Alibaba/Dense

Qwen 1.5 110B

Name: Qwen 1.5 110B
Author: Alibaba

Qwen 1.5 110B — largest dense Qwen model.

chat

110B

Parameters

32K

Context length

Benchmarks

Quantizations

Architecture

Dense

Released

2024-02-04

Layers

KV Heads

Head Dim

128

Family

qwen

Quantization Options

Quant	Bits	VRAM	Quality
IQ2_XXS	2.38	33.2 GB	low
IQ2_M	2.93	40.8 GB	low
Q2_K	3.16	43.9 GB	low
IQ3_XXS	3.25	45.2 GB	low
IQ3_XS	3.5	48.6 GB	low
Q3_K_S	3.64	50.5 GB	low
IQ3_M	3.76	52.2 GB	low
Q3_K_M	4	55.5 GB	low
Q3_K_L	4.3	59.6 GB	moderate
IQ4_XS	4.46	61.8 GB	moderate
Q4_K_S	4.67	64.7 GB	moderate
Q4_K_M	4.89	67.7 GB	good
Q5_K_S	5.57	77.1 GB	good
Q5_K_M	5.7	78.9 GB	good
Q6_K	6.56	90.7 GB	excellent
Q8_0	8.5	117.4 GB	lossless
FP16	16	220.5 GB	lossless

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

▸ READY TO RUN THIS?RENT BY THE HOUR

RENT A GPU AND RUN QWEN 1.5 110B NOW

Rent on RunPod →Or Vast.ai →

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

Community Ratings

Loading ratings...

Benchmarks (7)

IFEval59.4

BBH45.0

MMLU-PRO42.5

BigCodeBench35.0

MATH23.4

MUSR16.3

GPQA12.2

Run this model

▸Easiest way to get started·Beginners

DOCS ↗

curl -fsSL https://ollama.com/install.sh | sh

$ollama run qwen:110b-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

HuggingFace Ollama Library GGUF Downloads Build Hardware