FitMyLLM
Alibaba/Dense

AlibabaQwen3-Embedding 8B

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

embeddingmultilingual
7.57B
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
6.8 GB
5.1 + 1.7 KV
good
Q5_K_S5.57
7.4 GB
5.8 + 1.7 KV
good
Q5_K_M5.7
7.6 GB
5.9 + 1.7 KV
good
Q6_K6.56
8.4 GB
6.7 + 1.7 KV
excellent
Q8_08.5
10.2 GB
8.5 + 1.7 KV
lossless
FP1616
17.3 GB
15.6 + 1.7 KV
lossless

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

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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:8b-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 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 Qwen3-Embedding 8B

Build Hardware for Qwen3-Embedding 8B
▸ SPEC SHEET

Qwen3-Embedding 8B7.57B Dense.

▸ SPECIFICATIONS
PARAMETERS
7.57B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
40K tokens
CAPABILITIES
embedding, multilingual
RELEASE DATE
2025-06-05
PROVIDER
Alibaba
FAMILY
embedding
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
Q4_K_M4.895.1 GB94%
Q5_K_S5.575.8 GB96%
Q5_K_M5.75.9 GB96%
Q6_K6.566.7 GB97%
Q8_08.58.5 GB100%
FP161615.6 GB100%
§ 02RUN COMMAND

Run Qwen3-Embedding 8B locally with Ollama — needs 5.1 GB VRAM at Q4_K_M:

$ollama run qwen3-embedding:8b
§ 03COMPATIBLE GPUs
30 @ Q4_K_M