Rama LLAMA Ding Dong — an overview of four key LLMs: GPT, Llama, Claude and Bard

Photo by Paul Lequay on Unsplash

The launch of ChatGPT last November made a big splash. More than half a year later it is no longer the only game in town and many alternative large language models (LLMs) with slightly different strengths and weaknesses have been released. An LLM is a trained deep-learning model that understands and generates text in a human-like fashion. Just this week, Meta launched its Llama2 and made it widely available.

Here’s a high-level summary of four key LLMs, including their associated advantages and challenges.

OpenAI / GPT 4.0 (Microsoft)

• Advanced language understanding and generation capabilities for a wide range of topics.
• Impressive coding ability and sophisticated word choice
• Suitable for content creation and coding tasks.
• However, criticized for lack of transparency in model training process and the model is only available by using one of OpenAI’s services like user interfaces or APIs.

Llama 2.0 (Meta)

• Exceptional performance in generating helpful responses for single and multi-turn prompts.
• Suitable for chat applications and tasks requiring human interaction.
• However, comparatively lower coding capability.
• Open-source nature allows the model to be run in a company’s environment and larger control to finetune it to the specific domain and use cases.

Claude 2.0 (Anthropic)

• Excellent at tasks involving coding, mathematics, logical thinking, and document understanding.
• Proficient in processing large documents including PDFs, a challenging task for other models that are more limited regarding the maximum input size.
• Impressive Python coding skills, scoring 71.2% on Codex HumanEval.
• Similar to GPT 4.0, accessible via an API but not fully open source.

Bard (Google)

• Designed for conversational AI applications, capable of generating human-like responses and providing advice, answering questions, and generating content.
• Draws on information from the web to provide fresh, high-quality responses.
• Limited in comparison to GPT-4, particularly in providing specific and accurate responses for certain tasks like CSS coding.
• Currently not recommended to use at StSt because it doesn’t allow to block data sharing with Google.

Sources:

• The New Era of Generative AI: Unveiling GPT 4.0, Llama 2.0 and Claude 2.0
• Llama 2 vs GPT-4 vs Claude-2

Co-authored by Felicitas von Rauch, Timm Lochmann and Heinke Hihn

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