trained on over 140 languages, offers 128K context on the small models and up to 256K on the larger ones, and is released under Apache 2.0.

Gemma 4 is a year newer than Llama 4 and much smaller. Google says the 26B and 31B models fit on a single 80 GB H100 GPU unquantized, and quantized versions run on consumer graphics cards, while the E2B and E4B models are built for phones and small devices. Llama 4 Scout and Maverick are larger in total and need more hardware. For on-device use, Gemma 4's small models compete with Meta's older Llama 3.2 1B and 3B.

Licensing

Gemini has no license for weights because the weights are not released; you agree to Google's service terms when you use it. Gemma 4 uses Apache 2.0, a standard open-source license with few conditions. Llama 4 uses Meta's community license, which allows commercial use but adds the acceptable use policy, "Built with Llama" attribution, a naming rule, the 700 million monthly active user threshold and an EU restriction for multimodal models. Our license guide explains Llama's terms.

Privacy and cost

With Gemini, your prompts go to Google's services under Google's terms. With Llama or Gemma, you can run everything locally so nothing leaves your computer; see run Llama locally. In our online Llama chat, messages pass through our server and an inference provider, we do not store message text, and your history stays in your browser.

For developers, Llama 4 Maverick at $0.1875 input and $0.6525 output per million tokens is far cheaper than Gemini 3.8 Flash at $0.825 and $4.125 or Gemini 3.1 Pro Preview at $2 and $12. Gemini 3.5 Flash Lite is listed at $0.30 and $2.50 (OpenRouter list price, Oct 2026). Open models on your own hardware have no per-token cost.

How to decide in practice

Start with the question of where your data may go. If prompts must stay on your own hardware, the choice is between Llama and Gemma, and Gemini is out. If a hosted service is fine, compare Gemini's newer models against Llama 4 on a few of your real tasks, and weigh the difference in price per token. For phones and small devices, look at Gemma 4's E2B and E4B models or Meta's Llama 3.2 1B and 3B. And if you just want to chat with a capable model for free, our Llama chat needs no account.

Choose Llama if…

• you want open weights you can self-host, inspect and fine-tune;
• you want low API costs for everyday text and image tasks;
• you rely on the large ecosystem of Llama tools and fine-tunes;
• you want a free online chat without an account, like ours.

Chat with Llama 4 Maverick

Choose Gemini if…

• you need a current frontier model for demanding reasoning or research;
• you work with video, audio or long documents in one request;
• you already use Google's apps and services;
• you prefer a hosted service over running models yourself.

And if you want an open model from Google, consider Gemma 4, especially for phones and smaller GPUs. For more comparisons, see Llama vs ChatGPT and Llama vs Qwen.

FAQ

Is Gemini open source?

No. Gemini's weights are not released. Google's open-weight family is Gemma, which uses Apache 2.0.

Is Gemini better than Llama?

Gemini's current models are newer and handle more input types. Llama is open, cheaper per token and can run on your own hardware.

Can I use Gemini in the Llama.Online chat?

No. Our chat runs only Llama models. Gemini and Gemma are not available here.

What is the difference between Gemini and Gemma?

Gemini is Google's closed model family used in its products and APIs. Gemma is Google's open-weight family that you can download and run yourself.