Top LLMs for AI Agents in 2025

As we head into 2025, the landscape of large language models continues to evolve. We will have models until the last week of 2024, and there have been significant advancements in reasoning, multimodality, and cost-efficiency. Understanding the current standings is crucial.

Whether building intelligent assistants or deploying multipurpose AI Agents at scale, this guide will help you explore the versatility and deployment options available for the top foundational models.

Understanding Large Language Models

LLMs have surpassed their original purpose of text generation, now excelling in reasoning, multimodal tasks, and tool usage. How do you go about choosing a LLM? Two broad categories are setting the precedence for the sphere. 

Top Open Source LLMs

Open-source LLMs are community-driven models that can be customized and deployed freely. Their transparency and adaptability have made them popular among researchers and smaller enterprises.

Leading open-source models for 2025 include:

• Qwen 2.5 7B: A compact, high-performing open-source model optimized for efficiency and versatility.

• LLaMA 3.1 70B: Meta's latest model, praised for balancing capability and resource efficiency.

• Phi 3.5: A lightweight mixture-of-experts, with a focus on high-quality reasoning.

Top Closed-Source LLMs

Closed-source LLMs are proprietary models backed by significant R&D investments prioritizing peak performance, reliability, and enterprise-grade support. 

Leading closed-source models for 2025 include:

• Claude 3.5 Sonet: A model focused on safety, ethical reasoning, and user-aligned responses.

• Gemini 2.0 Flash: A highly advanced multimodal model that seamlessly integrates text and visual inputs.

• GPT-4o (Aug 24’): A gold standard in generative AI, excelling in reasoning, summarization, and contextual understanding.

As the lines between open and closed ecosystems blur, developers can now access models that deliver extraordinary results on any platform. 

Top LLMs in 2025

In 2024, LLMs surpassed their predecessors, moving beyond just the accessibility of weights. A significant shift toward explainability and interpretability emerged, paving the way for more advanced reasoning models. 

Alongside this, the rise of multimodal capabilities opened new frontiers in audio, video, and image processing. These advancements have led to the developing of knowledgeable and capable AI agents, which are now being adopted across various domains.

Best Reasoning

Reasoning or “O1” models are intelligent LLMs designed to analyze, reason, and thoughtfully respond to complex prompts. Unlike their impulsive "generative" counterparts, reasoning models excel in logical processes, making them ideal for advanced research, unexplored concepts, and intricate problem-solving.

True to its namesake, the top reason LLMs to present itself this year was GPTo1. Launched in September, the model took its complete form at the end of the year, when the final model was revealed to be the leader in most analytical and reasoning benchmarks.

Alternatives, Qwen QwQ 32B and DeepSeekR1, were some of the closest contenders, but for some, the best because of the Open-Source nature of both.

Best Multi-Modal

Multimodal models integrate text, images, and audio for tasks like image interpretation or caption generation. They excel in fields requiring a blend of visual and textual understanding, making them invaluable for content creation and data analysis.

Moving against the Closed-Source Leaders, Llama 3.2 90B truly set a precedent for pricing vs performance for vision models. A field dominated mainly by GPT-4v and GPT-4o, the model opened more doors for developers with prospects of finetuning for specialized use cases.

Alternatives, Qwen 2 VL and Pixtral 12B were other open-source models that excelled at various benchmarks.

Best Tool Usage

Models designed for tool usage act as AI assistants, automating workflows and interacting with APIs or databases. They help developers create intelligent agents that integrate smoothly into existing systems.

Anthropic Claude, leading with its Sonnet and Haiku series high-level instruction following. Invoking tools, APIs, and even computer use, the models emerged as a leading choice for customer-facing agents.

“Claude 3.5 Haiku is well suited for user-facing products, specialized sub-agent tasks, and generating personalized experiences from huge volumes of data.”

~ Anthropic

Alternatives: GPT4o, with its internal OpenAI tool usage, presents itself as one of the most versatile and widely adopted Closed-Source LLM for AI Agents.

Cost Effective

Cost-effective models, like Mistral 7B and LLaMA 3.1, offer outstanding performance at a lower price point. These models provide scalable solutions without compromising quality, making them ideal for budget-conscious projects.

As the year turned, so did the SOTA for many Benchmarks. DeepSeekv3, from China, challenges existing foundational models by performing exceptionally well in English, Coding, and Mathematics. The mixture-of-experts model is one of the cheapest to run and faces no competition in most generative tasks.

Alternatives, such as Llama 3.3 70B and Qwen 72B, are some other competent mid-level foundational models.

Deploy the Latest LLMs as Agents for Free

If you want to deploy any of these LLMs as agents, explore the large language models available on Tune Studio to find the right fit. Features like BYOC make it easy to connect databases and get workflows running.

Are you looking for help understanding what LLM fits your use case? Talk to us today, and start 2025 with an AI-driven solution that powers your workflows, boosts productivity, and transforms your operations.