Liquid AI

« Alibaba's very large, multimodal, open-source model. Performs particularly well on coding, research, or long, autonomous tasks. Supports a context size of up to 1 million tokens»

« A powerful LLM model designed for coding, research, and long-running agentic tasks, featuring 500,000 tokens of context, tool calls, and fine-tuned reasoning effort. Available directly in Cursor and Grok Build »

« Anthropic's LLM model for coding, research, and long, complex tasks. With improved performance and reduced costs on agent-based workloads. It also produces far fewer false security alerts »

« A fast and cost-effective model designed for code, agents, and complex workflows, with a 1-million-token context and significant improvements on long-running tasks and multi-step execution. Compared to its predecessor, this model scores 9 points higher on FrontierCode 1.1 and 16 points higher on DeepSWE v1.1 »

« Anthropic's latest high-end model, optimized for agentic code, long-running tasks, and critical business scenarios. It features self-checking of responses and a context window of one million tokens. It is also capable of automatically adjusting the depth of its reasoning based on the difficulty of the problem »

« Tackle time-consuming and complex tasks by letting AI plan, use tools, check its work, and see tasks through to completion with minimal supervision. This model significantly improves coding, the use of virtual machines, online research, and knowledge work tasks »

« Moonshot's LLM model, which rivals the best proprietary models on numerous benchmarks. Designed for long-form coding, advanced reasoning, and knowledge work tasks, it is also the first open-source model to surpass the 2.8 trillion-parameter mark »

« A long-term coding and agent model based on GLM-5.2, featuring enhanced training, a 1-million-token context, and always-active reasoning that can be adjusted across three levels. This LLM stands out for its performance in logical reasoning and semantic understanding. »