GLM-5.1

Zhipu AI's latest multimodal flagship released in April 2026, featuring unified visual-linguistic reasoning, a 1M context window, and 30% improved agentic.

GLMZhipu AILanguage ModelLarge Language ModelCodingOpen SourceMoELatestMultimodal
Developer
Zhipu AI
Type
Multimodal Language Model
License
MIT

Overview

GLM-5.1, released by Zhipu AI on April 8, 2026, is the latest multimodal flagship that redefines the standards for open-weight AI. Featuring a massive 754B parameter Mixture-of-Experts (MoE) architecture, it delivers unified visual-linguistic reasoning and industry-leading performance in agentic engineering tasks. GLM-5.1 is specifically designed for long-horizon autonomous workflows, capable of operating independently on complex tasks for up to eight hours while maintaining high reasoning precision.

Capabilities

GLM-5.1 provides a comprehensive suite of advanced AI capabilities:

  • Unified Visual-Linguistic Reasoning: Seamlessly integrates visual and textual information for complex multimodal reasoning.
  • Agentic Endurance: Capable of sustaining autonomous agentic workflows for up to eight hours.
  • Frontier Coding Intelligence: Achieves performance parity with top proprietary models on SWE-bench Pro and other engineering benchmarks.
  • Multimodal Long Context: Supports 200K context window with specialized optimization for large-scale multimodal document analysis.
  • MoE Efficiency: Optimized 754B architecture that only activates 40B parameters per forward pass, delivering high speed and lower latency.
  • Open Enterprise AI: Fully open weights under the MIT license, enabling custom fine-tuning and secure local deployment.

Technical Specifications

  • Model size: 754 billion total parameters, with 40 billion active per forward pass.
  • Architecture: Advanced Mixture-of-Experts (MoE) with unified multimodal support.
  • Context Window: 200,000 input tokens.
  • Maximum Output: 128,000 tokens for long-form generation.
  • License: MIT license for open weights.
  • Training Data: Diverse 25+ trillion token dataset focused on reasoning, coding, and multimodal patterns.
  • Knowledge Cutoff: January 2026.

Use Cases

GLM-4.6 excels across multiple application domains:

AI-Powered Development

  • Multi-language coding: Superior support for Python, JavaScript, Java, and other languages
  • Frontend development: Enhanced capabilities for creating visually appealing interfaces
  • Agent development: Native support for building AI agents and autonomous systems
  • Code optimization: Better performance in code review and optimization tasks
  • Documentation: Enhanced ability to generate comprehensive technical documentation

Smart Office and Automation

  • PowerPoint creation: Significantly enhanced presentation quality and aesthetics
  • Document automation: Better handling of complex office workflows
  • Layout generation: Advanced capabilities for creating aesthetically pleasing layouts
  • Content integrity: Maintains accuracy while improving visual presentation
  • Workflow optimization: Enhanced automation for office productivity tools

Translation and Cross-Language Applications

  • Minor language support: Optimized performance for French, Russian, Japanese, Korean
  • Informal contexts: Better handling of social media and casual communication
  • E-commerce content: Enhanced capabilities for product descriptions and marketing content
  • Semantic coherence: Maintains meaning across lengthy passages
  • Style adaptation: Superior localization and cultural adaptation

Content Creation and Virtual Characters

  • Novel writing: Enhanced capabilities for long-form creative writing
  • Script development: Better performance in screenplay and dialogue creation
  • Copywriting: Improved marketing and advertising content generation
  • Virtual characters: Maintains consistent personality across multi-turn conversations
  • Social AI: Enhanced capabilities for human-like interaction

Intelligent Search and Research

  • User intent understanding: Enhanced ability to understand and respond to user queries
  • Tool retrieval: Better performance in finding and using appropriate tools
  • Result integration: Improved synthesis of information from multiple sources
  • Deep research: Enhanced capabilities for comprehensive research tasks

Performance Metrics

GLM-5.1 sets new benchmarks for open-weights multimodal intelligence:

  • SWE-bench Pro: Achieves parity with Claude Opus 4.7 and GPT-5.4.
  • Multimodal Logic: 94% accuracy on complex visual-linguistic reasoning tasks.
  • Agentic Success Rate: 82% success in multi-hour autonomous engineering sessions.
  • Token Efficiency: 30% reduction in compute cost compared to the 4.6 series.

Positioning

GLM-5.1 is widely recognized as the most powerful open-weight multimodal model globally, outperforming many proprietary alternatives in raw reasoning and agentic stability.

Deployment Options

GLM-5.1 is available through multiple deployment channels:

API Access

  • Z.ai API: Direct access through Zhipu AI's platform.
  • Integrated Coding Tools: Full support in Cursor, Claude Code, and Antigravity.

Local Deployment

  • Hugging Face: Open weights (MIT license) for 754B MoE.
  • vLLM / SGLang: Native support for high-performance local inference.

Limitations

  • Peak Performance: While highly capable, it may not match the absolute peak performance of some proprietary models in specialized tasks
  • Resource Requirements: Local deployment requires significant computational resources
  • Language Support: While strong in multiple languages, performance may vary across different linguistic contexts
  • Specialized Domains: For extremely specialized tasks, domain-specific models may be more appropriate

Safety & Alignment

GLM-4.6 incorporates safety measures appropriate for its capabilities:

  • Open Development: Transparent development process with open weights for community scrutiny
  • Safety Research: Incorporates safety research from the broader AI community
  • Responsible Deployment: Guidelines for responsible use and deployment
  • Community Oversight: Open weights enable community review and safety improvements
  • Alignment Research: Incorporates alignment research from the open-source community

Pricing & Access

GLM-5.1 provides flexible options for both API users and local deployment:

API Access

  • Input Cost: $1.40 per 1 million tokens
  • Output Cost: $4.40 per 1 million tokens
  • Platforms: Z.ai API, OpenRouter, and integrated coding platforms.

Local Deployment

  • Open Weights: Free access under MIT license.
  • Platforms: Hugging Face and ModelScope.
  • Inference Engines: Full support for vLLM and SGLang.

Ecosystem & Tools

GLM-4.6 is well-integrated across development platforms:

  • Z.ai API: Primary platform for API access.
  • Hugging Face: Open weights and model hosting.
  • vLLM: Native support for high-performance inference.
  • SGLang: Compatible with SGLang for local serving.
  • Antigravity: Native integration for agentic partner workflows.

Community & Resources

Frequently Asked Questions

GLM-5.1 was released by Zhipu AI on April 8, 2026, as the latest multimodal flagship in the GLM series.
GLM-5.1 features a 754B MoE architecture, enhanced visual-linguistic reasoning, and specialized endurance for agentic tasks lasting up to eight hours.
GLM-5.1 achieves performance parity with frontier models like Claude Opus 4.6 and GPT-5.4 on complex benchmarks such as SWE-bench Pro.
Yes, GLM-5.1 is an open-weight model released under the MIT license, supporting local deployment and commercial use.
GLM-5.1 supports a 200K input context window with a massive 128K maximum output tokens.

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