ChatGLM3-6B
Parameters
6B
Context Length
8K
Modality
Text
Architecture
Dense
KV Cache Rate
28 KB/tok
License
Apache 2.0
Release Date
27 Oct 2023
Knowledge Cutoff
Jul 2023
API Pricing (per 1M)
Self-hosted only
Hardware Sizing
Precision
Context
Workload Memory: 5.51 GB
INT4 · 8K context
Base Weights: 2.79 GB
KV Cache: 0.22 GB
Runtime & Graphs: 2.50 GB
Minimum Required Hardware
1x NVIDIA L4 24GB
5.5 / 21.6 GB usable
1x RTX 3060 12GB
5.5 / 10.8 GB usable
Apple M4 24GB
5.5 / 18.0 GB usable
Determine requirements for your specific workload:
Open in VRAM Calculator
Architecture Diagram
Evaluation Benchmarks
Rank
#240
| Benchmark | Score | Rank |
|---|---|---|
General Text | 1057 | 197 |
Rankings
Overall Rank
#240
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
Normalization
RMS Normalization
Activation Function
SwigLU
Dimensions
Hidden Dimension Size
4,096
Number of Layers
28
FFN Intermediate Size (Dense)
13,696
Tokenizer
Vocabulary Size
65,024
About ChatGLM
ChatGLM series models from Z.ai, based on GLM architecture.