Discovering the Buzzworthy LLMs of 2025: The Top 5 Pioneers Accross All Modalities
In the rapidly evolving world of artificial intelligence, language and multimodal models continue to push the boundaries of what is possible. As of mid-2025, HuggingFace leaderboards and related evaluations have identified the top performing Large Language Models (LLMs) in each major modality category.
For text modalities, models like Gemma-2-9B, Llama-3.1, and Qwen-2.5-IT dominate HuggingFace’s multilingual leaderboards. These models consistently rank in the top 10 for Spanish varieties and multilingual benchmarks, with strong performance across various NLP tasks like NLI, reasoning, and QA.
However, code and image LLM leaderboards on HuggingFace are less explicitly reported in the sources. Models like LLaMA derivatives linearized with Lizard show efficiency improvements but no top rank data is available. For code models, consulting the HuggingFace model hub leaderboards directly or specialized benchmarks like OpenAI’s Codex evaluations would be recommended.
In the realm of image generation, models like Stable Diffusion or similar diffusion models lead in image generation tasks but are not covered in the provided search results, typically tracked on different platforms.
The multimodal LLM leaderboards exist, with a growing focus on language proficiency and task versatility. However, specific top models are not detailed in the latest publicly available sources. A taxonomy and evaluation pipeline for multimodal LLMs is available on HuggingFace, but top-ranked models are not explicitly listed in the results.
Some notable mentions in the multimodal category include DeepSeek V3, an ultra-large language model with approximately 671 billion parameters, designed for complex reasoning and multilingual understanding. Llama 4, created by Meta, is a multimodal model with a mixture of experts architecture, supporting text and image inputs.
In the code generation sector, Mistral Small 3.1, created by Mistral AI, is a 24B-parameter model that excels in text generation tasks, offering efficient performance on accessible hardware configurations. Codex, designed for code generation tasks, capable of understanding and generating code in multiple programming languages, was created by OpenAI. Code Llama, a model optimized for code generation tasks, trained on a diverse dataset of programming languages, was created by Meta.
Lastly, Runway Gen-2, created by Runway, generates images and videos from text prompts, offering creative possibilities for multimedia content.
As AI continues to advance, it is exciting to see the progress being made in these various modalities. For more specific rankings or model names, consulting the HuggingFace model hub leaderboards directly or specialized benchmarks would be recommended.
Artificial intelligence has made significant strides in data-and-cloud-computing, as evidenced by the dominance of models like Gemma-2-9B, Llama-3.1, and Qwen-2.5-IT in HuggingFace’s multilingual leaderboards for text modalities. However, top-ranked models in code generation, such as Mistral Small 3.1 and Codex, and image generation, like Stable Diffusion, may not be found on HuggingFace's provided search results, necessitating the use of direct model hub leaderboards or specialized benchmarks for more detailed information.
