LLMs: Top Models of 2025
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Top LLMs of 2025: A Global Guide
This guide covers leading Large Language Models (LLMs), organized by type, company, origin country, and best use cases. Entries are sorted alphabetically by model/tool name within country groups for easy navigation. Data is based on publicly available info as of 2025.
Large Language Models (LLMs)
These are versatile AI models for tasks like text generation, reasoning, and multimodality. Grouped by origin country.
Canada
| Model | Company | Best For |
|---|---|---|
| Cohere | Cohere | Enterprise-focused natural language understanding; excels in summarization, search, and custom fine-tuning |
China
| Model | Company | Best For |
|---|---|---|
| Baichuan | Baichuan | Open-source model for enterprise use with multi-modal capabilities (text, images, video, audio) |
| ByteDance Models | ByteDance | Expanding from consumer apps to enterprise tools, with a focus on multilingual applications |
| DeepSeek | DeepSeek | High-performance LLMs, with DeepSeek-Coder for specialized coding tasks |
| Ernie Bot | Baidu | General-purpose LLM, one of the first approved for public use in China |
| GLM | Zhipu AI | Models optimized for tool use and agentic workflows |
| Hunyuan | Tencent | Generative model suite for enterprise and cloud applications |
| Kimi | Moonshot AI | Multimodal LLM with agentic capabilities for planning and executing tasks |
| MiniMax Models | MiniMax | Models with code-native language frameworks for code generation and debugging |
| Qwen | Alibaba | Multilingual and coding capabilities, with specific variants for coding |
| Qwen3 | Alibaba | Advanced successor to Qwen; strong in academic writing, semantic similarity, and large-scale content generation (e.g., 235B parameters) |
| RWKV | RWKV | Efficient recurrent architecture for long-context tasks; open-source with strong bilingual and coding efficiency |
| Yi | 01.AI | Exceptional bilingual (Chinese-English) performance |
France
| Model | Company | Best For |
|---|---|---|
| Mistral | Mistral AI | Lightweight, efficient models for deployment; strong in coding, multilingual tasks, and open-source customization |
United States
| Model | Company | Best For |
|---|---|---|
| Claude | Anthropic | Advanced reasoning, ethical AI interactions, and long-context tasks; strong in coding and agentic workflows |
| Gemini | Multimodal processing (text, images, video); ideal for search-integrated tasks, translation, and creative generation | |
| Gemini 2.5 Pro | Enhanced multimodal capabilities for complex reasoning, coding, and integration with tools like Google Workspace | |
| GPT | OpenAI | General-purpose tasks like creative writing, reasoning, and chat; excels in multimodal (text, image, voice) applications |
| GPT-5 | OpenAI | Cutting-edge advancements in reasoning, creativity, and large-scale data processing; reshapes AI for global tech innovation |
| Grok | xAI | Witty, conversational AI with real-time knowledge integration; good for humor-infused queries and exploratory discussions |
| Llama | Meta | Foundational open-source model for research; efficient on benchmarks with sizes from 1B to 65B parameters |
| Llama 2 | Meta | Open-source fine-tuning for custom applications; strong in bilingual tasks and efficiency on consumer hardware |
| Llama 3 | Meta | Improved reasoning and coding; versatile for open-source deployments in research and enterprise |
| Llama 3.1 | Meta | Expanded context length, multilingual support (8 languages), and frontier-level performance for open-source AI |
| Llama 4 | Meta | Next-gen advancements in efficiency, multimodality, and performance; includes variants like Scout and Maverick for top efficiency |
| PaLM | Predecessor to Gemini; excels in reasoning benchmarks and large-scale data processing |