Alibaba/Dense

AlibabaQwen3-VL 32B Instruct

Meet Qwen3-VL — the most powerful vision-language model in the Qwen series to date.

chatvisionmultilingualreasoning
32B
Parameters
256K
Context length
22
Benchmarks
14
Quantizations
0
Architecture
Dense
Released
2025-10-15
Layers
64
KV Heads
8
Head Dim
128
Family
qwen

Quantization Options

QuantBitsVRAMQuality
IQ3_XXS3.2513.5 GBlow
IQ3_XS3.514.5 GBlow
Q3_K_S3.6415.0 GBlow
IQ3_M3.7615.5 GBlow
Q3_K_M416.5 GBlow
Q3_K_L4.317.7 GBmoderate
IQ4_XS4.4618.3 GBmoderate
Q4_K_S4.6719.2 GBmoderate
Q4_K_M4.8920.0 GBgood
Q5_K_S5.5722.8 GBgood
Q5_K_M5.723.3 GBgood
Q6_K6.5626.7 GBexcellent
Q8_08.534.5 GBlossless
FP161664.5 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 QWEN3-VL 32B INSTRUCT NOW

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

Community Ratings

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Benchmarks (22)

HumanEval87.2
IFEval78.9
MBPP77.0
AIME68.3
AA Math68.3
MATH-50068.3
GPQA Diamond67.1
MATH59.7
BBH58.3
MMLU-PRO52.9
LiveCodeBench51.4
IFBench39.2
BigCodeBench32.3
AA Long Context31.3
SciCode30.1
τ²-Bench29.2
MUSR19.1
AA Intelligence17.2
AA Coding15.6
GPQA15.2
Terminal-Bench8.3
HLE6.3

Run this model

Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run qwen:32b-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

GPUs that can run this model

At Q4_K_M quantization. Sorted by minimum VRAM.

NVIDIA RTX 4090
24 GB VRAM • 1008 GB/s
NVIDIA
$1599
NVIDIA RTX 3090 Ti
24 GB VRAM • 1008 GB/s
NVIDIA
$999
NVIDIA RTX 3090
24 GB VRAM • 936 GB/s
NVIDIA
$850
AMD RX 7900 XTX
24 GB VRAM • 960 GB/s
AMD
$999
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
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
NVIDIA GeForce RTX 3090
24 GB VRAM • 936 GB/s
NVIDIA
$1499
NVIDIA A10 PCIe
24 GB VRAM • 600 GB/s
NVIDIA
NVIDIA A10G
24 GB VRAM • 600 GB/s
NVIDIA
NVIDIA RTX A5000
24 GB VRAM • 768 GB/s
NVIDIA
$2500
NVIDIA GeForce RTX 4090
24 GB VRAM • 1010 GB/s
NVIDIA
$1599
NVIDIA L40 CNX
24 GB VRAM • 864 GB/s
NVIDIA
$5000
NVIDIA L40G
24 GB VRAM • 864 GB/s
NVIDIA
$5000
NVIDIA A30 PCIe
24 GB VRAM • 933 GB/s
NVIDIA
NVIDIA A30X
24 GB VRAM • 1220 GB/s
NVIDIA

Find the best GPU for Qwen3-VL 32B Instruct

Build Hardware for Qwen3-VL 32B Instruct
▸ SPEC SHEET

Qwen3-VL 32B Instruct32B Dense.

▸ SPECIFICATIONS
PARAMETERS
32B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
256K tokens
CAPABILITIES
chat, vision, multilingual, reasoning
RELEASE DATE
2025-10-15
PROVIDER
Alibaba
FAMILY
qwen
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
IQ3_XXS3.2513.5 GB82%
IQ3_XS3.514.5 GB84%
Q3_K_S3.6415.0 GB85%
IQ3_M3.7615.5 GB86%
Q3_K_M416.5 GB88%
Q3_K_L4.317.7 GB90%
IQ4_XS4.4618.3 GB92%
Q4_K_S4.6719.2 GB93%
Q4_K_M4.8920.0 GB94%
Q5_K_S5.5722.8 GB96%
Q5_K_M5.723.3 GB96%
Q6_K6.5626.7 GB97%
Q8_08.534.5 GB100%
FP161664.5 GB100%
§ 01BENCHMARK SCORES
HumanEval87.2
MMLU-PRO52.9
MATH59.7
IFEval78.9
BBH58.3
GPQA15.2
MUSR19.1
MBPP77.0
BigCodeBench32.3
GPQA Diamond67.1
LiveCodeBench51.4
AIME68.3
HLE6.3
AA Intelligence17.2
AA Coding15.6
AA Math68.3
aa_ifbench39.2
aa_terminal_bench8.3
aa_tau229.2
aa_scicode30.1
aa_lcr31.3
MATH-50068.3