Top LLM Examples To Choose For Your Business Application

Large Language Models (LLMs) have been on exponential growth for the last couple of years in terms of their development and application. The global revenue market for LLMs is predicted to be USD 259.8 billion by 2030, with USD 105.5 billion in North America alone. There's a lot to explore and develop LLMs before we can tag it as an evolved technology. LLMs have impacted each life on the planet in one way or the other and it is now going towards becoming a need rather than a want. As the internet has revolutionized how humans interact with each other to network, LLMs are about to revolutionize how humans work on a day-to-day basis to operate.

LLMs are automating workflows and AI-powered business tools, powering chatbots, content tools, and search engines. However, using a single LLM to leverage all the services would be a fool's job as each LLM has its own sets of capabilities and USPs. We should have a mix of all to develop the best AI-driven business solutions, keeping in mind the cost associated with them to optimize them as per the business needs. In this blog, we are going to have a look at the capabilities of the popular LLMs used in the industry and how we can leverage them for our business requirements with their key differentiators.

1. ChatGPT

ChatGPT is a conversational AI developed and designed to generate human-like text for a variety of applications with training parameters of 175 billion for GPT 3.5 and probably more than 1 trillion (Not Disclosed) for GPT 4o. It excels in creative tasks, code generation, and tutoring.

Developer: OpenAI

Key Capabilities:

• Generates conversational, creative, and context-aware responses.
• Available in various versions (e.g., GPT-4o, GPT-4o mini).
• Supports multi-modal input/output.
• Ideal for writing, summarization, code generation, tutoring, and brainstorming.
• Extensive plugins and integration support (e.g., OpenAI Plugins, code interpreter).

Differentiator: Versatile across creative, technical, and general-purpose tasks; integrates well with third-party tools and services.

2. DeepSeek

DeepSeek, a Chinese AI company, has been naming itself in the LLM realm, designed to focus on specialized information retrieval and deep contextual search. The latest DeepSeek V3, launched in the last month of 2024, is trained with 671 billion MoE parameters. DeepSeek launched their reasoning model R1 which is at par with the OpenAI o1 model.

Developer: Chinese hedge fund High-Flyer

Key Capabilities:

• Focuses on specialized search and information extraction capabilities and has powerful reasoning capabilities.
• It can understand longer pieces of text to provide more relevant answers.
• Good at performing tasks such as mathematics and code generation.
• It doesn't need high-end GPUs to run.

Differentiator: (Details unclear, potentially tailored for niche tasks requiring in-depth search precision.)

3. Qwen

Alibaba Cloud launched the beta version of Qwen (QWQ) back in April 2023, with the updates leading to QwQ 2.5 as of early 2025. Qwen is a multimodal LLM optimized for enterprise applications, especially in logistics and e-commerce and their LLM for customer service is to be considered for businesses. It was initially developed with high proficiency in the Chinese language, making it a go-to solution for Chinese-language and translation-intensive scenarios. However, QwQ 2.5 has been equally good with the English language.

Developer: Alibaba Cloud

Key Capabilities:

• Multi-modal LLM capable of handling text, image, and more input data, enabling more comprehensive and nuanced interactions.
• Very proficient in generating and understanding codes from various programming languages.
• Optimized for enterprise scenarios like e-commerce, supply chain, and customer service.
• It comes with pretrained and instruction-tuned models of 7 sizes, including 0.5B, 1.5B, 3B, 7B, 14B, 32B, and 72B.

Differentiator: A go-to choice for developers and those involved in software development.

4. LLaMA (Large Language Model Meta AI)

LLaMA (Large Language Model Meta AI) is Meta's open-source family of language models, focused on NLP tasks, including text generation, translation, and question answering. It was primarily designed for researchers and developers to explore and advance the field of large language models. Its focus on scalability and efficient performance makes it ideal for fine-tuning and customization in both academic and industry-specific business applications of LLMs. The latest Llama 3.3 (text) has 70B parameters, with Llama 3.1 (text) 8B and 405B, and Llama 3.2's 1B and 3B are lightweight and 11B and 90B are multimodal LLMs.

Developer: Meta

Key Capabilities:

• Open-source LLM family optimized for research and fine-tuning.
• Scalable, with versions like LLaMA 2 designed for efficiency and lower compute requirements.
• Supports customization for specific use cases and industries.

Differentiator: Open-source availability allows developers to fine-tune the models for their own needs.

5. Claude

Claude, created by Anthropic, is a conversational LLM that emphasizes ethical and safe AI use. It is particularly adept at handling large contexts undefined reasoning, providing detailed responses, vision analysis, and multilingual processing, making it an excellent tool for tasks requiring reliability and depth. Anthropic doesn't publicly disclose the exact number of parameters for each of their Claude models, however, Claude Opus is the most powerful, Claude Sonnet is a mix of performance and speed, and Claude Haiku is the fastest to provide quick responses.

Developer: Anthropic

Key Capabilities:

• Emphasizes safety and ethical AI with better guardrails for harmful content.
• Provides detailed reasoning and long-context capabilities (e.g., summarizing books or large documents).
• User-friendly, conversational model designed for safe applications.

Differentiator: Strong focus on safety, ethical AI, and long-context comprehension.

6. Mistral

Mistral AI offers open-weight language models like Mistral Large 2 (123B parameters), focusing on high-performance AI for research and enterprise use. Its modular "Mixture of Experts" architecture allows developers to use targeted resources, enhancing efficiency. Mistral offers numerous other models both premium and open source versions for code generation, visual analysis, mathematical problem solving, and more.

Developer: Mistral AI

Key Capabilities:

• Open-weight models, designed for compactness and high performance.
• Offers models like Mistral Large 2 (most powerful amongst the lot) and Mix Models (Mixture of Experts) for enhanced modularity.
• Suitable for research and fine-tuning.

Differentiator: Efficient models optimized for customization and modularity.

7. Gemini

Gemini, developed by Google DeepMind, is a closed-source model that integrates advanced reasoning and reinforcement learning into a multi-modal LLM. Gemini 2.0 is their latest advancement in the LLM, focused more on AI Agents that can memory, reasoning, and planning to complete tasks. They have upcoming Gemini 2.0 family LLMs i.e. 2.0 Flash and 2.0 Flash Thinking (still in the experimental phase) for low latency and enhanced reasoning respectively. Gemini is built for scientific, technical, and general-purpose tasks, and reflects Google's cutting-edge AI research and infrastructure, offering unparalleled capabilities in problem-solving.

Developer: Google DeepMind

Key Capabilities:

• Combines LLM with advanced reasoning and reinforcement learning capabilities.
• Adherence to security standards like GDPR, HIPAA, or other relevant data protection laws.
• Focused on AI Agents for intelligent systems.
• Multi-modal support (text, images, etc.).
• Strong focus on scientific and technical applications.

Differentiator: Incorporates Google’s vast AI research and infrastructure, making it cutting-edge in reasoning and generalizability.

8. Command

Cohere developed Command, with Command R7B (7B parameters for speed undefined efficiency)their latest release, specialized in business-focused natural language processing tasks. It is tailored for summarization, classification, and contextual understanding, making it a powerful tool for enterprises looking to extract actionable insights from textual data. The flagship Command R and R+ are focused on providing powerful performance focused on RAG without citations, making them the best LLMs for enterprises who want to customize according to their industry. Ayna Expanse has 8B and 32B parameter model versions, designed to be highly performant and multilingual oriented.

Developer: Cohere

Key Capabilities:

• Focused on text understanding and generation tasks.
• Specializes in business-focused use cases like summarization, classification, and entity extraction.
• Supports retrieval-augmented generation (RAG) for enhanced contextual accuracy, and the latest release doesn't need citations.
• Focused on generating AI Agents.

Differentiator: Tailored for enterprise-specific applications with emphasis on NLP and contextual understanding.

Summary of LLM Examples

• General-purpose LLMs: ChatGPT, Claude, and Gemini excel in diverse tasks and conversations.
• Enterprise-focused LLMs: Qwen, Command, and Claude target business use cases.
• Open-source/Research-friendly: LLaMA and Mistral prioritize accessibility and customizability.
• Safety and Ethics: Claude leads the prioritization of responsible AI.
• Specialized/Niche: DeepSeek focuses on specialized information retrieval.

End Note

The landscape of Large Language Models (LLMs) is dynamic and rapidly evolving. We explored a range of LLM examples with their own strengths and specializations. We explored ChatGPT's conversational prowess, DeepSeek's information retrieval focus, Qwen's open-source nature, and Claude's emphasis on safety, LLMs example caters to a wide range of requirements. Llama has a research-driven approach, Mistral is focused on efficiency, Gemini's AI-agent focus is unparalleled, and Command's RAG without citation further illustrates how LLMs are progressing day after day. However, precise parameter counts are often kept confidential for a competitive edge, each LLM example has a unique proposition for users seeking the right LLM for their specific applications. You need to analyze the task at hand, weighing factors like performance, cost, safety, and accessibility to choose the best LLM. Stay informed about the latest advancements to leverage the full potential of LLMs.

We, at Seaflux, are AI undefined Machine Learning enthusiasts, who are helping enterprises worldwide. Have a query or want to discuss AI projects where SLMs undefined LLMs can be leveraged to improve business operations? Schedule a meeting with us here, we'll be happy to talk to you.