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Z.ai GLM-5V-Turbo

GLM-5V-Turbo

Process images, videos, design drafts, and document layouts natively as a multimodal vision coding model with 200K context window and 128K max output tokens for long-horizon agentic tasks Execute the full perceive-plan-execute loop in GUI environments with leading scores on AndroidWorld, WebVoyager, and ZClawBench agent benchmarks optimized for OpenClaw workflows Fuse visual understanding and code generation through CogViT vision encoder and 30+ task joint reinforcement learning across STEM, grounding, video, and coding domains

Reviewed by ToolWorthy Editors·updated 3 months ago

Pricing:From $18/mo
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Pros & Cons

Pros

  • Native multimodal fusion eliminates separate OCR and vision preprocessing steps
  • 200K context window with 128K max output handles large codebases and long documents
  • Leading GUI agent benchmark scores for automated testing and web navigation workflows
  • Competitive pricing at $1.20/1M input tokens compared to other multimodal coding models
  • Multiple reasoning modes (thinking mode) for different task complexity levels
  • Open architecture with SDK support for Python, Java, and cURL

Cons

  • Vision-specific model costs more than text-only GLM-5 ($1.20 vs $1.00 per 1M input tokens)
  • Benchmark results are vendor-reported and may not fully reflect real-world performance
  • No free tier for GLM-5V-Turbo specifically (GLM-4.6V-Flash is the free vision option)
  • Relatively new model with limited third-party evaluation and community feedback

Overview

GLM-5V-Turbo is Z.ai's first native multimodal vision coding model, designed to bridge the gap between visual perception and code execution. Released on April 1, 2026, it processes images, videos, design drafts, and document layouts as primary inputs while generating code and executing multi-step agent workflows.

Unlike GLM-5.1 which focuses on text-based coding performance, GLM-5V-Turbo adds a CogViT vision encoder and 30+ task joint reinforcement learning pipeline to handle vision-grounded tasks. It targets developers building GUI automation agents, design-to-code pipelines, and document processing workflows where understanding visual context is essential for accurate code generation.

What's New

Native Multimodal Vision Coding

GLM-5V-Turbo natively fuses visual understanding with code generation from pretraining through post-training. The model processes images, videos, design drafts, and complex document layouts as first-class inputs, reducing the need for separate vision preprocessing in many multimodal coding workflows. This enables direct design-to-code generation, resume screening, visual grounding, and document-grounded writing in a single model call.

CogViT Vision Encoder

GLM-5V-Turbo introduces a new CogViT vision encoder combined with an inference-friendly architecture optimized for coding-relevant visual tasks. It handles high-resolution design mockups, screenshots of GUI environments, and multi-page documents while maintaining the 200K context window and 128K max output token capacity needed for long-horizon code generation.

Agent Workflow Optimization

GLM-5V-Turbo completes the full perceive-plan-execute loop for autonomous environment interaction. It delivered strong performance on AndroidWorld and WebVoyager for GUI agent tasks, solid results across CC-Bench-V2 benchmarks, and competitive scores on PinchBench, ClawEval, and ZClawBench for agent task execution. The model integrates natively with OpenClaw and Claude Code workflows.

30+ Task Joint Reinforcement Learning

The model was trained with joint reinforcement learning across STEM reasoning, visual grounding, video understanding, and coding domains simultaneously. This multi-task approach enables GLM-5V-Turbo to handle diverse visual inputs — from mathematical diagrams to UI wireframes — while maintaining strong code generation capabilities across all input types.

Performance Benchmarks

GLM-5V-Turbo scores 43 on the Artificial Analysis Intelligence Index, according to Artificial Analysis.

Benchmark Category GLM-5V-Turbo
AndroidWorld GUI agent tasks Strong
WebVoyager Web navigation agent Strong
CC-Bench-V2 Backend + frontend coding Strong
ZClawBench Agent task execution Strong
PinchBench Agent evaluation Competitive
ClawEval Agent evaluation Competitive

The model supports text, image, and video input with a 200K token context window. Performance data is based on Z.ai's official benchmark reports.

Pricing & Plans

GLM-5V-Turbo is available through Z.ai's API with pay-per-use pricing.

API Pricing

  • Input tokens: $1.20 per 1M tokens
  • Output tokens: $4.00 per 1M tokens
  • Context window: 200K tokens
  • Max output: 128K tokens

Comparison with Other Z.ai Vision Models

Model Input Cost (1M tokens) Output Cost (1M tokens) Status
GLM-5V-Turbo $1.20 $4.00 Current
GLM-4.6V-Flash Free Free Available
GLM-OCR $0.03 Available

For chat-based access, GLM-5V-Turbo is available through the Z.ai platform. Subscription plan access details may vary — check the official pricing page for current availability.

Best For

  • Frontend developers converting design mockups and Figma exports into production code
  • QA engineers building GUI automation agents for Android and web application testing
  • Document processing teams extracting structured data from PDFs, resumes, and scanned layouts
  • Agent developers building perceive-plan-execute workflows with OpenClaw or Claude Code
  • Teams needing vision-grounded code generation for screenshots, diagrams, and UI wireframes

FAQ

How does GLM-5V-Turbo differ from GLM-5.1?

GLM-5.1 is a text-focused coding model optimized for IDE integration and agentic coding tasks. GLM-5V-Turbo adds native multimodal vision capabilities through the CogViT encoder, enabling it to process images, videos, and design drafts as primary inputs for code generation. Choose GLM-5.1 for pure text coding tasks and GLM-5V-Turbo when visual context matters.

What input types does GLM-5V-Turbo support?

The model accepts images (PNG, JPG, WebP), video files, PDF documents, Word documents, and text. It can process design mockups, screenshots, diagrams, and multi-page document layouts alongside text prompts.

Can I use GLM-5V-Turbo with existing coding tools?

Yes. GLM-5V-Turbo integrates with OpenClaw and Claude Code workflows. It supports function calling for external tool integration, streaming output for real-time responses, and context caching for extended conversations.

Is GLM-5V-Turbo available for self-hosting?

Check Z.ai's official documentation for the current deployment and availability options for GLM-5V-Turbo weights and self-hosted deployment.

How does the pricing compare to other multimodal models?

At $1.20 per 1M input tokens and $4.00 per 1M output tokens, GLM-5V-Turbo is positioned as a cost-effective option for vision coding tasks. Z.ai also offers GLM-4.6V-Flash as a free alternative for lighter vision workloads.

Version History

GLM-5.2

Released on June 13, 2026

View Update
+What's new
3 updates
  • Use Z.ai's new flagship coding model across all GLM Coding Plan tiers, including Lite, Pro, Max, and Team plans, with 1M-context support for large codebases and long agent sessions
  • Configure Claude Code with `glm-5.2[1m]` plus `CLAUDE_CODE_AUTO_COMPACT_WINDOW=1000000`; configure OpenClaw/Cline-style tools with `glm-5.2`, 1M context settings, and 131K max output where the tool supports it.
  • Reserve GLM-5.2 for complex work because Z.ai treats it as a premium Opus-level model with higher quota multipliers, while GLM-4.7 remains the recommended option for routine tasks

GLM-5.1

Released on April 7, 2026

View Update
+What's new
3 updates
  • Use GLM-5.1 for long-horizon agentic engineering work, with stronger coding than GLM-5 and an official SWE-Bench Pro score of 58.4 against frontier coding models
  • Run multi-stage engineering tasks for up to 8 hours in one autonomous loop, covering planning, execution, testing, bug fixing, and production-grade delivery
  • Build agents that repeatedly experiment, analyze results, adjust strategy, and optimize systems, including benchmark-driven performance tuning workflows

GLM-5V-Turbo

Current Version

Released on April 1, 2026

+What's new
3 updates
  • Process images, videos, design drafts, and document layouts natively as a multimodal vision coding model with 200K context window and 128K max output tokens for long-horizon agentic tasks
  • Execute the full perceive-plan-execute loop in GUI environments with leading scores on AndroidWorld, WebVoyager, and ZClawBench agent benchmarks optimized for OpenClaw workflows
  • Fuse visual understanding and code generation through CogViT vision encoder and 30+ task joint reinforcement learning across STEM, grounding, video, and coding domains

GLM-5.1

Released on March 27, 2026

View Update
+What's new
3 updates
  • Score 45.3 on Claude Code coding benchmark—94.6% of Claude Opus 4.6 performance—with 28% improvement over GLM-5, establishing a new frontier in cost-efficient agentic coding
  • Generate code at 55+ tokens/sec with estimated 200K context window, enabling long-horizon multi-file refactoring and distributed system architecture design
  • Access frontier-level coding intelligence from $3/month via Coding Plan with native compatibility for Claude Code, Cline, and Roo Code MCP tool integrations

GLM-5-Turbo

Released on March 15, 2026

+What's new
3 updates
  • Execute complex OpenClaw agent workflows with superior tool invocation reliability, scheduled task continuity, and high-throughput long-chain execution optimized since training phase
  • Decompose and follow multi-layered complex instructions with enhanced comprehension, supporting collaborative task division among multiple agents and MCP tool integrations
  • Outperform GLM-5 across multiple ZClawBench task categories while supporting 200K context input with multiple thinking modes for dynamic, long-running agent tasks

GLM-5

Released on February 12, 2026

View Update
+What's new
3 updates
  • Handle complex systems engineering and long-horizon agentic tasks with 744B parameters (40B active) and DeepSeek Sparse Attention integration
  • Generate production-ready documents (.docx, .pdf, .xlsx) directly from text with built-in Agent mode and multi-turn collaboration
  • Execute code with best-in-class open-source performance on reasoning benchmarks, approaching frontier model capabilities

GLM-4.7-Flash

Released on January 19, 2026

+What's new
3 updates
  • Get lightweight version of GLM-4.7 with faster response times and high throughput optimized for real-time coding, writing, and translation tasks
  • Deploy efficiently with competitive performance at smaller scale while maintaining strong general capabilities across reasoning and content generation
  • Access free-tier model designed for high-frequency use cases with best-in-class aesthetic outputs, low latency, and simplified deployment

GLM-4.7-Flash

Released on January 19, 2026

+What's new
3 updates
  • Get lightweight version of GLM-4.7 with faster response times and high throughput optimized for real-time coding, writing, and translation tasks
  • Deploy efficiently with competitive performance at smaller scale while maintaining strong general capabilities across reasoning and content generation
  • Access free-tier model designed for high-frequency use cases with best-in-class aesthetic outputs, low latency, and simplified deployment

GLM-4.7

Released on December 22, 2025

+What's new
3 updates
  • Build cleaner modern webpages and professional slides with major improvements in UI aesthetics, visual quality, and accurate layout sizing for frontend development
  • Solve multilingual coding tasks faster with 73.8% on SWE-bench and 41% on Terminal Bench 2.0, delivering stronger performance across agent frameworks
  • Reason through complex mathematical and logical problems with 42.8% on HLE benchmark while enhancing tool-using and web browsing capabilities

GLM-4.6

Released on September 30, 2025

+What's new
3 updates
  • Handle longer conversations and complex multi-file codebases with expanded 200K context window, enabling more sophisticated agentic task execution
  • Code more efficiently in Claude Code, Cline, and Roo Code with superior benchmark performance and improved real-world coding accuracy
  • Leverage enhanced reasoning capabilities with native tool use support during inference, delivering stronger results in search-based agent workflows

GLM-4.5

Released on July 28, 2025

+What's new
3 updates
  • Unify reasoning, coding, and agentic capabilities in a single model delivering balanced performance across complex problem-solving and rapid content generation
  • Switch between thinking mode for deep analysis and non-thinking mode for instant responses, adapting intelligence level to task complexity on demand
  • Build full-stack web applications with stronger frontend quality, and integrate the model into Claude Code, Roo Code, or custom agent workflows through tool APIs

ChatGLM3-6B

Released on October 27, 2023

+What's new
3 updates
  • Execute code directly and invoke external tools with new Code Interpreter and Function Call capabilities, enabling autonomous agent-style task completion
  • Process information more accurately with improved training across 42 benchmarks covering semantics, mathematics, reasoning, code, and knowledge understanding
  • Deploy locally on consumer hardware with open-source 6B-parameter model supporting both academic research and free commercial use after registration

ChatGLM2-6B

Released on June 25, 2023

+What's new
3 updates
  • Handle longer conversations with expanded 32K context window using FlashAttention technology, enabling deeper multi-turn dialogue understanding
  • Get responses 42% faster with improved inference speed and INT4 quantization, supporting extended dialogues on consumer GPUs with only 6GB VRAM
  • Achieve stronger performance across reasoning and knowledge benchmarks with enhanced training on 1.4T bilingual tokens covering diverse domains

ChatGLM-6B

Released on March 14, 2023

+What's new
3 updates
  • Deploy locally on consumer-grade graphics cards with lightweight 6.2B-parameter bilingual model, enabling private ChatGPT-style conversations
  • Chat naturally in Chinese and English with open-source conversational AI trained on approximately 1 trillion tokens of diverse text data
  • Use freely for commercial purposes after simple registration, with full model weights and training code available for academic research

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