Kimi K2
Kimi K2 is a state-of-the-art open source large language model series built on a mixture-of-experts (MoE) architecture, featuring 1 trillion total parameters and 32 billion activated parameters for task-specific efficiency. Trained with the Muon optimizer on over 15.5 trillion tokens and stabilized by MuonClip’s attention-logit clamping, it delivers exceptional performance in frontier knowledge, reasoning, mathematics, coding, and general agentic workflows. Moonshot AI provides two variants, Kimi-K2-Base for research-level fine-tuning and Kimi-K2-Instruct pre-trained for immediate chat and tool-driven interactions, enabling both custom development and drop-in agentic capabilities. Benchmarks show it outperforms leading open source peers and rivals top proprietary models in coding tasks and complex task breakdowns, while its 128 K-token context length, tool-calling API compatibility, and support for industry-standard inference engines.
Learn more
Ministral 3
Mistral 3 is the latest generation of open-weight AI models from Mistral AI, offering a full family of models, from small, edge-optimized versions to a flagship, large-scale multimodal model. The lineup includes three compact “Ministral 3” models (3B, 8B, and 14B parameters) designed for efficiency and deployment on constrained hardware (even laptops, drones, or edge devices), plus the powerful “Mistral Large 3,” a sparse mixture-of-experts model with 675 billion total parameters (41 billion active). The models support multimodal and multilingual tasks, not only text, but also image understanding, and have demonstrated best-in-class performance on general prompts, multilingual conversations, and multimodal inputs. The base and instruction-fine-tuned versions are released under the Apache 2.0 license, enabling broad customization and integration in enterprise and open source projects.
Learn more
Qwen2
Qwen2 is the large language model series developed by Qwen team, Alibaba Cloud.
Qwen2 is a series of large language models developed by the Qwen team at Alibaba Cloud. It includes both base language models and instruction-tuned models, ranging from 0.5 billion to 72 billion parameters, and features both dense models and a Mixture-of-Experts model. The Qwen2 series is designed to surpass most previous open-weight models, including its predecessor Qwen1.5, and to compete with proprietary models across a broad spectrum of benchmarks in language understanding, generation, multilingual capabilities, coding, mathematics, and reasoning.
Learn more
MAI-1-preview
MAI-1 Preview is Microsoft AI’s first end-to-end trained foundation model, built entirely in-house as a mixture-of-experts architecture. Pre-trained and post-trained on approximately 15,000 NVIDIA H100 GPUs, it is designed to follow instructions and generate helpful, responsive text for everyday user queries, representing a prototype of future Copilot capabilities. Now available for public testing on LMArena, MAI-1 Preview delivers an early glimpse into the platform’s trajectory, with plans to roll out select text-based applications within Copilot over the coming weeks to gather user feedback and refine performance. Microsoft reinforces that it will continue combining its own models, partner models, and developments from the open-source community to flexibly power experiences across millions of unique interactions each day.
Learn more
