GLM-5.2

Z.ai’s flagship model for project-scale engineering, long-horizon coding, agent workflows, and reliable execution across a 1M-token context.

無需信用卡幾秒內部署完整程式碼所有權

受到來自以下地區客戶的信賴

GLM-5.2 是什麼?

GLM-5.2 is an AI model available through Atoms for coding, reasoning, research, and tool-driven workflows. Z.ai’s flagship model for project-scale engineering, long-horizon coding, agent workflows, and reliable execution across a 1M-token context. Review the model details below, compare alternatives, and start with the example prompt in the hero.

Decision point What to check
Best for coding, reasoning, research, and tool-driven workflows
Access Available through the Atoms model workflow when shown in the current model selector
Evidence Provider information and the practical guidance on this page
Limitation Results depend on the prompt, task, selected settings, and review workflow
Page verified August 23, 2026

GLM-5.2 is Z.ai’s flagship foundation model for long-horizon tasks. Z.ai positions it for project-scale engineering contexts where the model must retain architecture, API contracts, repository conventions, and earlier decisions while taking work from requirements to a deployable product. It accepts text input and produces text output.

  • 1M-token context: works across large codebases, technical documentation, requirements, and project history
  • 128K maximum output: supports detailed implementations, reviews, and long-form engineering deliverables
  • Long-horizon coding: plans, implements, verifies, and closes multi-file tasks in stages
  • Engineering discipline: follows architectural boundaries, dependency constraints, build processes, test requirements, and repository conventions
  • Agent integration: supports multiple thinking modes, streaming, function calling, context caching, structured JSON output, and MCP tools

Z.ai highlights GLM-5.2 for codebase audits, large refactors, API migrations, mobile debugging, Mini Program development, research reproduction, and other workflows where context continuity and reliable follow-through matter.

In August 2026, an anonymous model called Ox Alpha appeared on OpenRouter with a one-week free-access promotion. Developers and Reddit users spent several days trying to identify its provider. Bloomberg later reported that Z.AI confirmed Ox Alpha was a new iteration of its GLM series and planned to release the weights.

The episode matters because it was not only a launch stunt. Early developer reports focused on coding and agent tasks, while the model's identity was investigated through serving behavior, tokenizer and output fingerprints, and error-message similarities. Those community tests are evidence of the investigation—not a substitute for an official model card or a controlled benchmark.

  • The supplied DeepSWE screenshot reports an 80% mean on a 10-task subset for Ox Alpha, compared with 65% for Claude Fable 5 and 52% for GPT-5.6 Sol. This is a small, community-shared sample and should not be treated as a definitive leaderboard.
  • OpenCode's announcement described a 1M context window, multimodal support, zero data retention, generous limits, and claimed capacity. These are service claims from a social post and require separate verification for current availability and terms.
  • The practical signal is strongest in software engineering: repository changes, tool use, debugging, and long-horizon coding—not generic chat quality.
  • Z.AI's public GLM-5.3 documentation is the authoritative reference for the GLM product line; Ox Alpha's exact public checkpoint name, weights, license, and serving configuration should be verified against Z.AI's release materials before deployment.

Clean OpenCode Ox Alpha announcement

OpenCode's Ox Alpha announcement, cropped to remove unrelated publisher branding. This image documents a social-media claim, not independent verification.

Ox Alpha benchmark subset

Community-shared DeepSWE subset comparison. The image itself notes that the sample is only ten tasks; it should not be generalized to overall model quality.

For builders, the right takeaway is not “Ox Alpha beats every model.” It is that Z.AI demonstrated a high-attention path from anonymous preview to confirmed GLM release, while the strongest early user signal appeared in coding workflows. Test the exact model, harness, prompt, context, retries, and accepted changes before making a production decision.

Clean Ox Alpha art evidence

Ox Alpha evidence image, cropped to remove unrelated Evolving AI publisher branding. Treat social posts and community benchmark claims as reported evidence, not independent verification.

Clean Ox Alpha context evidence

Ox Alpha evidence image, cropped to remove unrelated Evolving AI publisher branding. Treat social posts and community benchmark claims as reported evidence, not independent verification.

Clean Ox Alpha reactions evidence

Ox Alpha evidence image, cropped to remove unrelated Evolving AI publisher branding. Treat social posts and community benchmark claims as reported evidence, not independent verification.

程式碼生成
錯誤偵測與修復
程式碼重構
程式碼說明
文件生成
單元測試編寫
為什麼選擇 Atoms

為什麼在 Atoms 上使用 GLM-5.2?

  • Turn requirements into implementation: move from a product goal and technical constraints into a structured build plan
  • Keep project context connected: work across specifications, code structure, API contracts, and existing engineering decisions
  • Coordinate multi-step execution: organize product, engineering, review, and validation tasks around one shared outcome
  • Review before release: inspect the live result, resolve issues, and verify behavior against the original requirements
  • Deploy and retain ownership: publish the finished product and export the code to GitHub when needed

多智能體 AI 團隊

產品經理、工程師和設計師協同合作,將你的提示轉化為完整產品。

幾分鐘上線,而不是幾個月

一次對話,即可從想法到已部署的產品。無需設定,無需配置。

完整程式碼所有權

可隨時匯出到 GitHub。所有內容都歸你所有——無供應商綁定。

如何在 Atoms 上使用 GLM-5.2

立即開始建立
01
Describe the product, refactor, or engineering task. Add requirements, repository conventions, API contracts, documents, and other relevant context.
02
Analyze the architecture, module responsibilities, dependencies, risks, and verification requirements before making changes.
03
Implement the solution in stages while following project constraints, checking behavior, and running the required build, lint, and test commands.
04
Review the working result, resolve remaining issues, and deploy it to a live URL when it meets the requirements.

為什麼在 Atoms 上使用 GLM-5.2 進行建置

一鍵部署

一鍵部署

立即上線。Atoms 會處理託管、SSL 和伺服器設定,讓你可以專注於建置。

視覺編輯器

視覺編輯器

以視覺化方式編輯你的應用程式——無需撰寫程式碼即可調整版面、顏色與內容。

即時 AI 整合

即時 AI 整合

透過一個提示即可新增 AI 驅動的功能——聊天機器人、圖像生成、文字分析。

多智能體 AI 團隊

多智能體 AI 團隊

一支完整的 AI 團隊——產品經理、工程師、設計師——協作將你的提示轉化為可運作的產品。

你可以用 GLM-5.2 建立什麼

SaaS 儀表板

建置一個具備使用者驗證、計費和即時分析功能的全端 SaaS。

電子商務商店

建立一個包含購物車、結帳和 Stripe 付款的產品目錄。

內部工具

在幾分鐘內為你的團隊交付管理面板、CRM 和工作流程工具。

行動應用程式

建立具備原生體驗 UI 和推播通知的跨平台行動應用程式。

Atoms 與從零開始建置對比

Atoms
DIY / 從零開始
上線時間
分鐘
數週到數月
所需技術技能
無
全端開發
部署與託管
一鍵即可,已包含
需要手動設定
AI 模型存取
頂級 AI 模型,預先配置完成
API 金鑰、SDK 和計費
持續維護
已為您處理
一切由你掌控
提供免費方案

免費開始使用 GLM-5.2

無需信用卡,無需設定。只要描述你想要的內容,Atoms 就能幫你交付。

  • 每天 15 個免費額度你的每日配額會自動補充——無需盯著分頁,也能持續迭代。
  • 無需信用卡使用電子郵件或 Google 可在幾秒內註冊——立即開始免費方案建置。
  • 頂級 AI 模型,一個帳戶盡享隨時在同一聊天中切換 GLM-5.2 和其他前沿模型。
  • 無需設定,無需基礎設施你的 AI 團隊負責規劃、建構和預覽——無需管理本地工具鏈或部署流程。
  • 可用於生產環境的部署每次建置都可部署到帶有自訂網域、SSL 和版本歷史記錄的線上 URL。

常見問題

Start Building with GLM-5.2

Turn project-scale coding and long-horizon agent ideas into products you can review, verify, and deploy.