Alibaba/Dense

AlibabaQwen3.5-2B

chatThinkingTool Use
2.3B
Parameters
256K
Context length
15
Benchmarks
6
Quantizations
973K
HF downloads
Architecture
Dense
Released
2025-06-01
Layers
36
KV Heads
4
Head Dim
128
Family
qwen

Quantization Options

QuantBitsVRAMQuality
Q4_K_M4.891.9 GBgood
Q5_K_S5.572.1 GBgood
Q5_K_M5.72.1 GBgood
Q6_K6.562.4 GBexcellent
Q8_08.52.9 GBlossless
FP16165.1 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 QWEN3.5-2B NOW

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

Community Ratings

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Benchmarks (15)

τ²-Bench69.0
MATH50.0
GPQA Diamond45.6
IFBench31.5
AA Long Context23.7
GPQA20.0
AA Intelligence16.3
IFEval12.9
MUSR5.5
Terminal-Bench3.8
AA Coding3.5
SciCode2.8
HLE2.1
MMLU-PRO1.9
BBH1.1

Run this model

Easiest way to get started·Beginners
DOCS ↗
curl -fsSL https://ollama.com/install.sh | sh
$ollama run qwen3:2.3b-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.

Find the best GPU for Qwen3.5-2B

Build Hardware for Qwen3.5-2B

Read the full model card for detailed information about this model.

▸ SPEC SHEET

Qwen3.5-2B2.3B Dense.

▸ SPECIFICATIONS
PARAMETERS
2.3B
ARCHITECTURE
Dense Transformer
CONTEXT LENGTH
256K tokens
CAPABILITIES
chat
RELEASE DATE
2025-06-01
PROVIDER
Alibaba
FAMILY
qwen
▸ VRAM REQUIREMENTS
QUANTBPWVRAMQUALITY
Q4_K_M4.891.9 GB94%
Q5_K_S5.572.1 GB96%
Q5_K_M5.72.1 GB96%
Q6_K6.562.4 GB97%
Q8_08.52.9 GB100%
FP16165.1 GB100%
§ 01BENCHMARK SCORES
MMLU-PRO1.9
MATH50.0
IFEval12.9
BBH1.1
GPQA20.0
MUSR5.5
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 Qwen3.5-2B locally with Ollama — needs 1.9 GB VRAM at Q4_K_M:

$ollama run qwen3:2.3b