Alibaba/Dense

AlibabaQwen3-VL 2B Instruct

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

chatvisionmultilingual
2B
Parameters
256K
Context length
6
Benchmarks
6
Quantizations
0
Architecture
Dense
Released
2025-10-15
Layers
28
KV Heads
8
Head Dim
128
Family
qwen

Quantization Options

QuantBitsVRAMQuality
Q4_K_M4.891.7 GBgood
Q5_K_S5.571.9 GBgood
Q5_K_M5.71.9 GBgood
Q6_K6.562.1 GBexcellent
Q8_08.52.6 GBlossless
FP16164.5 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 2B INSTRUCT NOW

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

Community Ratings

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Benchmarks (6)

IFEval47.7
MATH20.8
MMLU-PRO19.8
BBH18.3
MUSR4.0
GPQA0.0

Run this model

Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run qwen:2b-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.

Find the best GPU for Qwen3-VL 2B Instruct

Build Hardware for Qwen3-VL 2B Instruct
▸ SPEC SHEET

Qwen3-VL 2B Instruct2B Dense.

▸ SPECIFICATIONS
PARAMETERS
2B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
256K tokens
CAPABILITIES
chat, vision, multilingual
RELEASE DATE
2025-10-15
PROVIDER
Alibaba
FAMILY
qwen
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
Q4_K_M4.891.7 GB94%
Q5_K_S5.571.9 GB96%
Q5_K_M5.71.9 GB96%
Q6_K6.562.1 GB97%
Q8_08.52.6 GB100%
FP16164.5 GB100%
§ 01BENCHMARK SCORES
MMLU-PRO19.8
MATH20.8
IFEval47.7
BBH18.3
GPQA0.0
MUSR4.0