FitMyLLM
Alibaba/Dense

AlibabaQwen 3.6 27B

> This repository contains model weights and configuration files for the post-trained model in the Hugging Face Transformers format. > These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, KTransformers, etc.

chatcodingreasoningmultilingualvisionmath
27B
Parameters
256K
Context length
16
Benchmarks
10
Quantizations
0
Architecture
Dense
Released
2026-04-22
Layers
64
KV Heads
4
Head Dim
256
Family
qwen

Quantization Options

QuantBitsVRAMQuality
Q3_K_M414.0 GBlow
Q3_K_L4.315.0 GBmoderate
IQ4_XS4.4615.5 GBmoderate
Q4_K_S4.6716.3 GBmoderate
Q4_K_M4.8917.0 GBgood
Q5_K_S5.5719.3 GBgood
Q5_K_M5.719.7 GBgood
Q6_K6.5622.6 GBexcellent
Q8_08.529.2 GBlossless
FP161654.5 GBlossless

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 3.6 27B NOW

Rent on RunPod →Or Vast.ai →

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

Community Ratings

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Benchmarks (16)

τ²-Bench93.6
GPQA Diamond82.9
MATH55.4
AA Long Context55.0
IFBench45.7
MMLU-PRO40.3
BBH38.5
SciCode37.3
AA Intelligence37.1
IFEval34.2
BigCodeBench32.3
AA Coding26.6
MUSR25.2
Terminal-Bench21.2
GPQA18.1
HLE13.6

Run this model

▸Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run qwen:27b-q4_K_M

Tag may need adjustment — check ollama.com/library/qwen for available tags.

▸ 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
HuggingFaceGGUF DownloadsBuild Hardware

GPUs that can run this model

At Q4_K_M quantization. Sorted by minimum VRAM.

Apple M3 Pro (18GB)
18 GB VRAM • 150 GB/s
APPLE
$1599
AMD RX 7900 XT
20 GB VRAM • 800 GB/s
AMD
$849
AmazonNeweggeBayPCPartPicker
NVIDIA RTX 4000 Ada 20GB
20 GB VRAM • 432 GB/s
NVIDIA
$1250
AmazonNeweggeBayPCPartPicker
NVIDIA A10M
20 GB VRAM • 500 GB/s
NVIDIA
AmazonNeweggeBayPCPartPicker
NVIDIA GeForce RTX 3080 Ti 20 GB
20 GB VRAM • 760 GB/s
NVIDIA
$1199
AmazonNeweggeBayPCPartPicker
AMD Radeon RX 7900 XT
20 GB VRAM • 800 GB/s
AMD
$899
AmazonNeweggeBayPCPartPicker
NVIDIA RTX 4000 Ada Generation
20 GB VRAM • 360 GB/s
NVIDIA
$1250
AmazonNeweggeBayPCPartPicker
NVIDIA RTX 4000 SFF Ada Generation
20 GB VRAM • 280 GB/s
NVIDIA
$1250
AmazonNeweggeBayPCPartPicker
NVIDIA RTX A4500
20 GB VRAM • 640 GB/s
NVIDIA
$2000
NVIDIA RTX 4090
24 GB VRAM • 1008 GB/s
NVIDIA
$1599
AmazonNeweggeBayPCPartPicker
NVIDIA RTX 3090 Ti
24 GB VRAM • 1008 GB/s
NVIDIA
$999
AmazonNeweggeBayPCPartPicker
NVIDIA RTX 3090
24 GB VRAM • 936 GB/s
NVIDIA
$850
AmazonNeweggeBayPCPartPicker
AMD RX 7900 XTX
24 GB VRAM • 960 GB/s
AMD
$999
AmazonNeweggeBayPCPartPicker
Apple M4 Pro (24GB)
24 GB VRAM • 273 GB/s
APPLE
$1399
NVIDIA L4 24GB
24 GB VRAM • 300 GB/s
NVIDIA
$2500
NVIDIA A10 24GB
24 GB VRAM • 600 GB/s
NVIDIA
$3500
AmazonNeweggeBayPCPartPicker
Apple M2 (24GB)
24 GB VRAM • 100 GB/s
APPLE
$999
Apple M3 (24GB)
24 GB VRAM • 100 GB/s
APPLE
$999
Apple M4 (24GB)
24 GB VRAM • 120 GB/s
APPLE
$699
NVIDIA Tesla M40 24 GB
24 GB VRAM • 288 GB/s
NVIDIA
NVIDIA Tesla P10
24 GB VRAM • 694 GB/s
NVIDIA
NVIDIA Tesla P40
24 GB VRAM • 347 GB/s
NVIDIA
NVIDIA Quadro RTX 6000
24 GB VRAM • 672 GB/s
NVIDIA
$4000
AmazonNeweggeBayPCPartPicker
NVIDIA Quadro RTX 6000 Passive
24 GB VRAM • 624 GB/s
NVIDIA
$4000
AmazonNeweggeBayPCPartPicker
NVIDIA GeForce RTX 3090
24 GB VRAM • 936 GB/s
NVIDIA
$1499
AmazonNeweggeBayPCPartPicker
NVIDIA A10 PCIe
24 GB VRAM • 600 GB/s
NVIDIA
AmazonNeweggeBayPCPartPicker
NVIDIA A10G
24 GB VRAM • 600 GB/s
NVIDIA
AmazonNeweggeBayPCPartPicker
NVIDIA RTX A5000
24 GB VRAM • 768 GB/s
NVIDIA
$2500
NVIDIA GeForce RTX 3090 Ti
24 GB VRAM • 1010 GB/s
NVIDIA
$1999
AmazonNeweggeBayPCPartPicker
NVIDIA GeForce RTX 4090
24 GB VRAM • 1010 GB/s
NVIDIA
$1599
AmazonNeweggeBayPCPartPicker

Find the best GPU for Qwen 3.6 27B

Build Hardware for Qwen 3.6 27B
▸ SPEC SHEET

Qwen 3.6 27B — 27B Dense.

▸ SPECIFICATIONS
PARAMETERS
27B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
256K tokens
CAPABILITIES
chat, coding, reasoning, multilingual, vision, math
RELEASE DATE
2026-04-22
PROVIDER
Alibaba
FAMILY
qwen
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
Q3_K_M414.0 GB88%
Q3_K_L4.315.0 GB90%
IQ4_XS4.4615.5 GB92%
Q4_K_S4.6716.3 GB93%
Q4_K_M4.8917.0 GB94%
Q5_K_S5.5719.3 GB96%
Q5_K_M5.719.7 GB96%
Q6_K6.5622.6 GB97%
Q8_08.529.2 GB100%
FP161654.5 GB100%
§ 01BENCHMARK SCORES
MMLU-PRO40.3
MATH55.4
IFEval34.2
BBH38.5
GPQA18.1
MUSR25.2
BigCodeBench32.3
GPQA Diamond82.9
HLE13.6
AA Intelligence37.1
AA Coding26.6
aa_ifbench45.7
aa_terminal_bench21.2
aa_tau293.6
aa_scicode37.3
aa_lcr55.0
§ 03COMPATIBLE GPUs
30 @ Q4_K_M
Apple M3 Pro (18GB)
18 GB · 150 GB/s
AMD RX 7900 XT
20 GB · 800 GB/s
NVIDIA RTX 4000 Ada 20GB
20 GB · 432 GB/s
NVIDIA A10M
20 GB · 500 GB/s
NVIDIA GeForce RTX 3080 Ti 20 GB
20 GB · 760 GB/s
AMD Radeon RX 7900 XT
20 GB · 800 GB/s
NVIDIA RTX 4000 Ada Generation
20 GB · 360 GB/s
NVIDIA RTX 4000 SFF Ada Generation
20 GB · 280 GB/s
NVIDIA RTX A4500
20 GB · 640 GB/s
NVIDIA RTX 4090
24 GB · 1008 GB/s
NVIDIA RTX 3090 Ti
24 GB · 1008 GB/s
NVIDIA RTX 3090
24 GB · 936 GB/s
AMD RX 7900 XTX
24 GB · 960 GB/s
Apple M4 Pro (24GB)
24 GB · 273 GB/s
NVIDIA L4 24GB
24 GB · 300 GB/s