10 Best LLMs in 2025: Large Language Models Reviewed

Are you drowning in customer support requests? Battling tight deadlines for content creation? Worn out  from the pressure to maximize productivity? You're not alone. Running a business today can feel like a constant battle against the clock and budget. 

A solution exists: large language models (LLMs), your personal artificial intelligence (AI) assistant to help navigate all these challenges.

But how do you pick the right one with so many options and information overload? You have to compare performance, accuracy, data security, cost, vendor support – the list goes on!

Let me make it easier for you. I teamed up with Matthew Miller, our resident expert on LLMs, to evaluate 44 solutions. This listicle explores the 10 best LLMs for 2025. We mined each product to understand its features and how they benefit you. It'll help you find the perfect language model for your specific needs, whether it's scaling customer support, managing internal knowledge, automating repetitive tasks, upping your content game, or personalizing marketing and sales.

How did we select and evaluate the best LLMs?

We ranked large language model solutions using a proprietary algorithm that considers customer satisfaction and market presence based on actual user reviews. Our market research analysts and writers (Matthew and I in this case) spend weeks evaluating solutions against multiple criteria set for a software category. We give you unbiased software evaluations – that's the G2 difference! We don’t accept payment or exchange links for product placements in this list. Please read our G2 Research Scoring Methodology for more details.

1. Gemini: best known for natural conversation

Gemini is an LLM developed by Google AI. It stands out for its ability to process information from various formats, including text, images, and video. This capability allows it to extract information from documents and answer frequently asked questions, enhancing customer support, personalizing customer interactions, and even powering content creation. Launched in December 2023, it comprises three models: Gemini Ultra, Pro, and Nano, each serving different needs. 

Matthew and I liked the error learning capability where Gemini was able to identify, correct, and learn from prior mistakes.

What users like best:

“Gemini is a powerful AI chatbot. It processes large amounts of text and codes to generate results quickly. It also processes our images and performs the desired tasks. The integration with other Google tools, such as Google Docs, Sheets, Gmail, and Drive, automates our process. The interface for chatting with Gemini is also very intuitive.”

- Gemini Review, Rahul S.

What users dislike:

“Gemini's reasoning behind outputs can be unclear, making it difficult to verify accuracy and mitigate potential biases. This opacity is unsettling, especially for users handling sensitive information.”

- Gemini Review, Ömer K.

2. BERT: best known for ethical guidelines adherence

BERT or Bidirectional Encoder Representations from Transformers utilizes a transformer-based neural network to understand the relationships between words in a sentence. This architecture and nuanced understanding facilitate more accurate machine translation, bias detection, and responsible AI practices. Developed by Google in 2018, BERT shows off its skills with various natural language processing (NLP) applications, including machine translation, question-answering, and sentiment analysis.

We really appreciated the content moderation features that prevent the model from generating inappropriate responses.

What users like best:

“BERT's contextual understanding enables it to answer questions based on a given passage. It is open source and very easy to fine tune to improve further accuracy.”

- BERT Review, Prashanth D.

What users dislike:

“Its computational requirements are demanding. Implementing BERT effectively might necessitate robust hardware resources, which could be a consideration for certain projects.”

- BERT Review, Taahir B.

3. Meta Llama 3: best known for sentiment analysis

Meta Llama 3, developed by Meta, is presented as the latest generation of the best open-source LLMs. Available in 8B and 70B parameter configurations, these models utilize pretraining and instruction fine-tuning to deliver enhanced performance across AI tasks. Offered in versions like Llama 3.1, Llama 3.2, and Llama 3.3, the models use a tokenizer with a vocabulary of 128K tokens, substantially improving tasks such as responding to questions in natural language, writing code, and brainstorming ideas.

We really appreciated Meta Llama's flexibility in building custom language models.

What users like best:

“Meta Llama 3 is fantastic at understanding and responding to natural language, making conversations feel smooth and natural. It's highly accurate than previous versions of Llama and gives relevant answers, which boosts productivity and user experience. It also intergrates with development applications. Plus, it's easy to customize for different uses because of the variations 7B,13B based on their personal projects or business needs.”

- Meta Llama 3 Review, Praveen A.

What users dislike:

“One thing I dislike about Meta LLaMA 3 is its potential resource intensity. Running such an advanced model can require significant computational power and memory, which might be a limitation for smaller organizations or individual users with limited access to high-end hardware. Additionally, despite its advanced capabilities, there can still be occasional inaccuracies or biases in the generated responses, which highlights the need for continuous refinement and monitoring.”

- Meta Llama 3 Review, Luis N.

4. GPT3: best known for response generation speed

GPT-3, short for Generative Pre-trained Transformer 3 uses NLP,  natural language generation (NLG), and 175 billion (!) parameters to produce human-like text. This allows it to effectively perform tasks like content creation, translation, and code generation. GPT-3's high response generation speed makes it valuable for enhancing chatbots, automating manual tasks, and scaling customer interactions in real-time. 

We liked how the model efficiently handled long back-and-forth conversations.

I also liked this MarTech piece that covers what's new in the AI data usage space with OpenAI and Financial Times deal. Check it out.

What users like best:

“GPT3 as a large language model is the closest we are to a text-based artificial general intelligence (AGI). I use it daily both personally and professionally. It helps me summarize large text files, generate ideas, and optimize existing workflows.”

- GPT3 Review, Jahnavi Prasad S.

What users dislike:

“Just like that friend who misreads your mood, ChatGPT-3 may occasionally misinterpret your messages or provide responses that don't really align with your expectations. It's worth keeping in mind that ChatGPT3, while extremely intelligent, isn't the best source for the latest news. Its knowledge base is frozen in time in 2022, so you won't get the best and newest updates from it.”

- GPT3 Review, Ava L.

5. GPT4: best known for contextual understanding

GPT-4, OpenAI's latest release from March 2023, is a powerful multimodal language model with an estimated 1.76 trillion parameters. It surpasses previous GPT models in its ability to perform complex tasks with greater accuracy and efficiency. GPT-4 users often report that it is more creative, maintains a better conversation memory, excels at analysis, and offers a broader range of features. Here's a quote from a Redditor that I really liked: "4 is more like talking to someone who is just entering university. It's not perfect, but it has a pretty good understanding of things, is a lot more logical, less likely to make things up, and can express its answers better." 

Matthew and I thought the easy integration with existing processes ranked as a definite plus.

What users like best:

“GPT4’s advanced language understanding and generation capabilities are impressive. Its ability to produce human-like text with high fluency and coherence makes it an invaluable tool for applications ranging from drafting content to providing customer support. Additionally, GPT4’s versatility across different domains, from technical subjects to creative writing, and improved contextual understanding enhance the quality and relevance of its responses in complex and extended conversations.”

- GPT4 Review, Bryan S.

What users dislike:

“Sometimes it doesn't follow instructions. It always produces content in Markdown format, so I have to waste time deleting various symbols when I paste it into Google Docs.”

- GPT4 Review, Joseph G.

6. AutoGPT: best known for content moderation

AutoGPT is an open-source AI agent built on OpenAI's advanced GPT-4 language model. It understands your goals and breaks them down into manageable tasks. AutoGPT autonomously handles tasks such as market research, business plan creation, and content generation for articles and social media posts, utilizing online resources and various tools. It simplifies workflows and accelerates project completion with minimal manual input.

We loved AutoGPT’s ability to access popular websites and platforms and scrape data from those.

What users like best:

“AutoGPT includes various AI applications that save time and money for my business, such as email marketing, photo editing, content writing, and search optimization.”

- AutoGPT Review, Jagmeet S.

What users dislike:

“AutoGPT is tailored for users with Python proficiency and development software experience. Installation and usage involve complex technical steps, which can be difficult for non-technical users. Additionally, based on GPT-4 token usage, AutoGPT charges $0.03 per 1,000 tokens for prompts and $0.06 per 1,000 tokens for results. As tasks require multiple GPT-4 model calls, costs escalate swiftly, potentially becoming prohibitive for larger projects or smaller organizations.”

- AutoGPT Review, Maninder S.

7. Megatron-LM: best known for data privacy protection

NVIDIA's Megatron-LM is a powerful framework for training LLMs. It utilizes techniques like model parallelism and mixed precision training to efficiently handle massive datasets, resulting in significant performance and scalability gains. Megatron-LM’s offline deployment capability allows the utilization of powerful language models within highly secure, data-sensitive environments, ensuring greater confidentiality and compliance.  

The integration of Megatron-LM with Microsoft's DeepSpeed library is a really exceptional feature that further enhances its execution and flexibility.

What users like best:

“We appreciate its unparalleled scalability and efficiency on NVIDIA's graphics processing units. Its ability to process vast datasets rapidly accelerates our AI-driven projects, offering exceptional language understanding and generation capabilities. This robust performance enables us to innovate and deliver sophisticated AI solutions swiftly and effectively.”

- Megatron-LM Review, Yogesh B.

What users dislike:

“It's got a steep learning curve, requires serious hardware, and the documentation could be improved. Plus, potential bias lurks.”

- Megatron-LM Review, Nikhil O.

8. Tune AI: best known for content generation

Tune AI, formerly NimbleBox.ai, specializes in generative AI solutions for enterprises. It allows you to customize LLMs to your specific needs using your proprietary data, offering powerful features like open-stack compatibility, seamless document integration, and enterprise-grade security. One of their products, Tune Studio, provides a secure platform for fine-tuning and deploying large language models. Tune AI also comes with Tune Chat, an AI chat app with text and code generation capabilities for non-technical users.

In addition to everything we mentioned above, we liked its ability to act as a writing assistant and give suggestions for grammar, formatting, tone, and style.

What users like best:

“Tune AI’s user-friendly interface makes building and managing chatbots easier. Its AI-powered responses are remarkably accurate and closely mimic human interaction. It easily integrates with multiple communications channels, guaranteeing consistent customer service across platforms. Additionally, Tune AI's analytics capabilities are priceless for collecting user interaction insights and gradually improving the chatbot's efficacy.”

- Tune AI Review, Bessy G.

What users dislike:

“ChatNBX (now Tune AI) depends on the dataset on which it is trained. Because of this, it sometimes provides inaccurate and biased responses, which makes the service less useful. It also lacks some advanced features, like large text processing on a single input, providing invalid responses due to the large amount of information.”

- Tune AI Review, Yogender K.

9. GPT2: best known for the quality of documentation

GPT2, one of the initial models developed by OpenAI, is equipped with 1.5 billion parameters and was trained on a dataset of about 8 million web pages. Its primary function is to predict the next word in a sentence. GPT2 can generate contextually relevant text across various subjects, summarize content, translate, and create stories or essays based on prompts. Due to concerns over potential misuse, OpenAI released a limited version of the model.

We liked how GPT2 understood and maintained the context of the conversation.

What users like best:

“I love how intuitive it is to use. GPT2 is fast, adaptable, and easy to command. I like using GPT2 for brainstorming ideas to get me going, and then later for refinement on grammar and wording. We use it almost daily for all kinds of things--thought starters, turning bullets into a full paragraph of full sentences, grammar and punctuation correction, Excel troubleshooting, and more.”

- GPT2 Review, Avery C.

What users dislike:

“One notable drawback is that it sometimes produces content that is factually incorrect or biased, as it relies on patterns learned from the training data.”

- GPT2 Review, Jose M.

10. T5: best known for bias mitigation

T5, short for Text-to-Text Transfer Transformer, represents a group of large language models developed by Google AI. These models have undergone extensive training on tremendous quantities of text and code data and have been utilized in various applications, including chatbots, text summarization tools, code generation, and robotics. Additionally, you can fine-tune T5 to meet specific task requirements.

We both thought that the tool offered thorough and valuable documentation to help understand what it can do.

What users like best:

“I appreciate T5's versatility and its ability to handle a wide range of natural language processing tasks. It's been particularly useful for creating a chatbot for my business and a customer support agent for addressing common queries. The pre-training and fine-tuning capabilities make it easy to adapt to specific use cases.”

- T5 Review, Shamaas H.

What users dislike:

“Fine-tuning the T5 model is expensive and requires significant resources. As it is not trained on large amounts of data, it sometimes gives biased responses.”

- T5 Review, Aditya S.

Bonus large language models

Matthew and I also really liked the following software while testing LLMs:

1. IBM watsonx.ai: best known for pre-built algorithms for model development
2. Crowdin: best known for translation tracking
3. Claude: best known for context management

Finding the best LLM

When you’re trying to choose a large language model tool, Matthew and I agree that you have to consider your own use case, the accuracy of the model, and the model’s size and capacity. You might also want to look at the data it’s been trained on and the security and compliance features it offers before finalizing a purchase. Keeping all these things in check will make certain you invest in a solution that works best for your business needs and keeps your data secure.

We hope this compilation of the best large language models will assist you in finding your best match! 

Looking for LLM-powered AI chatbots? Check out this list of 7 Best AI Chatbot Software for 2025.

Edited by Aisha West