Alibaba/Dense

AlibabaQwen 3.5 2B

Qwen 3.5 2B — compact multimodal model. Strong for its size with vision, 262K context, 201 languages.

chatcodingreasoningmultilingualvision
2B
Parameters
256K
Context length
17
Benchmarks
6
Quantizations
1.5M
HF downloads
Architecture
Dense
Released
2026-03-01
Layers
24
KV Heads
2
Head Dim
256
Family
qwen

Quantization Options

QuantBitsVRAMQuality
Q4_K_M4.891.7 GBgood
Q5_K_S5.571.9 GBgood
Q5_K_M5.71.9 GBgood
Q6_K6.562.1 GBexcellent
Q8_08.52.6 GBlossless
FP16164.5 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 2B NOW

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

Community Ratings

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Benchmarks (17)

MMBench83.3
τ²-Bench69.0
MMMU64.2
IFEval61.2
MMLU-PRO55.3
GPQA Diamond45.6
IFBench31.5
AA Long Context23.7
MATH20.8
BBH18.3
AA Intelligence16.3
MUSR4.0
Terminal-Bench3.8
AA Coding3.5
SciCode2.8
HLE2.1
GPQA0.0

Run this model

Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run qwen3.5:2b-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.

Find the best GPU for Qwen 3.5 2B

Build Hardware for Qwen 3.5 2B
▸ SPEC SHEET

Qwen 3.5 2B2B Dense.

▸ SPECIFICATIONS
PARAMETERS
2B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
256K tokens
CAPABILITIES
chat, coding, reasoning, multilingual, vision
RELEASE DATE
2026-03-01
PROVIDER
Alibaba
FAMILY
qwen
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
Q4_K_M4.891.7 GB94%
Q5_K_S5.571.9 GB96%
Q5_K_M5.71.9 GB96%
Q6_K6.562.1 GB97%
Q8_08.52.6 GB100%
FP16164.5 GB100%
§ 01BENCHMARK SCORES
MMLU-PRO55.3
MATH20.8
IFEval61.2
BBH18.3
MMMU64.2
GPQA0.0
MUSR4.0
MMBench83.3
GPQA Diamond45.6
HLE2.1
AA Intelligence16.3
AA Coding3.5
aa_ifbench31.5
aa_terminal_bench3.8
aa_tau269.0
aa_scicode2.8
aa_lcr23.7
§ 02RUN COMMAND

Run Qwen 3.5 2B locally with Ollama — needs 1.7 GB VRAM at Q4_K_M:

$ollama run qwen3.5:2b