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Qwen3.5-27B

Parameters

27B

Context Length

262K

Modality

Multimodal

Auxiliary Parameters

450M

Architecture

Dense

License

Apache 2.0

Release Date

24 Feb 2026

Knowledge Cutoff

-

API Pricing (per 1M)

Input: $0.30 · Output: $2.40

System Requirements

VRAM requirements for different quantization methods and context sizes

1,024 tokens

58.48 GB VRAM

Consumer

3x RTX 4090

24GB VRAM

Datacenter

1x NVIDIA A100

80GB VRAM

Apple Silicon

1x Apple M3 Max

128GB VRAM

262,144 tokens

130.36 GB VRAM

Consumer

7x RTX 4090

24GB VRAM

Datacenter

2x NVIDIA A100

80GB VRAM

Apple Silicon

2x Apple M3 Max

128GB VRAM

Architecture Diagram

Input TokensToken EmbeddingPosition: RoPEHidden: 5.1k · Context: 262K · Vocab: 248.3kx 64 layersRMSNormPre-AttentionGrouped-Query Attention24Q / 4KV headsHead dim: 256+RMSNormPre-FFNFeed-Forward NetworkSwiGLUIntermediate: 17.4k+Final RMSNormOutput Logits

Evaluation Benchmarks

Rank

#73

BenchmarkScoreRank

Professional Knowledge

MMLU Pro

0.861

8

Graduate-Level QA

GPQA

0.855

44

auto

0.54

Standard

0.47

80

96

Web Development

WebDev Arena

1357

83

General Text

Text Arena

1408

95

Intelligence Index

Artificial Analysis
auto

0.23

Standard

0.19

122

149

Rankings

Overall Rank

#73

Coding Rank

#62

About Qwen3.5-27B

Qwen3.5-27B is Alibaba Cloud's dense multimodal foundation model with 27B parameters, released February 2026. Unlike the MoE variants, it uses a dense architecture combining Gated Delta Networks and Feed Forward Networks. It achieves MMLU-Pro (86.1%), GPQA Diamond (85.5%), SWE-bench Verified (72.4%), and Terminal-Bench 2.0 (41.6%). Features unified vision-language capabilities, 262k native context (extensible to 1M), and excels across reasoning, coding, multimodal understanding, and multilingual tasks spanning 201 languages.

Technical Specifications

Attention

Attention Structure

Grouped-Query Attention

Attention Heads

24

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

Auxiliary Parameters

450M

Hidden Dimension Size

5,120

Number of Layers

64

FFN Intermediate Size (Dense)

17,408

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