FitMyLLM
Alibaba/Dense

AlibabaQwen 3.8 27B

Qwen 3.8 27B — dense, natively vision-language (images and video), hybrid Gated DeltaNet + Gated Attention. Apache 2.0, 256K context natively and extensible to 1M. The single-GPU model of the Qwen3.8 generation.

chatcodingreasoningmultilingualvisionmathagentictool_use
27.78B
Parameters
256K
Context length
3
Benchmarks
10
Quantizations
92K
HF downloads
Architecture
Dense
Released
2026-08-14
Layers
64
KV Heads
4
Head Dim
256
Family
qwen

Quantization Options

Context length:
QuantBitsVRAM @ 16KQuality
Q3_K_M4
15.1 GB
14.4 + 0.8 KV
low
Q3_K_L4.3
16.2 GB
15.4 + 0.8 KV
moderate
IQ4_XS4.46
16.7 GB
16.0 + 0.8 KV
moderate
Q4_K_S4.67
17.5 GB
16.7 + 0.8 KV
moderate
Q4_K_M4.89
18.2 GB
17.5 + 0.8 KV
good
Q5_K_S5.57
20.6 GB
19.8 + 0.8 KV
good
Q5_K_M5.7
21.0 GB
20.3 + 0.8 KV
good
Q6_K6.56
24.0 GB
23.3 + 0.8 KV
excellent
Q8_08.5
30.8 GB
30.0 + 0.8 KV
lossless
FP1616
56.8 GB
56.0 + 0.8 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

RENT A GPU AND RUN QWEN 3.8 27B NOW

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 (3)

LiveCodeBench90.3
GPQA Diamond89.2
HLE30.8

Run this model

▸Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run qwen3.8:27b-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.

Apple M3 Pro (18GB)
18 GB VRAM • 150 GB/s
APPLE
$1599
AMD RX 7900 XT
20 GB VRAM • 800 GB/s
AMD
$849
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA RTX 4000 Ada 20GB
20 GB VRAM • 432 GB/s
NVIDIA
$1250
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA A10M
20 GB VRAM • 500 GB/s
NVIDIA
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA GeForce RTX 3080 Ti 20 GB
20 GB VRAM • 760 GB/s
NVIDIA
$1199
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
AMD Radeon RX 7900 XT
20 GB VRAM • 800 GB/s
AMD
$899
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA RTX 4000 Ada Generation
20 GB VRAM • 360 GB/s
NVIDIA
$1250
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA RTX 4000 SFF Ada Generation
20 GB VRAM • 280 GB/s
NVIDIA
$1250
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA RTX A4500
20 GB VRAM • 640 GB/s
NVIDIA
$2000
NVIDIA RTX 4090
24 GB VRAM • 1008 GB/s
NVIDIA
$1599
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA RTX 3090 Ti
24 GB VRAM • 1008 GB/s
NVIDIA
$999
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA RTX 3090
24 GB VRAM • 936 GB/s
NVIDIA
$850
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
AMD RX 7900 XTX
24 GB VRAM • 960 GB/s
AMD
$999
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
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
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
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
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA Quadro RTX 6000 Passive
24 GB VRAM • 624 GB/s
NVIDIA
$4000
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA GeForce RTX 3090
24 GB VRAM • 936 GB/s
NVIDIA
$1499
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA A10 PCIe
24 GB VRAM • 600 GB/s
NVIDIA
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA A10G
24 GB VRAM • 600 GB/s
NVIDIA
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA RTX A5000
24 GB VRAM • 768 GB/s
NVIDIA
$2500
NVIDIA GeForce RTX 3090 Ti
24 GB VRAM • 1010 GB/s
NVIDIA
$1999
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai
NVIDIA GeForce RTX 4090
24 GB VRAM • 1010 GB/s
NVIDIA
$1599
AmazonNeweggeBayPCPartPickerRent on RunPodRent on Vast.ai

Find the best GPU for Qwen 3.8 27B

Build Hardware for Qwen 3.8 27B
▸ SPEC SHEET

Qwen 3.8 27B — 27.78B Dense.

▸ SPECIFICATIONS
PARAMETERS
27.78B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
256K tokens
CAPABILITIES
chat, coding, reasoning, multilingual, vision, math, agentic, tool_use
RELEASE DATE
2026-08-14
PROVIDER
Alibaba
FAMILY
qwen
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
Q3_K_M414.4 GB88%
Q3_K_L4.315.4 GB90%
IQ4_XS4.4616.0 GB92%
Q4_K_S4.6716.7 GB93%
Q4_K_M4.8917.5 GB94%
Q5_K_S5.5719.8 GB96%
Q5_K_M5.720.3 GB96%
Q6_K6.5623.3 GB97%
Q8_08.530.0 GB100%
FP161656.0 GB100%
§ 01BENCHMARK SCORES
GPQA Diamond89.2
LiveCodeBench90.3
HLE30.8
§ 02RUN COMMAND

Run Qwen 3.8 27B locally with Ollama — needs 17.5 GB VRAM at Q4_K_M:

$ollama run qwen3.8:27b
§ 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