ChatGLM3-6B
Parameters
6B
Context Length
8K
Modality
Text
Architecture
Dense
License
Apache 2.0
Release Date
27 Oct 2023
Knowledge Cutoff
Jul 2023
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
8,192 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
#206
| Benchmark | Score | Rank |
|---|---|---|
General Text | 1056 | 174 |
Rankings
Overall Rank
#206
Coding Rank
-
About ChatGLM3-6B
ChatGLM3-6B is a versatile bilingual language model developed by Zhipu AI and Tsinghua University for conversational AI and tool integration. It natively supports code execution via an integrated interpreter and multi-turn agentic interactions.
Technical Specifications
Attention
Attention Structure
Multi-Head Attention
Attention Heads
32
Key-Value Heads
2
Attention Head Dimension
128
Position Embedding
Absolute Position Embedding
RoPE Theta
-
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
4,096
Number of Layers
28
FFN Intermediate Size (Dense)
13,696
Multi-Token Prediction Heads
-
Tokenizer
Vocabulary Size
65,024
About ChatGLM
ChatGLM series models from Z.ai, based on GLM architecture.