FitMyLLM
Alibaba/Dense

AlibabaQwen3-Embedding 4B

The Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks.

embeddingmultilingual
4B
Parameters
40K
Context length
0
Benchmarks
6
Quantizations
0
Architecture
Dense
Released
2025-06-05
Layers
36
KV Heads
8
Head Dim
128
Family
embedding

Quantization Options

Context length:
QuantBitsVRAM @ 16KQuality
Q4_K_M4.89
4.6 GB
2.9 + 1.7 KV
good
Q5_K_S5.57
5.0 GB
3.3 + 1.7 KV
good
Q5_K_M5.7
5.0 GB
3.3 + 1.7 KV
good
Q6_K6.56
5.5 GB
3.8 + 1.7 KV
excellent
Q8_08.5
6.4 GB
4.7 + 1.7 KV
lossless
FP1616
10.2 GB
8.5 + 1.7 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 QWEN3-EMBEDDING 4B NOW

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

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Run this model

Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run qwen3-embedding:4b-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.

NVIDIA Tesla C2050
3 GB VRAM • 144 GB/s
NVIDIA
NVIDIA Tesla M2050
3 GB VRAM • 148 GB/s
NVIDIA
NVIDIA Tesla S2050
3 GB VRAM • 148 GB/s
NVIDIA

Find the best GPU for Qwen3-Embedding 4B

Build Hardware for Qwen3-Embedding 4B
▸ SPEC SHEET

Qwen3-Embedding 4B4B Dense.

▸ SPECIFICATIONS
PARAMETERS
4B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
40K tokens
CAPABILITIES
embedding, multilingual
RELEASE DATE
2025-06-05
PROVIDER
Alibaba
FAMILY
embedding
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
Q4_K_M4.892.9 GB94%
Q5_K_S5.573.3 GB96%
Q5_K_M5.73.3 GB96%
Q6_K6.563.8 GB97%
Q8_08.54.7 GB100%
FP16168.5 GB100%
§ 02RUN COMMAND

Run Qwen3-Embedding 4B locally with Ollama — needs 2.9 GB VRAM at Q4_K_M:

$ollama run qwen3-embedding:4b
§ 03COMPATIBLE GPUs
30 @ Q4_K_M