【Honest Review】My Real Thoughts After Using Llama for One Month
機械翻訳 / Machine-translated
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AI Friends
6時間前・9分で読める
機械翻訳 / Machine-translated
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What you'll learn in this article
I started using Llama because I had a specific need: "I want to run AI on our own server." ChatGPT and Claude are convenient, but they require sending data to external servers. Llama is an open-source AI (meaning anyone can inspect or modify its inner workings) that you can download and run on your own computer or company server. On top of that, the model itself is publicly available for free, which made it appealing as something I could try without any upfront cost. I felt it was a perfect fit for tasks involving strict security requirements or sensitive information.
My honest impression after the first week was: "This was surprisingly easy to get running." It took about 30 minutes from downloading the model from the official site to getting it set up in a local environment (an environment on my own computer). On a machine with a GPU, performance was comfortable. That said, there's a lot of technical jargon involved, and I felt the barrier to entry was a bit high for beginners. It doesn't have the same ease of use as ChatGPT, where you just open a browser and start right away. Even so, the feeling of having "my own AI" was refreshing, and my expectations for the level of customization it offered grew considerably.
1. Peace of mind from keeping data in-house
Even when feeding internal documents or customer information to the AI, there's no risk of it being sent to an external server over the internet. This makes it easy to adopt even in companies with strict security policies.
2. A fully capable AI that's free to use
It's free for use — including commercial use — as long as your monthly active users don't exceed 700 million. Running it via the cloud incurs usage-based charges, but on your own server, you only pay for electricity.
3. Llama 4 delivers a massive performance boost
Llama 4 Maverick, released in 2026, can process up to 10 million tokens (roughly 7.5 million characters) at once. Tasks like loading a long document and having it summarized became much easier.
1. Initial setup is tough for beginners
If you're not comfortable with the command line (typing text into a black screen), there's a real chance you'll give up during setup. The official documentation is also primarily in English, and Japanese-language resources are still limited.
2. Without a GPU, it runs slowly
Running Llama on a standard computer (without a GPU) can mean waiting tens of seconds for a response. You need a reasonably powerful machine to use it comfortably.
3. The lack of a UI makes for a rough experience
Llama is ultimately just a model (the AI's "brain"), so it doesn't come with a polished interface like ChatGPT's. You either have to build your own interface or put in the effort to combine it with other tools.
Compared to ChatGPT and Claude, Llama's biggest differentiator is that you can manage it yourself. ChatGPT runs on OpenAI's servers, so you're subject to changes in their terms of service or pricing. Llama, running in your own environment, makes long-term cost forecasting much easier. On the other hand, ChatGPT comes with a ready-to-use interface from the start — sign up and you're immediately good to go. ChatGPT wins on ease of use, but Llama has an overwhelming advantage when it comes to customizability and security. I came to feel that the smart approach is to use each one according to your needs.
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This article is a cross-post from AI Friends.
