FitMyLLM
Alibaba/Dense

AlibabaQwen2.5-VL-7B

pipeline_tag: image-text-to-text

chattool_usevision
8.3B
Parameters
125K
Context length
10
Benchmarks
6
Quantizations
4.9M
HF downloads
Architecture
Dense
Released
2025-01-26
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
8.0 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

RENT A GPU AND RUN QWEN2.5-VL-7B 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 (10)

MMBench82.6
IFEval75.9
MMMU58.6
MATH50.0
MMLU-PRO36.5
BBH34.9
BigCodeBench29.1
GPQA Diamond9.3
MUSR8.5
GPQA5.5

Run this model

▸Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run qwen2.5:8.3b

Tag may need adjustment — check ollama.com/library/qwen2.5 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
HuggingFaceOllama LibraryGGUF DownloadsBuild Hardware

GPUs that can run this model

At Q4_K_M quantization. Sorted by minimum VRAM.

NVIDIA RTX 3050 6GB
6 GB VRAM • 168 GB/s
NVIDIA
$169
AmazonNeweggeBayPCPartPicker
Intel Arc A380
6 GB VRAM • 186 GB/s
INTEL
$129
AmazonNeweggeBayPCPartPicker
NVIDIA RTX 2060 6GB
6 GB VRAM • 336 GB/s
NVIDIA
$150
AmazonNeweggeBayPCPartPicker
NVIDIA GTX 1660 SUPER
6 GB VRAM • 336 GB/s
NVIDIA
$150
AmazonNeweggeBayPCPartPicker
NVIDIA GTX 1660 Ti
6 GB VRAM • 288 GB/s
NVIDIA
$140
AmazonNeweggeBayPCPartPicker
NVIDIA GTX 1060 6GB
6 GB VRAM • 192 GB/s
NVIDIA
$80
AmazonNeweggeBayPCPartPicker
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
NVIDIA GeForce GTX 1060 6 GB
6 GB VRAM • 192 GB/s
NVIDIA
AmazonNeweggeBayPCPartPicker
NVIDIA
AmazonNeweggeBayPCPartPicker
NVIDIA
AmazonNeweggeBayPCPartPicker
NVIDIA
AmazonNeweggeBayPCPartPicker
NVIDIA
AmazonNeweggeBayPCPartPicker
NVIDIA GeForce GTX 1660
6 GB VRAM • 192 GB/s
NVIDIA
AmazonNeweggeBayPCPartPicker
NVIDIA GeForce GTX 1660 SUPER
6 GB VRAM • 336 GB/s
NVIDIA
AmazonNeweggeBayPCPartPicker
NVIDIA GeForce GTX 1660 Ti
6 GB VRAM • 288 GB/s
NVIDIA
AmazonNeweggeBayPCPartPicker
NVIDIA GeForce RTX 2060
6 GB VRAM • 336 GB/s
NVIDIA
$140
AmazonNeweggeBayPCPartPicker
NVIDIA GeForce RTX 2060 TU104
6 GB VRAM • 336 GB/s
NVIDIA
$140
AmazonNeweggeBayPCPartPicker
AMD Radeon RX 5600 OEM
6 GB VRAM • 288 GB/s
AMD
AmazonNeweggeBayPCPartPicker
AMD Radeon RX 5600 XT
6 GB VRAM • 288 GB/s
AMD
$90
AmazonNeweggeBayPCPartPicker
AMD Radeon RX 5600M
6 GB VRAM • 288 GB/s
AMD
AmazonNeweggeBayPCPartPicker

Find the best GPU for Qwen2.5-VL-7B

Build Hardware for Qwen2.5-VL-7B

Model Card

View on HuggingFace

pipeline_tag: image-text-to-text

▸ SPEC SHEET

Qwen2.5-VL-7B — 8.3B Dense.

▸ SPECIFICATIONS
PARAMETERS
8.3B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
125K tokens
CAPABILITIES
chat, tool_use, vision
RELEASE DATE
2025-01-26
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
MMLU-PRO36.5
MATH50.0
IFEval75.9
BBH34.9
MMMU58.6
GPQA5.5
MUSR8.5
BigCodeBench29.1
MMBench82.6
GPQA Diamond9.3
§ 02RUN COMMAND

Run Qwen2.5-VL-7B locally with Ollama — needs 5.6 GB VRAM at Q4_K_M:

$ollama run qwen2.5:8.3b
§ 03COMPATIBLE GPUs
30 @ Q4_K_M
NVIDIA RTX 3050 6GB
6 GB · 168 GB/s
Intel Arc A380
6 GB · 186 GB/s
NVIDIA RTX 2060 6GB
6 GB · 336 GB/s
NVIDIA GTX 1660 SUPER
6 GB · 336 GB/s
NVIDIA GTX 1660 Ti
6 GB · 288 GB/s
NVIDIA GTX 1060 6GB
6 GB · 192 GB/s
NVIDIA Tesla C2070
6 GB · 143 GB/s
NVIDIA Tesla C2075
6 GB · 150 GB/s
NVIDIA Tesla C2090
6 GB · 177 GB/s
NVIDIA Tesla M2070
6 GB · 150 GB/s
NVIDIA Tesla M2070-Q
6 GB · 150 GB/s
NVIDIA Tesla M2075
6 GB · 150 GB/s
NVIDIA Tesla M2090
6 GB · 177 GB/s
NVIDIA Tesla X2070
6 GB · 177 GB/s
NVIDIA Tesla X2090
6 GB · 177 GB/s