December 11, 2024
In the last few years, we have seen businesses lean towards the adoption of AI solutions. Do you know that AI text generation tools use powerful large language models (LLMs)?
Over the past few years, hundreds of LLMs have emerged on the scene. Some are open-source, while others are proprietary large language models. Smaller organizations usually prefer open-source LLMs because they are free to use and modifiable to match their needs.
Today, we will be exploring the top 7 open-source LLMs among the hundreds available that you must use in 2025.
We have seen multiple top names like OpenAI introduce proprietary LLMs. However, a big name, Meta, didn’t shy away from releasing one of the best open-source LLM, Llama 3.1. It was released on July 23, 2024.
Llama 3.1 offers unmatched capabilities while staying openly available to developers. It is known for its scalability and high performance. It supports eight languages and supports a whopping 128,000 tokens context length. That means it is able to understand long texts and engage in more complex conversations. It is a powerhouse for creating synthetic data and improving smaller models.
BERT is another of the best open-source LLMs founded in 2018 by Google. It helps computers understand the context of a sentence by analyzing the surrounding words. This approach is called a bidirectional approach. It is easy to understand and works really well in practice. BERT comes in two versions:
BERT LLM is most suitable for tasks like summarization, question answering, and sentiment classification.
Falcon 180B is one of the largest open-source language models in existence. It is a top choice among free LLMs. It has 180 billion parameters and is trained on 3.5 trillion tokens. It is available for both commercial and research purposes.
Falcon 180B has better benchmarks than its competitor, Llama 2, in terms of reasoning and coding. The impressive thing about Falcon is that it not only handles a wide range of tasks but also does it efficiently. Don’t get too intimidated by its size, though; this model is optimized to make deployment less painful compared to some other massive models out there. It is most suitable for tasks that require reasoning and coding.
Mixtral 8x22B is an advanced LLM that operates with only 39 billion active parameters from a total of 141 billion. This helps reduce computational costs and resource usage while maintaining high performance.
Mixtral 8x22B is multilingual and fluent in French, English, Italian, and Spanish. It didn’t stop here; it outperforms competitors on the MBPP benchmark when it comes to math and programming. That’s what makes it the top choice for programming tasks. It’s the latest open model by Mistral AI in the game, but one that shows immense promise in the coming years.
Unlike other models developed by individual organizations, BLOOM was created by hundreds of researchers from over 70 countries. It’s a transformer-based language model with 176 billion parameters.
The best thing about this top open-source LLM is that it can provide accurate and logical responses in 46 languages and 13 programming languages. Still, you question why it is one of the best options for developers.
If you ask me what BLOOM is best at, I will say translation services, information extraction, and document classification.
I didn’t add GPT-4 or GPT-4o to the list of top open-source LLMs for 2025—mainly because, well, they’re not open-source. But I got something from GPT series variations: GPT-J.
Don’t you dare underestimate GPT-J because of the number of parameters—6 billion. It is a perfect fit for developers who want great performance without using too many resources. It’s widely used in independent projects and applications where you need a hassle-free model that still packs a punch.
GPT-J may not offer the mind-boggling scale of Falcon or BLOOM, but its practicality is unmatched. It excels the most in the data it is trained for, and that is turning prompts into text.
Vicuna 13-B is an open-source large language model that can also be called a conversational specialist. If you were to interact with it, it feels natural—almost human-like. This makes it particularly great for chat applications, customer support, or any scenario where conversation quality matters.
With 13 billion parameters, Vicuna 13-B strikes a sweet spot between size and capability. It’s highly fine-tuned to provide responses that are detailed, engaging, and cohesive. The AI community loves Vicuna for its friendly tone and conversational prowess. Honestly, it’s like chatting with your tech-savvy buddy who knows a little bit about everything!
Below is the side-by-side comparison of the key characteristics and parameters of some of the most popular open-source large language models:
The choice between an open-source and proprietary LLM is a tough call. However, there are multiple impressive benefits of using top open-source large language models. Let’s explore some of the reasons why you should use open-source LLMs in 2025:
First up is accessibility. Open-source LLMs are freely available. That means they are easy on your pockets. Whether you’re a small startup with big ideas or a curious student working on a side project, open-source LLMs give you the tools to get started right away. Anyone, anywhere in the world, can access open-source LLM models, modify them, and put them to work on solving real-world problems.
Here’s where things get even more exciting. With the best open-source LLMs, you can fine-tune the model. Tailor it to fit your specific needs. Have a niche industry that requires unique jargon? No problem. Training your model on relevant data can transform it into an efficient tool that was created only for your domain.
The best thing about top open-source LLMs is that they are affordable. Don’t get confused when I use free and affordable together. I understand that both these things are different. I stood by my stance that they are free, but the only money that you will pay is for hardware and any additional computational resources needed for fine-tuning or deployment. On the other hand, proprietary models come with a heavy cost that people with a limited budget can’t afford.
We all love transparency—be it buying your favorite dress from a store or hiring an AI development company. That’s what you get by using open-source language models. You can read the source code, understand how the model works, and even see what training data was used (in many cases). This particular thing catches the attention of many organizations committed to ethical AI practices.
The best open-source large language models thrive because of their users—developers, researchers, and enthusiasts—who actively contribute to improving the tools. Found a bug? Chances are someone’s already working on fixing it. Need help with implementation? Forums are available to offer help to the ones using free LLMs.
New large language models are emerging rapidly. Each of them has its own strengths and weaknesses that make them suitable for some tasks and not so much for others. The above-mentioned top open-source LLMs are a great choice for developers and organizations on a limited budget. We have only mentioned the best 7 LLMs that are free to use; however, the numbers are far more than these.
If you want to utilize the full potential of large language models for your businesses, you can get in touch with LLM experts at Xeven Solutions without a second thought. We have delivered secure and scalable LLM solutions to global clients, meeting their requirements.
Open-source LLMs are one of the many types of AI models that understand and generate textual data that sound natural and context-aware. Open-source large language models are free to use, modify, and distribute.
These models are trained on a vast dataset to understand the nuances of human language and provide the best possible responses. Developers from all over the world can work together to add new features and improve how the model works.
Open-source LLMs are important because they are accessible and affordable, can be tailored to specific needs, encourage ethical transparency, and enhance community engagement.
The challenges and concerns of using open-source LLMs include:
About the Author: Taimoor Asghar
Taimoor Asghar is a Technical Content Writer with a passion for emerging technologies, continuously keeping himself updated with the latest industry and technological trends. He ensures that complex concepts are translated into informative pieces, catering to both experts and novices. He crafts engaging narratives through blogs, articles, and how-to guides that captivate audiences and inspire them to delve deeper into the ever-evolving world of tech innovation.
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