GLM 4.7 API
Released December 2025 | 205K Tokens context | 355B params (32B active) parameters
GLM 4.7 API enables Agentic multilingual coding, Terminal-based task automation, Vibe coding & UI generation, Complex mathematical reasoning, Tool orchestration (Claude Code, Cline, Roo Code), and Long-horizon multi-turn tasks. GLM-4.7 is Z.ai's (formerly Zhipu AI) new-generation flagship model with 355B total parameters and 32B activated per forward pass. It introduces Interleaved Thinking, Preserved Thinking, and Turn-level Thinking — enabling models to reason before actions and maintain coherent state across long coding sessions. Achieves 95.7% on AIME 2025, 73.8% on SWE-bench, and 87.4% on τ²-Bench. Standout strengths include Interleaved Thinking for reasoning before every action and Preserved Thinking retains reasoning across coding sessions. It is optimized for production agent and assistant workloads where response quality, latency, and predictable operating cost all matter.
from openai import OpenAI # Initialize the OpenAI client with Qubrid base URL client = OpenAI( base_url="https://platform.qubrid.com/v1", api_key="QUBRID_API_KEY", ) stream = client.chat.completions.create( model="zai-org/GLM-4.7", messages=[ { "role": "user", "content": "Explain quantum computing in simple terms" } ], max_tokens=4096, temperature=0.6, top_p=1, stream=True ) for chunk in stream: if chunk.choices and chunk.choices[0].delta.content: print(chunk.choices[0].delta.content, end="", flush=True) print("\n")from openai import OpenAI # Initialize the OpenAI client with Qubrid base URL client = OpenAI( base_url="https://platform.qubrid.com/v1", api_key="QUBRID_API_KEY", ) stream = client.chat.completions.create( model="zai-org/GLM-4.7", messages=[ { "role": "user", "content": "Explain quantum computing in simple terms" } ], max_tokens=4096, temperature=0.6, top_p=1, stream=True ) for chunk in stream: if chunk.choices and chunk.choices[0].delta.content: print(chunk.choices[0].delta.content, end="", flush=True) print("\n") Enterprise
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