zai-org/glm-4.7-flash

GLM-4.7-Flash is a free, high-performance text language model launched by Zhipu AI, with a core positioning as a “lightweight flagship that strikes a balance between state-of-the-art performance and high efficiency at the 30B parameter level.” It provides powerful support for agentic coding, deep research, and high-frequency collaboration scenarios.

• Key Upgrades: As an efficient version of the GLM-4.7 series, it achieves leading performance among open-source models of the same size in benchmarks such as SWE-bench Verified and τ²-Bench.
• Applicable Scenarios: Agentic Coding (end-to-end runnable code generation), Deep Research (multi-source information integration), automatic frontend/PPT generation, role-playing creation, intelligent customer service, and more.
• Product Value: Supports up to 200K context tokens and 128K output tokens, significantly reducing development and deployment costs for complex tasks.
• Enhanced Capabilities: Greatly enhanced coding abilities, enabling autonomous requirement breakdown and multi-technology stack integration; optimized frontend aesthetics, making PPT/webpage generation closer to “ready-to-use” standards.
• Improved Interaction Experience: Maintains context stability throughout multi-turn conversations, continuously clarifies objectives when dealing with complex issues, and behaves more like a “problem-solving partner.”

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Core Capabilities

⚡ Efficient Long-Context Processing: 200K input window + intelligent context caching ensures smooth, non-forgetting long conversations.

🧠 Deep Thinking Mode: Supports enabling the thinking mode, allowing for a reasoning chain of “think first, then act,” improving accuracy in complex tasks.

🛠️ Powerful Tool Collaboration: Natively supports Function Call and MCP protocols, enabling flexible invocation of external tools and data sources.

🎨 Frontend Aesthetic Upgrade: More aesthetically pleasing layouts, color schemes, and component styles; default configurations reduce the cost of repeated fine-tuning.

📊 Structured Output: Supports formats such as JSON, facilitating direct system parsing and seamless integration into automated workflows.

💬 Streaming Real-Time Responses: Supports streaming output, returning results word by word, delivering low-latency, highly immersive interaction experiences.

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Test Data

• In mainstream benchmarks such as SWE-bench Verified and τ²-Bench, GLM-4.7-Flash reaches state-of-the-art levels among open-source models of the same size.
• It boasts leading frontend and backend development capabilities and performs exceptionally well in internal programming tests.
• Strong general-purpose capabilities, recommended for scenarios including Chinese writing, translation, long-text processing, sentiment expression, and role-playing.