FitMyLLM
Alibaba/Dense

AlibabaQwen3-VL 2B Instruct

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

chatvisionmultilingual
2.13B
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

Context length:
QuantBitsVRAM @ 16KQuality
Q4_K_M4.89
3.1 GB
1.8 + 1.3 KV
good
Q5_K_S5.57
3.3 GB
2.0 + 1.3 KV
good
Q5_K_M5.7
3.3 GB
2.0 + 1.3 KV
good
Q6_K6.56
3.5 GB
2.2 + 1.3 KV
excellent
Q8_08.5
4.1 GB
2.8 + 1.3 KV
lossless
FP1616
6.1 GB
4.7 + 1.3 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 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 qwen3-vl:2b-instruct-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

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 Instruct2.13B Dense.

▸ SPECIFICATIONS
PARAMETERS
2.13B
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_M4.891.8 GB94%
Q5_K_S5.572.0 GB96%
Q5_K_M5.72.0 GB96%
Q6_K6.562.2 GB97%
Q8_08.52.8 GB100%
FP16164.7 GB100%
§ 01BENCHMARK SCORES
MMLU-PRO19.8
MATH20.8
IFEval47.7
BBH18.3
GPQA0.0
MUSR4.0
§ 02RUN COMMAND

Run Qwen3-VL 2B Instruct locally with Ollama — needs 1.8 GB VRAM at Q4_K_M:

$ollama run qwen3-vl:2b
§ 03COMPATIBLE GPUs
30 @ Q4_K_M