> ## Documentation Index
> Fetch the complete documentation index at: https://docs.z.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# New Released

> Follow along with updates across Z.AI’s models

## Models

<Update label="2026-08-26" description="  GLM-5.3-Flash">
  * Native visual capabilities enable the model to observe interfaces, rendering results, and interaction feedback—creating a closed loop across code, browsers, and GUIs.

  * Efficient hybrid architecture: Combines linear and sparse attention with 320B total parameters and 18B activated, significantly reducing compute and KV-cache requirements.

  * Beyond coding: Supports office document and financial research workflows, autonomously breaking down goals, using tools, and refining outputs. Learn more in our [documentation](/guides/vlm/glm-5.3-flash).\*
</Update>

<Update label="2026-08-18" description="  GLM-5.3">
  * Stronger Coding Capabilities: GLM-5.3 delivers a significant improvement in coding capabilities, achieving a 50% gain over GLM-5.2 on Z.ai Code Bench and reaching state-of-the-art (SOTA) performance among open-source models on public benchmarks, including Terminal Bench 3.0.

  * Emergent Cybersecurity Capabilities: GLM-5.3 matches Mythos 5 in white-box code review and vulnerability discovery. In collaboration with multiple cybersecurity teams, it has been tested on real-world targets and has identified a total of 2,436 vulnerabilities, including 1,097 medium- and high-severity vulnerabilities.Learn more in our [documentation](https://docs.z.ai/guides/llm/glm-5.3).\*
</Update>

<Update label="2026-06-16" description="  GLM-5.2">
  * Supports 1M lossless context, significantly improving long-horizon task capabilities and reducing context drift and goal forgetting in complex tasks

  * Achieves open-source SOTA performance on coding and long-horizon task benchmarks, delivering more stable results in complex system engineering and deep debugging

  * Significantly improves the real-world developer experience, with more reliable project-level context handling, adherence to engineering standards, and multi-platform development. Learn more in our [documentation](/guides/llm/glm-5.2).\*
</Update>

<Update label="2026-04-07" description="  GLM-5.1">
  * Designed for long-horizon tasks, GLM-5.1 can work independently for up to 8 hours in a single run, enabling a full loop from planning and execution to iterative refinement and final delivery.

  * It demonstrates stronger engineering intelligence across autonomous planning, sustained execution, bug fixing, and strategy iteration, while achieving comprehensive capability alignment with Claude Opus 4.6. Built with multi-turn SFT, RL, and a process-quality evaluation framework, GLM-5.1 further improves stability, consistency, and tool use over extended tasks. Learn more in our [documentation](/guides/llm/glm-5.1).\*
</Update>

<Update label="2026-02-12" description="  GLM-5">
  * Designed for complex system engineering and long-range Agent tasks, GLM-5 shifts the paradigm from coding to engineering, demonstrating strong deep-reasoning performance in backend architecture, complex algorithms, and stubborn bug fixing.

  * It directly benchmarks against Claude Opus 4.5 in code-logic density and systems-engineering capability, and integrates DeepSeek Sparse Attention for higher token efficiency while preserving long-context quality.Learn more in our [documentation](/guides/llm/glm-5).\*
</Update>

<Update label="2026-02-03" description="  GLM-OCR">
  * We’ve launched GLM-OCR, a compact and high-performance optical character recognition model powered by the self-developed CogViT and GLM-0.5B encoder-decoder architecture, enabling efficient cross-modal alignment through its dedicated connection layer.
  * The update leverages CLIP pre-training on billions of image-text pairs to deliver robust visual semantic understanding and key token extraction capabilities, while maintaining a lightweight design for fast inference. Learn more in our [documentation](/guides/vlm/glm-ocr).\*
</Update>

<Update label="2026-01-19" description="  GLM-4.7-Flash">
  * We’ve launched GLM-4.7-Flash, a lightweight and efficient model designed as the free-tier version of GLM-4.7, delivering strong performance across coding, reasoning, and generative tasks with low latency and high throughput.
  * The update brings competitive coding capabilities at its scale, offering best-in-class general abilities in writing, translation, long-form content, role play, and aesthetic outputs for high-frequency and real-time use cases. Learn more in our [documentation](/guides/llm/glm-4.7).\*
</Update>

<Update label="2026-01-14" description="  GLM-Image">
  * We’ve launched GLM-Image, a state-of-the-art image generation model built on a multimodal architecture and fully trained on domestic chips, combining autoregressive semantic understanding with diffusion-based decoding to deliver high-quality, controllable visual generation.
  * The update significantly enhances performance in knowledge-intensive scenarios, with more stable and accurate text rendering inside images, making GLM-Image especially well suited for commercial design, educational illustrations, and content-rich visual applications.Learn more in our [documentation](/guides/image/glm-image).\*
</Update>

<Update label="2025-12-22" description="  GLM-4.7">
  * We’ve released GLM-4.7, our foundation model with significant improvements in coding, reasoning, and agentic capabilities. It delivers more reliable code generation, stronger long-context understanding, and improved end-to-end task execution across real-world development workflows.
  * The update brings open-source SOTA performance on major coding and reasoning benchmarks, enhanced agentic coding for goal-driven, multi-step tasks, and improved front-end and document generation quality. Learn more in our [documentation](/guides/llm/glm-4.7).\*
</Update>

<Update label="2025-12-11" description="  AutoGLM-Phone-Multilingual">
  * We’ve launched AutoGLM-Phone-Multilingual, our latest multimodal mobile automation framework that understands screen content and executes real actions through ADB. It enables natural-language task execution across 50+ mainstream apps, delivering true end-to-end mobile control.
  * The update introduces multilingual support (English & Chinese), enhanced workflow planning capabilities, and improved task execution reliability. Learn more in our [documentation](/guides/vlm/autoglm-phone-multilingual).\*
</Update>

<Update label="2025-12-10" description="  GLM-ASR-2512">
  * We’ve launched GLM-ASR-2512, our ASR model, delivering industry-leading accuracy with a Character Error Rate of just 0.0717, and significantly improved performance across real-world multilingual and accent-rich scenarios.
  * The update introduces enhanced custom dictionary support and expanded specialized terminology recognition. Learn more in our [documentation](/guides/audio/glm-asr-2512).\*
</Update>

<Update label="2025-12-08" description="  GLM-4.6V">
  * We’re excited to introduce GLM-4.6V, Z.ai’s latest iteration in multimodal large language models. This version enhances vision understanding, achieving state-of-the-art performance in tasks involving images and text.
  * The update also expands the context window to 128K, enabling more efficient processing of long inputs and complex multimodal tasks. Learn more in our [documentation](/guides/vlm/glm-4.6v).\*
</Update>

<Update label="2025-09-30" description="  GLM-4.6">
  * We’ve launched GLM-4.6, the flagship coding model, showcasing enhanced performance in both public benchmarks and real-world programming tasks, making it the leading coding model in China.
  * The update also expands the context window to 200K, improving its ability to handle longer code and complex agent tasks. Learn more in our [documentation](/guides/llm/glm-4.6).\*
</Update>

<Update label="2025-08-11" description="  GLM-4.5V">
  * We’ve launched GLM-4.5V, a 100B-scale open-source vision reasoning model, supporting a broad range of visual tasks including video understanding, visual grounding, GUI agents and etc.
  * The update also adds a new thinking mode. Learn more in our [documentation](/guides/vlm/glm-4.5v).\*
</Update>

<Update label="2025-08-08" description="  GLM Slide/Poster Agent(beta)">
  * We’ve launched GLM Slide/Poster Agent, an AI-powered creation agent that combines information retrieval, content structuring, and visual layout design to generate professional-grade slides and posters from natural language instructions.
  * The update also brings a seamless integration of content generation with design conventions. Learn more in our [documentation](/guides/agents/slide).\*
</Update>

<Update label="2025-07-28" description="  GLM-4.5 Series">
  * We’ve launched GLM-4.5, our latest native agentic LLM, delivering doubled parameter efficiency and strong reasoning, coding, and agentic capabilities.
  * It also offers seamless one-click compatibility with the Claude Code framework. Learn more in our [documentation](/guides/llm/glm-4.5).\*
</Update>

<Update label="2025-07-15" description="  CogVideoX-3">
  * We’ve launched CogVideoX-3, an incremental upgrade to our video generation model with improved quality and new features.
  * It adds support for start and end frame synthesis. Learn more in our [documentation](/guides/video/cogvideox-3).\*
</Update>