FitMyLLM
Alibaba/Dense

AlibabaQwen 3.5 9B

Qwen 3.5 9B — multimodal model with math, coding, vision, and 201 languages.

chatcodingreasoningmultilingualvisionmath
9B
Parameters
256K
Context length
18
Benchmarks
6
Quantizations
500K
HF downloads
Architecture
Dense
Released
2026-02-01
Layers
32
KV Heads
4
Head Dim
256
Family
qwen

Quantization Options

QuantBitsVRAMQuality
Q4_K_M4.896.0 GBgood
Q5_K_S5.576.8 GBgood
Q5_K_M5.76.9 GBgood
Q6_K6.567.9 GBexcellent
Q8_08.510.1 GBlossless
FP161618.5 GBlossless

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

▸ READY TO RUN THIS?RENT BY THE HOUR

RENT A GPU AND RUN QWEN 3.5 9B NOW

Rent on RunPod →Or Vast.ai →

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

Community Ratings

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Benchmarks (18)

Arena Elo1470
IFEval91.5
MMBench90.1
τ²-Bench86.8
MMLU-PRO82.5
GPQA Diamond80.6
MMMU70.1
IFBench66.7
AA Long Context59.0
MATH48.8
BBH36.6
AA Intelligence32.4
SciCode27.5
AA Coding25.3
Terminal-Bench24.2
MUSR15.5
HLE13.3
GPQA8.9

Run this model

▸Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run qwen3.5:9b-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
HuggingFaceOllama LibraryGGUF DownloadsBuild Hardware

GPUs that can run this model

At Q4_K_M quantization. Sorted by minimum VRAM.

NVIDIA RTX 3050 6GB
6 GB VRAM • 168 GB/s
NVIDIA
$169
AmazonNeweggeBayPCPartPicker
Intel Arc A380
6 GB VRAM • 186 GB/s
INTEL
$129
AmazonNeweggeBayPCPartPicker
NVIDIA RTX 2060 6GB
6 GB VRAM • 336 GB/s
NVIDIA
$150
AmazonNeweggeBayPCPartPicker
NVIDIA GTX 1660 SUPER
6 GB VRAM • 336 GB/s
NVIDIA
$150
AmazonNeweggeBayPCPartPicker
NVIDIA GTX 1660 Ti
6 GB VRAM • 288 GB/s
NVIDIA
$140
AmazonNeweggeBayPCPartPicker
NVIDIA GTX 1060 6GB
6 GB VRAM • 192 GB/s
NVIDIA
$80
AmazonNeweggeBayPCPartPicker
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
NVIDIA GeForce GTX 1060 6 GB
6 GB VRAM • 192 GB/s
NVIDIA
AmazonNeweggeBayPCPartPicker
NVIDIA
AmazonNeweggeBayPCPartPicker
NVIDIA
AmazonNeweggeBayPCPartPicker
NVIDIA
AmazonNeweggeBayPCPartPicker
NVIDIA
AmazonNeweggeBayPCPartPicker
NVIDIA GeForce GTX 1660
6 GB VRAM • 192 GB/s
NVIDIA
AmazonNeweggeBayPCPartPicker
NVIDIA GeForce GTX 1660 SUPER
6 GB VRAM • 336 GB/s
NVIDIA
AmazonNeweggeBayPCPartPicker
NVIDIA GeForce GTX 1660 Ti
6 GB VRAM • 288 GB/s
NVIDIA
AmazonNeweggeBayPCPartPicker
NVIDIA GeForce RTX 2060
6 GB VRAM • 336 GB/s
NVIDIA
$140
AmazonNeweggeBayPCPartPicker
NVIDIA GeForce RTX 2060 TU104
6 GB VRAM • 336 GB/s
NVIDIA
$140
AmazonNeweggeBayPCPartPicker
AMD Radeon RX 5600 OEM
6 GB VRAM • 288 GB/s
AMD
AmazonNeweggeBayPCPartPicker
AMD Radeon RX 5600 XT
6 GB VRAM • 288 GB/s
AMD
$90
AmazonNeweggeBayPCPartPicker
AMD Radeon RX 5600M
6 GB VRAM • 288 GB/s
AMD
AmazonNeweggeBayPCPartPicker

Find the best GPU for Qwen 3.5 9B

Build Hardware for Qwen 3.5 9B

Model Card

View on HuggingFace

Qwen 3.5 9B — multimodal model with math, coding, vision, and 201 languages.

▸ SPEC SHEET

Qwen 3.5 9B — 9B Dense.

▸ SPECIFICATIONS
PARAMETERS
9B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
256K tokens
CAPABILITIES
chat, coding, reasoning, multilingual, vision, math
RELEASE DATE
2026-02-01
PROVIDER
Alibaba
FAMILY
qwen
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
Q4_K_M4.896.0 GB94%
Q5_K_S5.576.8 GB96%
Q5_K_M5.76.9 GB96%
Q6_K6.567.9 GB97%
Q8_08.510.1 GB100%
FP161618.5 GB100%
§ 01BENCHMARK SCORES
MMLU-PRO82.5
MATH48.8
IFEval91.5
BBH36.6
MMMU70.1
MUSR15.5
MMBench90.1
Arena Elo1470.0
GPQA Diamond80.6
HLE13.3
AA Intelligence32.4
AA Coding25.3
GPQA8.9
aa_ifbench66.7
aa_terminal_bench24.2
aa_tau286.8
aa_scicode27.5
aa_lcr59.0
§ 02RUN COMMAND

Run Qwen 3.5 9B locally with Ollama — needs 6.0 GB VRAM at Q4_K_M:

$ollama run qwen3.5:9b
§ 03COMPATIBLE GPUs
30 @ Q4_K_M
NVIDIA RTX 3050 6GB
6 GB · 168 GB/s
Intel Arc A380
6 GB · 186 GB/s
NVIDIA RTX 2060 6GB
6 GB · 336 GB/s
NVIDIA GTX 1660 SUPER
6 GB · 336 GB/s
NVIDIA GTX 1660 Ti
6 GB · 288 GB/s
NVIDIA GTX 1060 6GB
6 GB · 192 GB/s
NVIDIA Tesla C2070
6 GB · 143 GB/s
NVIDIA Tesla C2075
6 GB · 150 GB/s
NVIDIA Tesla C2090
6 GB · 177 GB/s
NVIDIA Tesla M2070
6 GB · 150 GB/s
NVIDIA Tesla M2070-Q
6 GB · 150 GB/s
NVIDIA Tesla M2075
6 GB · 150 GB/s
NVIDIA Tesla M2090
6 GB · 177 GB/s
NVIDIA Tesla X2070
6 GB · 177 GB/s
NVIDIA Tesla X2090
6 GB · 177 GB/s