FitMyLLM
DeepSeek/Mixture of Experts

DeepSeekDeepSeek-VL2 Small 16B

DeepSeek VL2 Small — vision-language MoE for multimodal understanding.

chatvision
15.7B
Parameters (2.4B active)
4K
Context length
9
Benchmarks
10
Quantizations
50K
HF downloads
Architecture
MoE
Released
2024-12-13
Layers
27
KV Heads
16
Head Dim
128
Family
deepseek

Quantization Options

QuantBitsVRAM @ 4KQuality
Q3_K_M4
8.3 GB
low
Q3_K_L4.3
8.9 GB
moderate
IQ4_XS4.46
9.2 GB
moderate
Q4_K_S4.67
9.7 GB
moderate
Q4_K_M4.89
10.1 GB
good
Q5_K_S5.57
11.4 GB
good
Q5_K_M5.7
11.7 GB
good
Q6_K6.56
13.4 GB
excellent
Q8_08.5
17.2 GB
lossless
FP1616
31.9 GB
lossless

Select your GPU above to see speed estimates and compatibility for each quantization.

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Community Ratings

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Benchmarks (9)

MMBench73.0
MATH57.0
MMMU49.0
IFEval43.8
MMLU-PRO40.7
BBH40.7
BigCodeBench36.8
MUSR28.7
GPQA18.3

Run this model

Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run deepseek:16b-q4_K_M

Tag may need adjustment — check ollama.com/library/deepseek 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 K40c
12 GB VRAM • 288 GB/s
NVIDIA
NVIDIA Tesla K40d
12 GB VRAM • 288 GB/s
NVIDIA
NVIDIA Tesla K40m
12 GB VRAM • 288 GB/s
NVIDIA
NVIDIA Tesla K40s
12 GB VRAM • 288 GB/s
NVIDIA
NVIDIA Tesla K40st
12 GB VRAM • 288 GB/s
NVIDIA
NVIDIA Tesla K40t
12 GB VRAM • 288 GB/s
NVIDIA
NVIDIA Tesla K80
12 GB VRAM • 241 GB/s
NVIDIA
NVIDIA Tesla M40
12 GB VRAM • 288 GB/s
NVIDIA
NVIDIA Tesla P100 PCIe 12 GB
12 GB VRAM • 549 GB/s
NVIDIA
NVIDIA RTX A2000 12 GB
12 GB VRAM • 288 GB/s
NVIDIA
$550

Find the best GPU for DeepSeek-VL2 Small 16B

Build Hardware for DeepSeek-VL2 Small 16B

DeepSeek VL2 Small — vision-language MoE for multimodal understanding.

▸ SPEC SHEET

DeepSeek-VL2 Small 16B15.7B MoE.

▸ SPECIFICATIONS
PARAMETERS
15.7B (2.4B active)
ARCHITECTURE
Mixture of Experts
CONTEXT LENGTH
4K tokens
CAPABILITIES
chat, vision
RELEASE DATE
2024-12-13
PROVIDER
DeepSeek
FAMILY
deepseek
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
Q3_K_M48.3 GB88%
Q3_K_L4.38.9 GB90%
IQ4_XS4.469.2 GB92%
Q4_K_S4.679.7 GB93%
Q4_K_M4.8910.1 GB94%
Q5_K_S5.5711.4 GB96%
Q5_K_M5.711.7 GB96%
Q6_K6.5613.4 GB97%
Q8_08.517.2 GB100%
FP161631.9 GB100%
§ 01BENCHMARK SCORES
MMLU-PRO40.7
MATH57.0
IFEval43.8
BBH40.7
MMMU49.0
GPQA18.3
MUSR28.7
BigCodeBench36.8
MMBench73.0
§ 03COMPATIBLE GPUs
30 @ Q4_K_M