Alibaba/Qwen

Latest AI news, models and releases from Alibaba/Qwen. ['CodeQwen1.5', 'Cotype Light 3', 'Cotype Pro 3', 'Fun-Realtime-TTS', 'Hanguang', 'Hanguang 800', 'HappyOyster 1.0', 'ICN Switch 1.0', 'not specified', 'Panjiu', 'Qianwen', 'Qoder Security', 'QVQ-72B-Preview', 'QVQ-Max', 'Qwen', 'Qwen 2', 'Qwen2.5', 'Qwen2.5-0.5B', 'Qwen2.5-14B', 'Qwen2.5-14B-Instruct-1M', 'Qwen2.5-1.5B', 'Qwen2.5-32B', 'Qwen2.5-3B', 'Qwen-2.5 72B', 'Qwen2.5-72B', 'Qwen2.5-7B', 'Qwen2.5-7B-Instruct-1M', 'Qwen2.5-Coder', 'Qwen2.5-Coder-0.5B', 'Qwen2.5-Coder-0.5B-Instruct', 'Qwen2.5-Coder-14B', 'Qwen2.5-Coder-1.5B', 'Qwen2.5-Coder-1.5B-Instruct', 'Qwen2.5-Coder-32B', 'Qwen2.5-Coder-32B-Instruct', 'Qwen2.5-Coder-3B', 'Qwen2.5-Coder-3B-Instruct', 'Qwen2.5-Coder-7B', 'Qwen2.5-Coder-7B-Instruct', 'Qwen2.5-Coder-Instruct']

Official site ↗

Harnesses 🇷🇺

Context Engineering: What It Is, How to Work with LLM Agent Context, and Why You Get Paid for It

Context engineering is a set of techniques for collecting and maintaining optimal context when working with LLMs. It differs from prompt engineering (which only handles instructions) and complements RAG (knowledge delivery) and MCP (tool integration). The article breaks down the layers of an agent's context, four typical failure scenarios (poisoning, distraction, confusion, conflict), and a context management approach through write, select, compress, isolate.

Anthropic

OpenAI

Google/DeepMind

Alibaba/Qwen

LangChain

Habr — хаб NLP27.07 · 09:05

Hardware & Inference 🇷🇺

LLM Inference: From KV-Cache to Production Deployment

MLOps engineer from hh.ru explains the fundamentals of LLM inference on on-premises hardware. The article covers KV-cache, inference engines vLLM and SGLang, attention mechanisms evolution (MHA, GQA, MLA, DSA), and practical recommendations for choosing hardware and parallelism schemes.

vLLM

SGLang