Z.ai 發表 GLM-5.2：具備可用 100 萬 Token 上下文、兩種思考努力層級，發表時未附基準測試

GLM-5.2 is the latest large language model from Z.ai, becoming the third major release in the GLM-5 line. It follows GLM-5 (February 11), GLM-5-Turbo (March 15), and GLM-5.1 (April 7). That makes four flagship-tier coding releases in roughly four months. Usable 1M-Token Context Window GLM-5.2’s standout spec is a 1,000,000-token context window. Z.ai labels the variant glm-5.2[1m] in its own configuration. Each response can return up to 131,072 output tokens. That is roughly a 5x jump from GLM-5.1’s 200,000-token window. A 1M-token window changes how a coding agent works in practice. The agent can hold an entire mid-sized repository in working memory. That includes source files, tests, configuration, and conversation history. It avoids the constant summarization that smaller windows force. The release also adds two thinking-effort levels: High and Max. Z.ai recommends Max effort for complex, multi-step coding work. In Claude Code, the /effort command controls this setting. The xhigh, max, and ultracode options all map to GLM-5.2’s Max effort. Architecture and What Changed Z.ai did not specify GLM-5.2’s architecture in its launch materials. But based on community notes, the GLM-5 base is a 744-billion-parameter Mixture-of-Experts model. It activates 40 billion parameters per token. GLM-5.1 kept that same backbone with retargeted post-training. MTP Explainer Playground #mtp-glm52-demo, #mtp-glm52-demo * { box-sizing:border-box!important; } #mtp-glm52-demo hr, #mtp-glm52-demo p:empty, #mtp-glm52-demo del, #mtp-glm52-demo s { display:none!important; } #mtp-glm52-demo { background:#111!important; color:#e8e8e8!important; border:1px solid #2a2a2a!important; border-radius:14px!important; font-family:-apple-system,BlinkMacSystemFont,"Segoe UI",Roboto,Helvetica,Arial,sans-serif!important; max-width:900px!important; margin:24px auto!important; padding:24px!important; line-height:1.5!important; } #mtp-glm52-demo .g52-head { border-bottom:1px solid #2a2a2a!important; padding-bottom:14px!important; margin-bottom:18px!important; } #mtp-glm52-demo .g52-kicker { color:#76B900!important; font-size:12px!important; letter-spacing:.12em!important; text-transform:uppercase!important; font-weight:700!important; margin:0 0 6px!important; } #mtp-glm52-demo .g52-title { font-size:21px!important; font-weight:700!important; color:#fff!important; margin:0!important; 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} #mtp-glm52-demo .g52-title { font-size:18px!important; } #mtp-glm52-demo .g52-btn { padding:8px 11px!important; font-size:12px!important; } #mtp-glm52-demo pre { font-size:11.5px!important; padding:13px!important; } #mtp-glm52-demo .g52-chip { min-width:calc(50% - 5px)!important; } } Interactive Demo GLM-5.2 Setup Generator & Context Visualizer Pick your agent and effort mode. Copy the exact config. See what 1M tokens buys you. 1. Coding agent Claude Code Claude Code (env vars) OpenClaw Cline 2. Context window 1M tokens (glm-5.2[1m]) Standard (glm-5.2) 3. Thinking effort Max (complex coding) High Your config Copy Context window: GLM-5.1 vs GLM-5.2 GLM-5.1~200,000 tokens GLM-5.21,000,000 tokens GLM-5.2 at a glance 1,000,000input tokens in one context window 131,072max output tokens per response 5xlarger than GLM-5.1’s window 8agentic tools supported day one Config sourced from Z.ai developer docs · June 2026 © Marktechpost (function(){ var root = document.getElementById('mtp-glm52-demo'); if(!root) return; var state = { tool:'claude', ctx:'1m', eff:'max' }; function model(){ return state.ctx==='1m' ? 'glm-5.2[1m]' : 'glm-5.2'; } function effortLine(){ return state.eff==='max' ? 'Run /effort in your session and select max for deeper reasoning.' : 'Run /effort in your session and select high for faster turns.'; } function configs(){ var m = model(); var compact = state.ctx==='1m' ? '1000000' : '200000'; if(state.tool==='claude'){ return { text:'{\n "env": {\n "CLAUDE_CODE_AUTO_COMPACT_WINDOW": "'+c