GLM-4.7 is a frontier-level open-source model from Zhipu AI featuring a Mixture-of-Experts (MoE) architecture designed to balance computational efficiency with depth. The model represents cutting-edge performance in code generation and reasoning tasks.
- Context Window: 200,000 tokens
- Output Capacity: 128,000 tokens per generation
- Architecture: MoE-based for efficiency
- Can generate complete software frameworks in a single pass
Coding Excellence:
- SWE-bench: 73.8% (5.8% improvement over predecessor)
- SWE-bench Multilingual: 66.7% (12.9% improvement)
- LiveCodeBench-v6: 84.9% (surpassing Claude Sonnet 4.5 at 64%)
- Terminal Bench 2.0: 41% (+16.5% improvement)
Reasoning & Tool Use:
- τ²-Bench: 87.4 (highest for any open-source tool-using model)
- HLE Benchmark: 42.8% (+12.4% improvement)
- AIME 2025: 95.7%
- GPQA-Diamond: 85.7%
- Interleaved Thinking with Preserved Thinking and Turn-level Thinking
- Tool-use capabilities for complex workflows
- Local deployment support via vLLM and SGLang
Supports multiple inference frameworks for flexible local and cloud deployment.