Zhipu AI/Mixture of Experts

GLM 4.5 Air

chatcodingreasoningtool_useThinking
110B
Parameters (12B active)
125K
Context length
8
Benchmarks
4
Quantizations
378K
HF downloads
Architecture
MoE
Released
2025-08-08
Layers
46
KV Heads
8
Head Dim
128
Family
glm

GLM-4.5-Air

Model Introduction

The GLM-4.5 series models are foundation models designed for intelligent agents. GLM-4.5 has 355 billion total parameters with 32 billion active parameters, while GLM-4.5-Air adopts a more compact design with 106 billion total parameters and 12 billion active parameters. GLM-4.5 models unify reasoning, coding, and intelligent agent capabilities to meet the complex demands of intelligent agent applications.

Both GLM-4.5 and GLM-4.5-Air are hybrid reasoning models that provide two modes: thinking mode for complex reasoning and tool usage, and non-thinking mode for immediate responses.

We have open-sourced the base models, hybrid reasoning models, and FP8 versions of the hybrid reasoning models for both GLM-4.5 and GLM-4.5-Air. They are released under the MIT open-source license and can be used commercially and for secondary development.

As demonstrated in our comprehensive evaluation across 12 industry-standard benchmarks, GLM-4.5 achieves exceptional performance with a score of 63.2, in the 3rd place among all the proprietary and open-source models. Notably, GLM-4.5-Air delivers competitive results at 59.8 while maintaining superior efficiency.

For more eval results, show cases, and technical details, please visit our technical blog or technical report.

The model code, tool parser and reasoning parser can be found in the implementation of transformers, vLLM and SGLang.

Quick Start

Please refer our github page for more detail.

Quantizations & VRAM

Q4_K_M4.5 bpw
62.4 GB
VRAM required
94%
Quality
Q6_K6.5 bpw
89.9 GB
VRAM required
97%
Quality
Q8_08 bpw
110.5 GB
VRAM required
100%
Quality
FP1616 bpw
220.5 GB
VRAM required
100%
Quality

Benchmarks (8)

MATH-50096.5
AIME80.7
AA Math80.7
GPQA Diamond73.3
LiveCodeBench68.4
AA Coding23.8
AA Intelligence23.2
HLE6.8

GPUs that can run this model

At Q4_K_M quantization. Sorted by minimum VRAM.

Apple M1 Ultra (64GB)
64 GB VRAM • 800 GB/s
APPLE
$2499
Apple M2 Ultra (64GB)
64 GB VRAM • 800 GB/s
APPLE
$2999
Apple M4 Max (64GB)
64 GB VRAM • 546 GB/s
APPLE
$2899
Apple M2 Max (64GB)
64 GB VRAM • 400 GB/s
APPLE
$2299
Apple M3 Max (64GB)
64 GB VRAM • 300 GB/s
APPLE
$2799
Apple M4 Pro (64GB)
64 GB VRAM • 273 GB/s
APPLE
$2599
AMD Radeon Instinct MI200
64 GB VRAM • 1640 GB/s
AMD
AMD Radeon Instinct MI210
64 GB VRAM • 1640 GB/s
AMD
NVIDIA H100 SXM5 64 GB
64 GB VRAM • 2020 GB/s
NVIDIA
NVIDIA Jetson AGX Orin 64 GB
64 GB VRAM • 205 GB/s
NVIDIA
NVIDIA Jetson T4000
64 GB VRAM • 273 GB/s
NVIDIA
NVIDIA RTX PRO 5000 72 GB Blackwell
72 GB VRAM • 1340 GB/s
NVIDIA
NVIDIA H100 SXM5 80GB
80 GB VRAM • 3350 GB/s
NVIDIA
$25000
NVIDIA H100 PCIe 80GB
80 GB VRAM • 2000 GB/s
NVIDIA
$25000
NVIDIA A100 SXM 80GB
80 GB VRAM • 2039 GB/s
NVIDIA
$10000
NVIDIA A100 PCIe 80GB
80 GB VRAM • 1935 GB/s
NVIDIA
$10000
NVIDIA A100 SXM4 80 GB
80 GB VRAM • 2040 GB/s
NVIDIA
NVIDIA A100 PCIe 80 GB
80 GB VRAM • 1940 GB/s
NVIDIA
NVIDIA A100X
80 GB VRAM • 2040 GB/s
NVIDIA
NVIDIA H100 PCIe 80 GB
80 GB VRAM • 2040 GB/s
NVIDIA
NVIDIA H100 SXM5 80 GB
80 GB VRAM • 3360 GB/s
NVIDIA
NVIDIA H100 CNX
80 GB VRAM • 2040 GB/s
NVIDIA
NVIDIA A800 PCIe 80 GB
80 GB VRAM • 1940 GB/s
NVIDIA
NVIDIA A800 SXM4 80 GB
80 GB VRAM • 2040 GB/s
NVIDIA
NVIDIA H800 PCIe 80 GB
80 GB VRAM • 2040 GB/s
NVIDIA
NVIDIA H800 SXM5
80 GB VRAM • 3360 GB/s
NVIDIA
NVIDIA RTX 6000D
84 GB VRAM • 1570 GB/s
NVIDIA
NVIDIA B200
90 GB VRAM • 4100 GB/s
NVIDIA
NVIDIA H100 NVL 94 GB
94 GB VRAM • 3940 GB/s
NVIDIA
NVIDIA H100 SXM5 94 GB
94 GB VRAM • 3360 GB/s
NVIDIA

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