ChatGLM-6B
Parameters
6B
Context Length
2K
Modality
Text
Architecture
Dense
License
Apache 2.0
Release Date
14 Mar 2023
Knowledge Cutoff
-
API Pricing (per 1M)
Self-hosted only
System Requirements
VRAM requirements for different quantization methods and context sizes
1,024 tokens
Consumer
1x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
2,048 tokens
Consumer
1x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
Architecture Diagram
Evaluation Benchmarks
Rank
#203
| Benchmark | Score | Rank |
|---|---|---|
General Text | 995 | 174 |
Rankings
Overall Rank
#203
Coding Rank
-
About ChatGLM-6B
ChatGLM-6B is an open-source bilingual dialogue model developed by Tsinghua KEG and Zhipu AI, optimized for consumer-grade GPU deployment. It delivers coherent conversational responses with low memory overhead via INT4 quantization.
Technical Specifications
Attention
Attention Structure
Multi-Head Attention
Attention Heads
32
Key-Value Heads
32
Attention Head Dimension
-
Position Embedding
Absolute Position Embedding
RoPE Theta
-
Sliding Window Attention
No
Sliding Window Size
-
Sliding Window Ratio
-
Linear Attention
-
Linear Attention Ratio
-
Normalization
Layer Normalization
Activation Function
GELU
Dimensions
Hidden Dimension Size
4,096
Number of Layers
28
FFN Intermediate Size (Dense)
16,384
Multi-Token Prediction Heads
-
Tokenizer
Vocabulary Size
130,528
About ChatGLM
ChatGLM series models from Z.ai, based on GLM architecture.