GLM-4.7

Overview

GLM-4.7 is Z.AI's flagship foundation model, released on December 22, 2025. Built on a 358-billion parameter Mixture-of-Experts (MoE) architecture, it represents a major leap in coding, reasoning, and agentic capabilities. The model supports a 200,000-token context window paired with an exceptional 128,000-token output capacity—allowing it to generate entire software frameworks, comprehensive reports, or multi-file modules in a single pass.

The architecture activates only specific expert regions based on task requirements, delivering high performance per unit of compute. GLM-4.7 introduces "Interleaved Thinking"—the model reasons before every response and tool call across multi-step turns—combined with "Preserved Thinking" that retains reasoning blocks across conversations to reduce information loss during complex agentic workflows.

A standout feature is "Vibe Coding": enhanced aesthetic intelligence that produces cleaner, more modern user interfaces by default. When generating webpages, slides, or UI components, GLM-4.7 understands visual hierarchy, color harmony, and layout structure better than previous models, significantly reducing frontend polish time.

Capabilities

• 358B MoE architecture with efficient expert routing for cost-effective inference
• 200K token context with massive 128K output capacity for end-to-end generation
• Interleaved Thinking that reasons before each response and tool invocation
• Preserved Thinking to maintain reasoning context across multi-turn sessions
• Vibe Coding for aesthetically superior frontend and UI generation
• Tool streaming with real-time tool call parameter delivery

Strengths

• 73.8% on SWE-bench Verified (+5.8% over GLM-4.6), competitive with Claude Sonnet 4.5
• 42.8% on Humanity's Last Exam (+12.4% improvement), surpassing GPT-5.1
• Open-source SOTA on τ²-Bench for multi-step tool sequencing
• 66.7% on SWE-bench Multilingual for international codebases
• Competitive pricing at $0.60/1M input and $2.20/1M output tokens
• Context caching reduces costs by 20-40% for repeated prompts
• Drop-in OpenAI-compatible API with streaming and function calling

Limitations and Considerations

• Text-only: no native vision or audio (use GLM-4V variants for multimodal)
• MoE architecture requires specialized infrastructure for self-hosting
• Weights not yet fully open-source (expected based on GLM-4.5 precedent)
• Higher latency than Flash variant for simple tasks

Best Use Cases

GLM-4.7 is ideal for:

• Agentic coding with Claude Code, Cline, or Roo Code integrations
• Generating complete software frameworks and multi-file modules
• Frontend development with "Vibe Coding" for polished UI output
• Deep research and multi-step tool orchestration workflows
• Enterprise applications requiring 200K context and 128K output
• Complex reasoning tasks in academic or analytical domains