WeDLM

« 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 »

« 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»

« 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 »

« 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 »

« A multimodal model with 552B parameters, of which only 8B are active at the input stage, featuring native visual understanding and accessible via API for your applications. This open-source model uses a Causal Encoder-Decoder architecture to respond to your text and image queries »

« 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 »

« 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 »

« Take advantage of Anthropic’s AI model—more reliable, more honest, and four times less likely to overlook its own errors. Its fast mode delivers up to 2.5 times more tokens per second (at the same API rate as the previous version) »