FitMyLLM
Alibaba/Dense

AlibabaQwen2 Math 7B

Qwen2 Math 7B — competitive math model, strong on GSM8K and MATH.

reasoning
7.62B
Parameters
4K
Context length
9
Benchmarks
6
Quantizations
0
Architecture
Dense
Released
2024-08-08
Layers
28
KV Heads
4
Head Dim
128
Family
qwen

Quantization Options

QuantBitsVRAM @ 4KQuality
Q4_K_M4.89
5.1 GB
good
Q5_K_S5.57
5.8 GB
good
Q5_K_M5.7
5.9 GB
good
Q6_K6.56
6.7 GB
excellent
Q8_08.5
8.6 GB
lossless
FP1616
15.7 GB
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 MATH 7B NOW

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

Community Ratings

Loading ratings...

Benchmarks (9)

IFEval75.9
MBPP60.8
MATH50.0
HumanEval45.7
MMLU-PRO36.5
BBH34.9
BigCodeBench29.1
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-math:7b-instruct-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 Qwen2 Math 7B

Build Hardware for Qwen2 Math 7B

Qwen2 Math 7B — competitive math model, strong on GSM8K and MATH.

▸ SPEC SHEET

Qwen2 Math 7B7.62B Dense.

▸ SPECIFICATIONS
PARAMETERS
7.62B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
4K tokens
CAPABILITIES
reasoning
RELEASE DATE
2024-08-08
PROVIDER
Alibaba
FAMILY
qwen
▸ 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_08.58.6 GB100%
FP161615.7 GB100%
§ 01BENCHMARK SCORES
HumanEval45.7
MMLU-PRO36.5
MATH50.0
IFEval75.9
BBH34.9
GPQA5.5
MUSR8.5
MBPP60.8
BigCodeBench29.1
§ 02RUN COMMAND

Run Qwen2 Math 7B locally with Ollama — needs 5.1 GB VRAM at Q4_K_M:

$ollama run qwen2-math:7b
§ 03COMPATIBLE GPUs
30 @ Q4_K_M