Large Language Models (LLMs) as of January 2025

By early 2025, numerous advanced Large Language Models (LLMs) have been developed, each with unique features tailored to specific applications. Below is a comprehensive overview of some of the most notable LLMs:

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1. GPT-4

• Developer: OpenAI
• Key Features: A multimodal model capable of processing both text and images, with rumored parameters exceeding 170 trillion.

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2. Claude

• Developer: Anthropic
• Key Features: Known for its advanced conversational abilities and safety features, making it suitable for tasks ranging from dialogue systems to coding.

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3. Gemini

• Developer: Google AI
• Key Features: Previously known as Bard, this multimodal model excels at real-time data access, text generation, language translation, and coding tasks.

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4. LLaMA (Large Language Model Meta AI)

• Developer: Meta
• Key Features: Open-source with versions scaling up to 405 billion parameters, designed for a variety of applications including text and image processing.

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5. Mistral Large 2

• Developer: Mistral
• Key Features: Offers 123 billion parameters with an extended context window of 128,000 tokens, optimized for computational efficiency and document processing.

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6. Vicuna

• Developer: LMSYS
• Key Features: Built on LLaMA, this model is fine-tuned with conversational data, improving its performance in real-world applications.

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7. OLMo 2

• Developer: Allen Institute for AI (Ai2)
• Key Features: Available in 7B and 13B parameter versions, particularly strong in question answering and summarization tasks.

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8. StableLM

• Developer: Stability AI
• Key Features: Open-source with parameter sizes ranging from 3B to 175B, recognized for its flexibility and broad applicability.

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9. Cohere

• Developer: Cohere Inc.
• Key Features: An open-source model trained on a diverse dataset, excelling in handling multiple languages and accents.

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10. GLM-130B

• Developer: Tsinghua University
• Key Features: A powerful model designed for various natural language processing tasks.

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11. DeepSeek

• Developer: Unknown
• Key Features: Gained recognition for its innovative approach to language understanding.

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12. Qwen

• Developer: Unknown
• Key Features: Delivers strong performance across a wide range of NLP tasks.

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13. Phi-1

• Developer: Microsoft
• Key Features: A compact model with 1.3 billion parameters, highly effective in Python coding tasks.

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14. Gemma

• Developer: Google (Open Source)
• Key Features: Offered in 2B and 7B parameter variants, providing efficient performance for local applications.

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Conclusion

The LLM landscape by January 2025 highlights rapid innovation, showcasing models with varied capabilities from multimodal processing to domain-specific optimizations. These advancements reflect the growing diversity in AI technologies, offering solutions for a wide range of industries and applications.

Comparison of Large Language Models (LLMs) as of January 2025

Comparison of Large Language Models (LLMs) as of January 2025

Here is an updated comparison of notable LLMs available by January 2025:

Here’s a comparative table of notable large language models (LLMs) available by January 2025, highlighting their key features, parameters, and capabilities:

Model Name	Developer	Parameters	Multimodal Capabilities	Key Features	Use Cases
GPT-4	OpenAI	1.5 Trillion	Yes	Advanced reasoning, strong performance across benchmarks	General AI applications, coding
Claude	Anthropic	52 Billion	No	Strong conversational abilities, safety-focused	Customer support, content generation
Gemini	Google AI	1.6 Trillion	Yes	Real-time data access, strong reasoning capabilities	Research, content creation
LLaMA 3.2	Meta	Up to 405 Billion	Yes	Open-source, versatile for various applications	Education, marketing
Mistral Large 2	Mistral	123 Billion	No	High efficiency, excels in coding tasks	Software development
Vicuna	LMSYS	Up to 13 Billion	No	Fine-tuned for conversational context	Chatbots, personal assistants
OLMo 2	Allen Institute	7B / 13B	No	Strong in question answering and summarization	Educational tools
StableLM	Stability AI	3B – 175B	No	Open-source and versatile	Various NLP tasks
GLM-130B	Tsinghua University	130 Billion	No	Strong natural language processing capabilities	Research and development
DeepSeek	Unknown	Undisclosed	No	Innovative language understanding	General AI applications
Qwen	Unknown	Undisclosed	No	Competitive performance in NLP tasks	Various applications

This table summarizes the key aspects of each model, providing a clear overview of their capabilities and potential applications in various fields.

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Insights:

1. Multimodal Capabilities: Models like GPT-4 and Gemini excel with text and image processing, making them versatile for creative and analytical tasks.
2. Open-Source Advantages: LLaMA, StableLM, and Gemma offer accessibility for developers to build custom applications.
3. Coding Specialization: Phi-1 (Microsoft) and Claude (Anthropic) stand out in programming-related tasks.
4. Efficiency Models: Mistral Large 2 and StableLM provide options for computational efficiency and long-context tasks.
5. Multilingual Excellence: Cohere and StableLM are strong contenders for multilingual NLP tasks.

This table reflects the diversity and rapid advancements in LLMs, catering to a broad spectrum of industries and applications by January 2025.