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Z.ai Launches GLM-5.2 With a Usable 1M-Token Context, Two Thinking-Effort Levels, and No Benchmarks at Launch

ByRicardo

GLM-5.2 is the newest giant language mannequin from Z.ai, turning into the third main launch within the GLM-5 line. It follows GLM-5 (February 11), GLM-5-Turbo (March 15), and GLM-5.1 (April 7). That makes 4 flagship-tier coding releases in roughly 4 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 personal configuration. Each response can return as much as 131,072 output tokens. That is roughly a 5x leap from GLM-5.1’s 200,000-token window.

A 1M-token window adjustments how a coding agent works in follow. The agent can maintain a complete mid-sized repository in working reminiscence. That contains supply recordsdata, assessments, configuration, and dialog historical past. It avoids the fixed summarization that smaller home windows drive.

The launch additionally provides two thinking-effort ranges: High and Max. Z.ai recommends Max effort for complicated, multi-step coding work. In Claude Code, the /effort command controls this setting. The xhigh, max, and ultracode choices all map to GLM-5.2’s Max effort.

Architecture and What Changed

Z.ai didn’t specify GLM-5.2’s structure in its launch supplies. But primarily based on neighborhood notes, the GLM-5 base is a 744-billion-parameter Mixture-of-Experts mannequin. It prompts 40 billion parameters per token. GLM-5.1 stored that very same spine with retargeted post-training.

MTP Explainer Playground

Interactive Demo

GLM-5.2 Setup Generator & Context Visualizer

Pick your agent and effort mode. Copy the precise config. See what 1M tokens buys you.

1. Coding agent




2. Context window


3. Thinking effort


Your config

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 look

1,000,000enter tokens in a single context window
131,072max output tokens per response
5xbigger than GLM-5.1’s window
8agentic instruments supported day one

Config sourced from Z.ai developer docs · June 2026
© Marktechpost

The Benchmark Question

Here is the necessary caveat. Z.ai printed no benchmark scores for GLM-5.2 at launch. There isn’t any SWE-bench, Terminal-Bench, or Code Arena quantity but. The announcement centered on availability, context, and the open-source roadmap.

Specification Comparison: GLM-5.2 vs GLM-5.1

Attribute GLM-5.2 GLM-5.1
Released June 13, 2026 April 7, 2026
Context window 1,000,000 tokens (glm-5.2[1m]) ~200,000 tokens
Max output tokens 131,072 Not disclosed
Reasoning modes High, Max Single mode
Architecture Not specified at launch (GLM-5 lineage) 744B MoE, 40B energetic
License MIT (weights pending subsequent week) MIT (open weights launched)
Launch benchmarks None printed 58.4 SWE-bench Pro
Access at launch GLM Coding Plan (all tiers) Coding Plan, API, and weights

Use Cases With Examples

  • Whole-repository refactors: Load a mid-sized repo into one context window. The agent tracks cross-file dependencies with out re-fetching. Example: refactor a 40-file Python knowledge pipeline in a single session.
  • Long-horizon agent runs: GLM-5.2 targets sustained plan, execute, check, repair loops. GLM-5.1 sustained roughly 1,700 agent steps in a single session. It ran autonomous loops for as much as eight hours. GLM-5.2 inherits that trajectory, although its personal numbers are pending.
  • Drop-in Claude Code alternative: Swap the bottom URL and mannequin identifier solely. Keep your current agent harness and workflow. This issues when frontier API entry is disrupted.
  • Large-document evaluation: Feed lengthy specs, logs, or transcripts previous 200K tokens. The 1M window holds materials that smaller fashions truncate.

How to Set Up GLM-5.2

For Claude Code, edit ~/.claude/settings.json. Point the Sonnet and Opus slots at the 1M variant. Raise the auto-compact window so the agent makes use of the total context.

Copy Code
{
  "env": {
    "CLAUDE_CODE_AUTO_COMPACT_WINDOW": "1000000",
    "ANTHROPIC_DEFAULT_HAIKU_MODEL": "glm-4.5-air",
    "ANTHROPIC_DEFAULT_SONNET_MODEL": "glm-5.2[1m]",
    "ANTHROPIC_DEFAULT_OPUS_MODEL": "glm-5.2[1m]"
  }
}

Alternatively, set the endpoint by way of surroundings variables. The Anthropic-compatible endpoint accepts a base-URL swap.

Copy Code
export ANTHROPIC_AUTH_TOKEN="your-zai-api-key"
export ANTHROPIC_BASE_URL="https://api.z.ai/api/anthropic"
export ANTHROPIC_DEFAULT_OPUS_MODEL="glm-5.2[1m]"
export ANTHROPIC_DEFAULT_SONNET_MODEL="glm-5.2[1m]"
export ANTHROPIC_DEFAULT_HAIKU_MODEL="glm-4.5-air"
claude

Then run /effort in a session and choose max. Run /standing to substantiate GLM-5.2 is energetic. For Cline, select the OpenAI Compatible supplier. Set the bottom URL to https://api.z.ai/api/coding/paas/v4. Enter the customized mannequin glm-5.2 and set context to 1,000,000.

GLM-5.2 is appropriate with eight agentic coding instruments from day one. The listing contains Claude Code, Cline, OpenCode, and OpenClaw.

Key Takeaways

  • Z.ai shipped GLM-5.2 on June 13, 2026, dwell instantly throughout all GLM Coding Plan tiers (Lite, Pro, Max, Team).
  • 1M-token context window (glm-5.2[1m]) with as much as 131,072 output tokens.
  • No benchmarks had been printed at launch
  • It drops into Claude Code, Cline, and OpenClaw through an Anthropic-compatible endpoint with simply a base-URL and mannequin swap.

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