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ChatGLM2-6B

Parameters

6B

Context Length

33K

Modality

Text

Architecture

Dense

License

Custom License (ChatGLM2-6B License)

Release Date

25 Jun 2023

Knowledge Cutoff

-

API Pricing (per 1M)

Self-hosted only

System Requirements

VRAM requirements for different quantization methods and context sizes

1,024 tokens

14.13 GB VRAM

Consumer

1x RTX 4090

24GB VRAM

Datacenter

1x NVIDIA A100

80GB VRAM

Apple Silicon

1x Apple M3 Max

128GB VRAM

32,768 tokens

15.09 GB VRAM

Consumer

1x RTX 4090

24GB VRAM

Datacenter

1x NVIDIA A100

80GB VRAM

Apple Silicon

1x Apple M3 Max

128GB VRAM

Architecture Diagram

Input TokensToken EmbeddingPosition: AbsoluteHidden: 4.1k · Context: 33K · Vocab: 65kx 28 layersRMSNormPre-AttentionMulti-Head Attention32Q / 2KV headsHead dim: 128+RMSNormPre-FFNFeed-Forward NetworkSwiGLUIntermediate: 13.7k+Final RMSNormOutput Logits

Evaluation Benchmarks

Rank

#202

BenchmarkScoreRank

General Text

Text Arena

1024

159

Rankings

Overall Rank

#202

Coding Rank

-

About ChatGLM2-6B

ChatGLM2-6B is the second-generation bilingual conversational model by THUDM featuring Multi-Query Attention and FlashAttention. It offers improved inference speed, low latency, and extended context retention on consumer hardware.

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.


Other ChatGLM Models