Decoding the Titans: The 12 Best Large Language Models (LLMs) of 2024

Introduction

In the ever-evolving landscape of artificial intelligence, large language models (LLMs) have emerged as the new frontier, revolutionizing the way we interact with technology. With the release of ChatGPT by OpenAI and the subsequent advancements in the field, the competition to develop the most advanced LLMs has intensified. In this blog post, we'll dive into the top 6 LLMs of 2024, exploring their capabilities, applications, and the impact they're making on the AI landscape.

1. GPT-4 by OpenAI

GPT-4 by OpenAI is considered the top AI large language model (LLM) in 2024. Released in March 2023, it boasts exceptional capabilities in complex reasoning, advanced coding, and proficiency across various academic domains.

Key Features:

• GPT-4 is the first multimodal model, accepting both text and image inputs.

• It has addressed issues like hallucination and improved factuality significantly compared to previous versions.

• Trained on over 1 trillion parameters, GPT-4 supports a maximum context length of 32,768 tokens.

• George Hotz revealed that GPT-4 is a mixture model with 8 disparate models, each with 220 billion parameters.

Applications:

• GPT-4 powers ChatGPT plugins and Microsoft Bing's creative mode, allowing input of images alongside text.

• It exhibits human-level performance in various tasks and scores close to 80% in factual evaluations.

• OpenAI has focused on aligning GPT-4 with human values through reinforcement learning and adversarial testing.

2. OpenAI's GPT-3.5

OpenAI's GPT-3.5, following GPT-4, holds the second spot among large language models. It's a general-purpose model similar to GPT-4 but lacks specialization in specific domains.

Key Features:

• GPT-3.5 is known for its remarkable speed, generating responses within seconds.

• It excels in various tasks such as creative writing, business planning, coding, translation, and understanding scientific concepts.

• OpenAI recently introduced a larger 16K context length for the GPT-3.5-turbo model, enhancing its versatility.

• Despite its strengths, GPT-3.5 is prone to hallucinations and frequently produces false information, making it unsuitable for serious research work.

Applications:

• In the HumanEval benchmark, GPT-3.5 scored 48.1%, while GPT-4 scored the highest at 67% for any general-purpose LLM.

• GPT-3.5 has been trained on 175 billion parameters, whereas GPT-4 surpasses it with over 1 trillion parameters.

3. Google’s PaLM 2 (Bison-001)

Google's PaLM 2 model is among the top large language models of 2024, focusing on commonsense reasoning, formal logic, mathematics, and advanced coding in over 20 languages.

Key Features

• The largest PaLM 2 model has been trained on 540 billion parameters, with a maximum context length of 4096 tokens.

• Google offers four models based on PaLM 2 in different sizes: Gecko, Otter, Bison, and Unicorn, with Bison currently available.

• Bison scored 6.40 in the MT-Bench test, slightly lower than GPT-4's 8.99 points, but outperforms GPT-4 in reasoning evaluations like WinoGrande and StrategyQA.

• PaLM 2 is multilingual and adept at understanding idioms, riddles, and nuanced texts across different languages.

• It provides quick responses and offers three responses simultaneously.

Applications

• PaLM 2 (Bison-001) can be tested on Google's Vertex AI platform for developers. Consumers can interact with Google Bard, which runs on PaLM 2.

4. Claude v1

Claude is a powerful large language model (LLM) developed by Anthropic, backed by Google. Co-founded by former OpenAI employees, Anthropic aims to build AI assistants that are helpful, honest, and harmless.

Key Features

• Claude v1 and Claude Instant models have shown great promise in multiple benchmark tests.

• In benchmark tests like MMLU and MT-Bench, Claude v1 performs comparably to GPT-4, scoring 7.94 and 75.6 points respectively, while GPT-4 scores 8.99 and 86.4 points.

• Anthropic introduced the Claude-instant-100k model, offering a context window of up to 100k tokens, allowing loading of close to 75,000 words in a single window.

Applications

• Anthropic's Claude models are suitable for various applications, including chatbots and AI assistants.

• Developers can explore tutorials on how to use Anthropic Claude for their projects.

5. LLaMA by Meta

Key Features

• Open-Source Development: Meta has embraced open-source with the release of LLaMA models, ranging from 7 billion to 65 billion parameters.

• Superior Performance: LLaMA-13B model surpasses GPT-3 from OpenAI in performance metrics, despite having fewer parameters.

• Community Engagement: The release of LLaMA sparked innovation within the open-source community, leading to the development of novel techniques for creating smaller and more efficient models.

• Data Utilization: Meta utilized publicly available data sources such as CommonCrawl, C4, GitHub, ArXiv, Wikipedia, and StackExchange to train the LLaMA models.

Applications

• Research Development: LLaMA models are primarily intended for research purposes, attracting developers to fine-tune and innovate within the open-source AI landscape.

• Community Collaboration: The availability of LLaMA fosters collaboration within the open-source community, encouraging the exploration of new methodologies and techniques for model improvement.

6. Falcon by Technology Innovation Institute (TII)

Key Features

• First Open-Source LLM: Falcon holds the distinction of being the first open-source large language model, surpassing other open-source models like LLaMA and StableLM.

• Developed by TII: Falcon is developed by the Technology Innovation Institute (TII), UAE, showcasing advancements in AI research from the Middle East.

• Apache 2.0 License: Released under the Apache 2.0 license, Falcon can be freely used for commercial purposes without any royalties or restrictions.

• Multiple Models: TII has released two Falcon models, with parameters ranging from 7 billion to 40 billion. The Falcon-40B-Instruct model is fine-tuned for chatting and other common use cases.

• Multilingual Support: While primarily trained in English, Falcon also supports several other languages including German, Spanish, French, Italian, Portuguese, Polish, Dutch, Romanian, Czech, and Swedish.

Applications

• Commercial Use: Falcon's Apache 2.0 license enables its utilization in commercial applications without any constraints, making it an attractive option for businesses seeking open-source AI models.

• Language Support: With support for multiple languages, Falcon can be deployed in various linguistic environments, catering to a diverse user base.

• Innovation in AI: Falcon's release marks a significant milestone in open-source AI development, encouraging further innovation and collaboration within the research community.

Choosing the right large language model (LLM) depends on your specific needs and use case. Here's a brief guide:

1. For General Purposes: If you need an LLM for various tasks such as creative writing, business planning, coding, translation, and scientific understanding, consider OpenAI's GPT-4 or GPT-3.5. They offer versatility and proficiency across a wide range of applications.

2. For Research and Collaboration: If you're involved in research or want to collaborate within the open-source community, Meta's LLaMA models could be ideal. They provide superior performance metrics and encourage innovation through community engagement.

3. For Commercial Use: If you're looking for an open-source model that can be used commercially, Falcon by TII offers a viable option. With its Apache 2.0 license and multilingual support, Falcon enables commercial applications without constraints.

4. For Specific Domains: If your application requires specialized knowledge in areas like commonsense reasoning, formal logic, or advanced coding, consider Google's PaLM 2 model. It excels in these domains and offers multilingual support.

5. For Ethical and Harmless AI: If ethical considerations and harmless AI interactions are crucial for your project, Anthropic's Claude models prioritize these principles. They aim to build AI assistants that are helpful, honest, and harmless.

Conclusion

The top 6 large language models (LLMs) of 2024 showcase remarkable advancements in AI. From OpenAI's GPT-4 to Meta's LLaMA and Google's PaLM 2, each model offers unique features and applications. Additionally, the emergence of open-source models like Falcon by TII signals a new era of accessibility and innovation in AI research. Together, these LLMs pave the way for enhanced natural language understanding and human-AI collaboration, promising a future of transformative possibilities.