FitMyLLM
Alibaba/Dense

AlibabaQwen2-VL 7B

Qwen2-VL 7B — solid vision-language model for image analysis.

chatvision
8.29B
Parameters
32K
Context length
9
Benchmarks
6
Quantizations
400K
HF downloads
Architecture
Dense
Released
2024-10-03
Layers
28
KV Heads
4
Head Dim
128
Family
qwen

Quantization Options

Context length:
QuantBitsVRAM @ 16KQuality
Q4_K_M4.89
6.2 GB
5.6 + 0.7 KV
good
Q5_K_S5.57
6.9 GB
6.3 + 0.7 KV
good
Q5_K_M5.7
7.1 GB
6.4 + 0.7 KV
good
Q6_K6.56
7.9 GB
7.3 + 0.7 KV
excellent
Q8_08.5
10.0 GB
9.3 + 0.7 KV
lossless
FP1616
17.7 GB
17.1 + 0.7 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

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

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Benchmarks (9)

MMBench81.8
IFEval76.4
HumanEval60.0
MMMU54.1
MATH48.8
MMLU-PRO37.5
BBH36.6
MUSR15.5
GPQA8.9

Run this model

Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run qwen:8b-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 Tesla C2070
6 GB VRAM • 143 GB/s
NVIDIA
NVIDIA Tesla C2075
6 GB VRAM • 150 GB/s
NVIDIA
NVIDIA Tesla C2090
6 GB VRAM • 177 GB/s
NVIDIA
NVIDIA Tesla M2070
6 GB VRAM • 150 GB/s
NVIDIA
NVIDIA Tesla M2070-Q
6 GB VRAM • 150 GB/s
NVIDIA
NVIDIA Tesla M2075
6 GB VRAM • 150 GB/s
NVIDIA
NVIDIA Tesla M2090
6 GB VRAM • 177 GB/s
NVIDIA
NVIDIA Tesla X2070
6 GB VRAM • 177 GB/s
NVIDIA
NVIDIA Tesla X2090
6 GB VRAM • 177 GB/s
NVIDIA
NVIDIA Tesla K20X
6 GB VRAM • 250 GB/s
NVIDIA
NVIDIA Tesla K20Xm
6 GB VRAM • 250 GB/s
NVIDIA

Find the best GPU for Qwen2-VL 7B

Build Hardware for Qwen2-VL 7B

Qwen2-VL 7B — solid vision-language model for image analysis.

▸ SPEC SHEET

Qwen2-VL 7B8.29B Dense.

▸ SPECIFICATIONS
PARAMETERS
8.29B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
32K tokens
CAPABILITIES
chat, vision
RELEASE DATE
2024-10-03
PROVIDER
Alibaba
FAMILY
qwen
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
Q4_K_M4.895.6 GB94%
Q5_K_S5.576.3 GB96%
Q5_K_M5.76.4 GB96%
Q6_K6.567.3 GB97%
Q8_08.59.3 GB100%
FP161617.1 GB100%
§ 01BENCHMARK SCORES
HumanEval60.0
MMLU-PRO37.5
MATH48.8
IFEval76.4
BBH36.6
MMMU54.1
GPQA8.9
MUSR15.5
MMBench81.8
§ 02RUN COMMAND

Run Qwen2-VL 7B locally with Ollama — needs 5.6 GB VRAM at Q4_K_M:

$ollama run qwen2-vl:7b
§ 03COMPATIBLE GPUs
30 @ Q4_K_M