Browse AI Models

Mistral

Codestral 2 is Mistral AI's latest code-focused model with enhanced performance on code generation, refactoring, and documentation across dozens of programming languages.

Mistral

Devstral is an agentic LLM for software engineering tasks built under a collaboration between Mistral AI and All Hands AI 🙌. Devstral excels at using tools to explore codebases, editing multiple files and power software engineering agents. The model achieves remarkable performance on SWE-bench which positions it as the #1 open source model on this benchmark.

Meta

Llama 3.1 70B is Meta's high-capability open model with 128K context window. Excels at complex reasoning, multilingual tasks, code generation, and tool use with quality competitive with leading proprietary models.

NVIDIA

Llama-3.1-Nemotron-70B-Instruct is a large language model customized by NVIDIA to improve the helpfulness of LLM generated responses to user queries.

Mistral AI

Pixtral-Large-Instruct-2411 is a 124B multimodal model built on top of Mistral Large 2, i.e., Mistral-Large-Instruct-2407. Pixtral Large is the second model in our multimodal family and demonstrates frontier-level image understanding. Particularly, the model is able to understand documents, charts and natural images, while maintaining the leading text-only understanding of Mistral Large 2.

Alibaba

> [!Warning] > > > 🚨 Qwen2.5-Math mainly supports solving English and Chinese math problems through CoT and TIR. We do not recommend using this series of models for other tasks. > >

Cohere

Command R+ is Cohere's most capable open-weight model for enterprise RAG workloads. Offers superior long-context reasoning, multi-step tool use, and grounded generation with citations across 10 languages.

DeepSeek

We present DeepSeek-Coder-V2, an open-source Mixture-of-Experts (MoE) code language model that achieves performance comparable to GPT4-Turbo in code-specific tasks. Specifically, DeepSeek-Coder-V2 is further pre-trained from an intermediate checkpoint of DeepSeek-V2 with additional 6 trillion tokens. Through this continued pre-training, DeepSeek-Coder-V2 substantially enhances the coding and mathematical reasoning capabilities of DeepSeek-V2, while maintaining comparable performance in general language tasks.

DeepSeek

We introduce our first-generation reasoning models, DeepSeek-R1-Zero and DeepSeek-R1. DeepSeek-R1-Zero, a model trained via large-scale reinforcement learning (RL) without supervised fine-tuning (SFT) as a preliminary step, demonstrated remarkable performance on reasoning. With RL, DeepSeek-R1-Zero naturally emerged with numerous powerful and interesting reasoning behaviors. However, DeepSeek-R1-Zero encounters challenges such as endless repetition, poor readability, and language mixing.

Meta

Llama 4 Scout is Meta's efficient Mixture-of-Experts model with 17B active parameters across 16 experts. Supports a 10M token context window and natively handles text, images, and video inputs.

Alibaba

We introduce the updated version of the Qwen3-30B-A3B non-thinking mode, named Qwen3-30B-A3B-Instruct-2507, featuring the following key enhancements:

BigCode

StarCoder 15B is BigCode's flagship code generation model trained on 1 trillion tokens from The Stack. Supports 80+ programming languages with 8K context and strong code completion capabilities.

DeepSeek

DeepSeek-V2.5 is an upgraded version that combines DeepSeek-V2-Chat and DeepSeek-Coder-V2-Instruct. The new model integrates the general and coding abilities of the two previous versions. For model details, please visit DeepSeek-V2 page for more information.