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GLM-5

Active Parameters

744B

Context Length

205K

Modality

Multimodal

Architecture

Mixture of Experts (MoE)

License

MIT

Release Date

12 Feb 2026

Knowledge Cutoff

Dec 2025

API Pricing (per 1M)

Input: $1.00 · Output: $3.20

System Requirements

VRAM requirements for different quantization methods and context sizes

1,024 tokens

1565.31 GB VRAM

Consumer

98x RTX 4090

24GB VRAM

Datacenter

25x NVIDIA A100

80GB VRAM

Apple Silicon

21x Apple M3 Max

128GB VRAM

204,800 tokens

1845.76 GB VRAM

Consumer

119x RTX 4090

24GB VRAM

Datacenter

30x NVIDIA A100

80GB VRAM

Apple Silicon

26x Apple M3 Max

128GB VRAM

Architecture Diagram

Input TokensToken EmbeddingPosition: AbsoluteHidden: 6.1k · Context: 205K · Vocab: 154.9kx 80 layersRMSNormPre-AttentionMulti-Head Attention64Q / 64KV headsHead dim: 64+RMSNormPre-FFNSparse MoE FFN (8/256 experts)SwishIntermediate: 2k+Final RMSNormOutput Logits

Evaluation Benchmarks

Rank

#60

BenchmarkScoreRank

Software Engineering

SWE-bench Verified

0.73

10

0.551

21

General Text

Text Arena

1458

45

Web Development

WebDev Arena

1436

53

Intelligence Index

Artificial Analysis

0.26

114

Rankings

Overall Rank

#60

Coding Rank

#55

About GLM-5

GLM-5 is Z.ai's 744B-parameter flagship Mixture-of-Experts multimodal foundation model activating 40B parameters for complex systems engineering. Featuring DeepSeek Sparse Attention and open weights, it supports up to 128K token generations over a 205K context window.

Technical Specifications

Attention

Attention Structure

Multi-Head Attention

Attention Heads

64

Key-Value Heads

64

Attention Head Dimension

64

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

Swish

Dimensions

Hidden Dimension Size

6,144

Number of Layers

80

FFN Intermediate Size (Dense)

2,048

Multi-Token Prediction Heads

1

Tokenizer

Vocabulary Size

154,880

Mixture of Experts

Total Expert Parameters

40.0B

Number of Experts

256

Active Experts

8

Shared Experts

1

FFN Intermediate Size (per Expert)

2,048

Dense Layers Before MoE

3

About GLM 5

GLM 5 is the fifth generation of General Language Models developed by Z.ai. It represents a significant leap in multimodal foundational capabilities, featuring advanced reasoning and long-horizon agentic capabilities across diverse systems engineering tasks.


Other GLM 5 Models
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