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Qwen3.5-9B

Parameters

9B

Context Length

262K

Modality

Multimodal

Architecture

Dense

License

Apache 2.0

Release Date

24 Feb 2026

Knowledge Cutoff

-

API Pricing (per 1M)

Input: $0.17 · Output: $0.25

System Requirements

VRAM requirements for different quantization methods and context sizes

1,024 tokens

20.54 GB VRAM

Consumer

1x RTX 4090

24GB VRAM

Datacenter

1x NVIDIA A100

80GB VRAM

Apple Silicon

1x Apple M3 Max

128GB VRAM

262,144 tokens

56.48 GB VRAM

Consumer

3x RTX 4090

24GB VRAM

Datacenter

1x NVIDIA A100

80GB VRAM

Apple Silicon

1x Apple M3 Max

128GB VRAM

Architecture Diagram

Input TokensToken EmbeddingPosition: RoPEHidden: 4.1k · Context: 262K · Vocab: 248.3kx 32 layersRMSNormPre-AttentionGrouped-Query Attention16Q / 4KV headsHead dim: 256+RMSNormPre-FFNFeed-Forward NetworkSwiGLUIntermediate: 12.3k+Final RMSNormOutput Logits

Evaluation Benchmarks

Rank

#118

BenchmarkScoreRank

Professional Knowledge

MMLU Pro

0.825

21

Graduate-Level QA

GPQA

0.817

57

Agentic Index

Artificial Analysis

0.07

102

auto

0.29

Standard

0.23

123

128

Intelligence Index

Artificial Analysis
auto

0.14

Standard

0.13

186

189

Rankings

Overall Rank

#118

Coding Rank

#110

About Qwen3.5-9B

Qwen3.5-9B is Alibaba Cloud's efficient multimodal foundation model with 9B parameters, released February 2026. It uses a hybrid architecture combining Gated Delta Networks and Gated Attention in an 8×(3×DeltaNet→FFN→1×Attention→FFN) pattern. It achieves strong scores on MMLU-Pro (82.5%), GPQA Diamond (81.7%), HMMT benchmarks (90%/90%), and LiveCodeBench v6 (82.7%). Features unified vision-language capabilities, 262k native context (extensible to 1M), multi-token prediction training, and excels in multimodal reasoning, coding, agents, and multilingual tasks across 201 languages.

Technical Specifications

Attention

Attention Structure

Grouped-Query Attention

Attention Heads

16

Key-Value Heads

4

Attention Head Dimension

256

Position Embedding

ROPE

RoPE Theta

10,000,000

Sliding Window Attention

No

Sliding Window Size

-

Sliding Window Ratio

-

Linear Attention

Yes

Linear Attention Ratio

75.0%

Normalization

RMS Normalization

Activation Function

SwigLU

Dimensions

Hidden Dimension Size

4,096

Number of Layers

32

FFN Intermediate Size (Dense)

12,288

Multi-Token Prediction Heads

1

Tokenizer

Vocabulary Size

248,320

About Qwen 3.5

Qwen 3.5 is Alibaba Cloud's latest-generation foundation model family, released February 2026. It represents a significant leap forward, integrating breakthroughs in multimodal learning (unified vision-language foundation), efficient hybrid architecture (Gated Delta Networks with sparse Mixture-of-Experts), scalable reinforcement learning across million-agent environments, and global linguistic coverage spanning 201 languages. Available under Apache 2.0 license with open weights.


Other Qwen 3.5 Models