FitMyLLM
Alibaba/Dense

AlibabaQwen 1.5 14B

Qwen 1.5 14B — strong Chinese-English model at the 14B scale.

chat
14B
Parameters
32K
Context length
7
Benchmarks
10
Quantizations
0
Architecture
Dense
Released
2024-02-04
Layers
40
KV Heads
40
Head Dim
128
Family
qwen

Quantization Options

Context length:
QuantBitsVRAM @ 16KQuality
Q3_K_M4
16.9 GB
7.5 + 9.4 KV
low
Q3_K_L4.3
17.4 GB
8.0 + 9.4 KV
moderate
IQ4_XS4.46
17.7 GB
8.3 + 9.4 KV
moderate
Q4_K_S4.67
18.0 GB
8.7 + 9.4 KV
moderate
Q4_K_M4.89
18.4 GB
9.0 + 9.4 KV
good
Q5_K_S5.57
19.6 GB
10.2 + 9.4 KV
good
Q5_K_M5.7
19.8 GB
10.5 + 9.4 KV
good
Q6_K6.56
21.3 GB
12.0 + 9.4 KV
excellent
Q8_08.5
24.7 GB
15.4 + 9.4 KV
lossless
FP1616
37.9 GB
28.5 + 9.4 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 QWEN 1.5 14B NOW

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

Community Ratings

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Benchmarks (7)

IFEval84.1
MATH53.0
BBH45.7
MMLU-PRO42.8
BigCodeBench39.8
GPQA12.4
MUSR11.4

Run this model

Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run qwen:14b-chat-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 CMP 170HX 10 GB
10 GB VRAM • 1560 GB/s
NVIDIA
NVIDIA CMP 50HX
10 GB VRAM • 560 GB/s
NVIDIA
NVIDIA CMP 90HX
10 GB VRAM • 760 GB/s
NVIDIA
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

Find the best GPU for Qwen 1.5 14B

Build Hardware for Qwen 1.5 14B

Qwen 1.5 14B — strong Chinese-English model at the 14B scale.

▸ SPEC SHEET

Qwen 1.5 14B14B Dense.

▸ SPECIFICATIONS
PARAMETERS
14B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
32K tokens
CAPABILITIES
chat
RELEASE DATE
2024-02-04
PROVIDER
Alibaba
FAMILY
qwen
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
Q3_K_M47.5 GB88%
Q3_K_L4.38.0 GB90%
IQ4_XS4.468.3 GB92%
Q4_K_S4.678.7 GB93%
Q4_K_M4.899.0 GB94%
Q5_K_S5.5710.2 GB96%
Q5_K_M5.710.5 GB96%
Q6_K6.5612.0 GB97%
Q8_08.515.4 GB100%
FP161628.5 GB100%
§ 01BENCHMARK SCORES
MMLU-PRO42.8
MATH53.0
IFEval84.1
BBH45.7
GPQA12.4
MUSR11.4
BigCodeBench39.8
§ 02RUN COMMAND

Run Qwen 1.5 14B locally with Ollama — needs 9.0 GB VRAM at Q4_K_M:

$ollama run qwen:14b
§ 03COMPATIBLE GPUs
30 @ Q4_K_M