AI Model Catalogue

OpenAI's most capable frontier model for complex professional work, coding, and multi-step reasoning.

Grok 4 is xAI’s most advanced reasoning model. Excels at logical thinking and in-depth analysis. Ideal for insightful discussions and complex problem-solving.

Google's most intelligent model, with improved reasoning and a new medium thinking level

Kimi K2 Thinking is the latest, most capable version of an open-source thinking model.

A reasoning model trained with reinforcement learning, on par with OpenAI o1

DeepSeek-V3-0324 is the leading non-reasoning model, a milestone for open source

Latest hybrid thinking model from Deepseek

Generate and edit high-quality images with Alibaba's Wan 2.7 Pro with 4K output, thinking mode, text-to-image, multi-image editing, and image set generation

Open-source HyperCLOVAX-SEED-Think-14B-GPTQ model from k-compression — available for download and self-hosting on Hugging Face.

kimi-k2-thinking — available to run locally via Ollama on CPU and GPU hardware.

Open-source Qwen3-4B-Thinking-2507 model from qwen — available for download and self-hosting on Hugging Face.

Qwen3 235B A22B is Alibaba's flagship mixture-of-experts model with 235B total parameters and 22B active per token. Delivers frontier-level performance on coding, reasoning, and multilingual tasks at significantly lower inference cost.

Falcon 180B is one of the largest openly available language models, trained on 3.5 trillion tokens with TII's custom RefinedWeb dataset. Excels at reasoning, summarization, and generation tasks at state-of-the-art quality for open models.

DBRX Instruct is an open, general-purpose LLM from Databricks. Built with a fine-grained mixture-of-experts (MoE) architecture, it was the most capable open LLM at launch and excels at code, math, and language tasks.

NVIDIA Nemotron-4 340B Instruct is a large open language model trained to generate diverse synthetic data for training other LLMs. Strong at following instructions, classification, and generating reward model training data.

Microsoft Phi-4 Mini is a 3.8B parameter compact model from Microsoft. Delivers impressive reasoning capabilities for edge and mobile deployment scenarios, with strong performance on math and coding tasks relative to its size.

OpenAI's flagship model, GPT-4 is a large-scale multimodal language model capable of solving difficult problems with greater accuracy than previous models due to its broader general knowledge and advanced reasoning...

This is Mistral AI's flagship model, Mistral Large 2 (version `mistral-large-2407`). It's a proprietary weights-available model and excels at reasoning, code, JSON, chat, and more. Read the launch announcement [here](https://mistral.ai/news/mistral-large-2407/)....

Hermes 3 is a generalist language model with many improvements over Hermes 2, including advanced agentic capabilities, much better roleplaying, reasoning, multi-turn conversation, long context coherence, and improvements across the...

Hermes 3 is a generalist language model with many improvements over [Hermes 2](/models/nousresearch/nous-hermes-2-mistral-7b-dpo), including advanced agentic capabilities, much better roleplaying, reasoning, multi-turn conversation, long context coherence, and improvements across the...

command-r-08-2024 is an update of the [Command R](/models/cohere/command-r) with improved performance for multilingual retrieval-augmented generation (RAG) and tool use. More broadly, it is better at math, code and reasoning and...

Llama 3.2 3B is a 3-billion-parameter multilingual large language model, optimized for advanced natural language processing tasks like dialogue generation, reasoning, and summarization. Designed with the latest transformer architecture, it...

Qwen2.5-Coder is the latest series of Code-Specific Qwen large language models (formerly known as CodeQwen). Qwen2.5-Coder brings the following improvements upon CodeQwen1.5: - Significantly improvements in **code generation**, **code reasoning**...

This is Mistral AI's flagship model, Mistral Large 2 (version mistral-large-2407). It's a proprietary weights-available model and excels at reasoning, code, JSON, chat, and more. Read the launch announcement [here](https://mistral.ai/news/mistral-large-2407/)....

Command R7B (12-2024) is a small, fast update of the Command R+ model, delivered in December 2024. It excels at RAG, tool use, agents, and similar tasks requiring complex reasoning...

The latest and strongest model family from OpenAI, o1 is designed to spend more time thinking before responding. The o1 model series is trained with large-scale reinforcement learning to reason...

[Microsoft Research](/microsoft) Phi-4 is designed to perform well in complex reasoning tasks and can operate efficiently in situations with limited memory or where quick responses are needed. At 14 billion...

DeepSeek R1 is here: Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active in an inference pass....

OpenAI o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and coding. This model supports the `reasoning_effort` parameter, which can be set to...

Aion-1.0-Mini 32B parameter model is a distilled version of the DeepSeek-R1 model, designed for strong performance in reasoning domains such as mathematics, coding, and logic. It is a modified variant...

Aion-1.0 is a multi-model system designed for high performance across various tasks, including reasoning and coding. It is built on DeepSeek-R1, augmented with additional models and techniques such as Tree...

OpenAI o3-mini-high is the same model as [o3-mini](/openai/o3-mini) with reasoning_effort set to high. o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and...

Claude 3.7 Sonnet is an advanced large language model with improved reasoning, coding, and problem-solving capabilities. It introduces a hybrid reasoning approach, allowing users to choose between rapid responses and...