Search Results for "active shape model"

Qwen3-Coder is the latest and most powerful agentic code model developed by the Qwen team at Alibaba Cloud. Its flagship version, Qwen3-Coder-480B-A35B-Instruct, features a massive 480 billion-parameter Mixture-of-Experts architecture with 35 billion active parameters, delivering top-tier performance on coding and agentic tasks. This model sets new state-of-the-art benchmarks among open models for agentic coding, browser-use, and tool-use, matching performance comparable to leading models like Claude Sonnet. ...

MiniMax-M2 is an open-weight large language model designed specifically for high-end coding and agentic workflows while staying compact and efficient. It uses a Mixture-of-Experts (MoE) architecture with 230 billion total parameters but only 10 billion activated per token, giving it the behavior of a very large model at a fraction of the runtime cost. The model is tuned for end-to-end developer flows such as multi-file edits, compile–run–fix loops, and test-validated repairs across real...

Gemini CLI is an open‑source AI agent that brings the capabilities of Google’s Gemini 2.5 Pro large‑language model directly into your terminal, enabling tasks ranging from coding and debugging to content creation and research via natural‑language prompts, with support for multimodal outputs like image and video generation. Gemini CLI integrates with external tools and MCP servers, enabling media generation and enhanced workflow automation. It also includes a built-in Google Search tool to...

agentsview is a local-first analytics and session browser for developers using AI coding agents. It indexes conversations from tools like Claude Code, Codex, Gemini CLI, Cursor, OpenHands, and many other agent systems. The project lets users browse, search, and analyze coding-agent activity without creating an account or sending session content to a hosted service. It tracks token usage, cost, models, projects, tools, and session behavior across different agents. Its web interface adds...

Kimi K2.7 Code is a coding-focused agentic model built on Kimi K2.6, designed for long-horizon software engineering, autonomous coding workflows, and complex tool-based execution. It improves end-to-end task completion across real-world programming scenarios while reducing thinking-token usage by about 30% compared with K2.6. Architecturally, it uses a 1T-parameter Mixture-of-Experts design with 32B activated parameters, 61 layers, 384 experts, a 256K-token context window, and a MoonViT...