{"slug": "minimax-m3-how-sparse-attention-makes-long-horizon-agents-practical", "title": "MiniMax M3: How Sparse Attention Makes Long-Horizon Agents Practical", "summary": "MiniMax M3 introduces sparse attention to make long-horizon agents practical, according to a post by elvis@omarsar0. The model aims to improve efficiency for AI agents operating over extended timeframes, contrasting with the recent focus on GLM 5.2 versus Opus comparisons.", "body_md": "https://t.co/v9huIornsf\n\nelvis@omarsar0ArticleMiniMax M3: How Sparse Attention Makes Long-Horizon Agents Practical GLM 5.2 has taken over much of the AI timeline lately, and most of the conversation has centered on how it stacks up against Opus. That is the headline. The workload tells a quieter story: the...2:04 PM · Jul 7, 2026202.1KViews5056065605673073Read 5 replies", "url": "https://wpnews.pro/news/minimax-m3-how-sparse-attention-makes-long-horizon-agents-practical", "canonical_source": "https://twitter.com/omarsar0/status/2074494774292148726", "published_at": "2026-07-21 02:51:43+00:00", "updated_at": "2026-07-21 03:23:24.694727+00:00", "lang": "en", "topics": ["artificial-intelligence", "ai-agents", "ai-research"], "entities": ["MiniMax", "M3", "GLM 5.2", "Opus"], "alternates": {"html": "https://wpnews.pro/news/minimax-m3-how-sparse-attention-makes-long-horizon-agents-practical", "markdown": "https://wpnews.pro/news/minimax-m3-how-sparse-attention-makes-long-horizon-agents-practical.md", "text": "https://wpnews.pro/news/minimax-m3-how-sparse-attention-makes-long-horizon-agents-practical.txt", "jsonld": "https://wpnews.pro/news/minimax-m3-how-sparse-attention-makes-long-horizon-agents-practical.jsonld"}}