FitMyLLM
Zhipu AI/Dense

Zhipu AIglm-4-9b

2024/11/25, 我们建议使用从 transformers>=4.46.0 开始，使用 glm-4-9b-chat-hf 以减少后续 transformers 升级导致的兼容性问题。

chatTool Use
9.4B
Parameters
128K
Context length
6
Benchmarks
6
Quantizations
152K
HF downloads
Architecture
Dense
Released
2024-06-04
Layers
40
KV Heads
2
Head Dim
128
Family
glm

Quantization Options

Context length:
QuantBitsVRAM @ 16KQuality
Q4_K_M4.89
6.7 GB
6.2 + 0.5 KV
good
Q5_K_S5.57
7.5 GB
7.0 + 0.5 KV
good
Q5_K_M5.7
7.7 GB
7.2 + 0.5 KV
good
Q6_K6.56
8.7 GB
8.2 + 0.5 KV
excellent
Q8_08.5
10.9 GB
10.5 + 0.5 KV
lossless
FP1616
19.8 GB
19.3 + 0.5 KV
lossless

Select your GPU above to see speed estimates and compatibility for each quantization.

Deploying for a team or in production? Size GPUs, cost & scaling in Enterprise →
▸ READY TO RUN THIS?RENT BY THE HOUR

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Rent on Vast.ai →Or RunPod →

Spin up an A100 / H100 / 4090 in ~60s. Pay by the second. Cancel anytime.

Community Ratings

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Benchmarks (6)

IFEval65.1
BBH20.7
MMLU-PRO19.7
MATH8.5
GPQA7.0
MUSR2.2

Run this model

▸Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run glm4:9b-chat-q4_K_M

Downloads and runs automatically. Add --verbose for speed stats.

▸ SETUP GUIDE
>_

Auto-setup with fitmyllm CLI

Detects your GPU, recommends the best model, downloads it, and starts chatting — zero config. Benchmarks your speed and contributes anonymous data to improve predictions.

pip install fitmyllmthen run fitmyllmLearn more
Auto-detect GPULive tok/s in chatSpeed benchmarks9 inference engines
HuggingFaceOllama LibraryGGUF DownloadsBuild Hardware

GPUs that can run this model

At Q4_K_M quantization. Sorted by minimum VRAM.

NVIDIA RTX 4060 Ti 8GB
8 GB VRAM • 288 GB/s
NVIDIA
$399
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA RTX 4060
8 GB VRAM • 272 GB/s
NVIDIA
$299
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA RTX 3070 Ti
8 GB VRAM • 608 GB/s
NVIDIA
$499
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA RTX 3070
8 GB VRAM • 448 GB/s
NVIDIA
$325
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA RTX 3060 Ti
8 GB VRAM • 448 GB/s
NVIDIA
$250
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA RTX 3050 8GB
8 GB VRAM • 224 GB/s
NVIDIA
$249
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
AMD RX 7600
8 GB VRAM • 288 GB/s
AMD
$269
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
AMD RX 6650 XT
8 GB VRAM • 280 GB/s
AMD
$399
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
Intel Arc A750
8 GB VRAM • 512 GB/s
INTEL
$199
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
Apple M1 (8GB)
8 GB VRAM • 68 GB/s
APPLE
$499
Apple M2 (8GB)
8 GB VRAM • 100 GB/s
APPLE
$599
Apple M3 (8GB)
8 GB VRAM • 100 GB/s
APPLE
$599
NVIDIA RTX 2080 SUPER
8 GB VRAM • 496 GB/s
NVIDIA
$280
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA RTX 2080
8 GB VRAM • 448 GB/s
NVIDIA
$260
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA RTX 2070 SUPER
8 GB VRAM • 448 GB/s
NVIDIA
$240
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA RTX 2070
8 GB VRAM • 448 GB/s
NVIDIA
$200
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA RTX 2060 SUPER
8 GB VRAM • 448 GB/s
NVIDIA
$180
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA GTX 1080
8 GB VRAM • 320 GB/s
NVIDIA
$130
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA GTX 1070 Ti
8 GB VRAM • 256 GB/s
NVIDIA
$120
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA GTX 1070
8 GB VRAM • 256 GB/s
NVIDIA
$100
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA RTX 3060 8GB
8 GB VRAM • 224 GB/s
NVIDIA
$280
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
AMD RX 6600 XT
8 GB VRAM • 256 GB/s
AMD
$200
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
AMD RX 6600
8 GB VRAM • 224 GB/s
AMD
$165
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
AMD RX 5700 XT
8 GB VRAM • 448 GB/s
AMD
$150
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
AMD RX 5700
8 GB VRAM • 448 GB/s
AMD
$130
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
Intel Arc A580
8 GB VRAM • 512 GB/s
INTEL
$179
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA RTX 5060 Ti 8GB
8 GB VRAM • 448 GB/s
NVIDIA
$379
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA RTX 5060
8 GB VRAM • 448 GB/s
NVIDIA
$299
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA Tesla K8
8 GB VRAM • 160 GB/s
NVIDIA
NVIDIA Tesla M60
8 GB VRAM • 160 GB/s
NVIDIA

Find the best GPU for glm-4-9b

Build Hardware for glm-4-9b

Model Card

View on HuggingFace

2024/11/25, 我们建议使用从 transformers>=4.46.0 开始，使用 glm-4-9b-chat-hf 以减少后续 transformers 升级导致的兼容性问题。

▸ SPEC SHEET

glm-4-9b — 9.4B Dense.

▸ SPECIFICATIONS
PARAMETERS
9.4B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
128K tokens
CAPABILITIES
chat
RELEASE DATE
2024-06-04
PROVIDER
Zhipu AI
FAMILY
glm
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
Q4_K_M4.896.2 GB94%
Q5_K_S5.577.0 GB96%
Q5_K_M5.77.2 GB96%
Q6_K6.568.2 GB97%
Q8_08.510.5 GB100%
FP161619.3 GB100%
§ 01BENCHMARK SCORES
MMLU-PRO19.7
MATH8.5
IFEval65.1
BBH20.7
GPQA7.0
MUSR2.2
§ 02RUN COMMAND

Run glm-4-9b locally with Ollama — needs 6.2 GB VRAM at Q4_K_M:

$ollama run glm4:9b
§ 03COMPATIBLE GPUs
30 @ Q4_K_M
NVIDIA RTX 4060 Ti 8GB
8 GB · 288 GB/s
NVIDIA RTX 4060
8 GB · 272 GB/s
NVIDIA RTX 3070 Ti
8 GB · 608 GB/s
NVIDIA RTX 3070
8 GB · 448 GB/s
NVIDIA RTX 3060 Ti
8 GB · 448 GB/s
NVIDIA RTX 3050 8GB
8 GB · 224 GB/s
AMD RX 7600
8 GB · 288 GB/s
AMD RX 6650 XT
8 GB · 280 GB/s
Intel Arc A750
8 GB · 512 GB/s
Apple M1 (8GB)
8 GB · 68 GB/s
Apple M2 (8GB)
8 GB · 100 GB/s
Apple M3 (8GB)
8 GB · 100 GB/s
NVIDIA RTX 2080 SUPER
8 GB · 496 GB/s
NVIDIA RTX 2080
8 GB · 448 GB/s
NVIDIA RTX 2070 SUPER
8 GB · 448 GB/s