GLM-4.5
Active Parameters
355B
Context Length
128K
Modality
Multimodal
Architecture
Mixture of Experts (MoE)
License
MIT License
Release Date
28 Jul 2025
Knowledge Cutoff
Jan 2025
System Requirements
VRAM requirements for different quantization methods and context sizes
1,024 tokens
Consumer
41x RTX 4090
24GB VRAM
Datacenter
11x NVIDIA A100
80GB VRAM
Apple Silicon
9x Apple M3 Max
128GB VRAM
128,000 tokens
Consumer
45x RTX 4090
24GB VRAM
Datacenter
12x NVIDIA A100
80GB VRAM
Apple Silicon
9x Apple M3 Max
128GB VRAM
Architecture Diagram
Evaluation Benchmarks
Rank
#81
| Benchmark | Score | Rank |
|---|---|---|
Professional Knowledge | 0.81 | 23 |
Graduate-Level QA | 0.791 | 25 |
General Text | 1411 | 100 |
Rankings
Overall Rank
#81
Coding Rank
-
About GLM-4.5
GLM-4.5 is Z.ai's 355B-parameter flagship Mixture-of-Experts model activating 32B parameters for advanced systems engineering and agentic workflows. It features dual Thinking/Non-Thinking modes, native function calling, and a 128K context window.
Technical Specifications
Attention
Attention Structure
Multi-Head Attention
Attention Heads
96
Key-Value Heads
8
Attention Head Dimension
128
Position Embedding
Absolute Position Embedding
RoPE Theta
1,000,000
Sliding Window Attention
No
Sliding Window Size
-
Sliding Window Ratio
-
Linear Attention
-
Linear Attention Ratio
-
Normalization
RMS Normalization
Activation Function
SwigLU
Dimensions
Hidden Dimension Size
5,120
Number of Layers
96
FFN Intermediate Size (Dense)
1,536
Multi-Token Prediction Heads
1
Tokenizer
Vocabulary Size
151,552
Mixture of Experts
Total Expert Parameters
32.0B
Number of Experts
160
Active Experts
8
Shared Experts
1
FFN Intermediate Size (per Expert)
1,536
Dense Layers Before MoE
3
About GLM Family
General Language Models from Z.ai