Qwen3.5-35B-A3B
Active Parameters
35B
Context Length
262K
Modality
Multimodal
Architecture
Mixture of Experts (MoE)
License
Apache 2.0
Release Date
24 Feb 2026
Knowledge Cutoff
-
System Requirements
VRAM requirements for different quantization methods and context sizes
1,024 tokens
Consumer
4x RTX 4090
24GB VRAM
Datacenter
1x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
262,144 tokens
Consumer
5x RTX 4090
24GB VRAM
Datacenter
2x NVIDIA A100
80GB VRAM
Apple Silicon
1x Apple M3 Max
128GB VRAM
Architecture Diagram
Evaluation Benchmarks
Rank
#134
| Benchmark | Score | Rank |
|---|---|---|
Web Development | 1250 | 86 |
General Text | 1395 | 99 |
Rankings
Overall Rank
#134
Coding Rank
#86
About Qwen3.5-35B-A3B
Qwen3.5-35B-A3B is Alibaba Cloud's efficient multimodal foundation model, released February 2026. With 35B total parameters and 3B activated through a Mixture-of-Experts architecture (256 experts), it delivers strong performance with minimal compute. It achieves MMLU-Pro (85.3%), GPQA Diamond (84.2%), SWE-bench Verified (69.2%), and Terminal-Bench 2.0 (40.5%). Qwen3.5-Flash is the hosted API version. Features unified vision-language capabilities, 262k native context (extensible to 1M), and strong performance on multimodal reasoning, coding, and multilingual tasks.
Technical Specifications
Attention
Attention Structure
Grouped-Query Attention
Attention Heads
16
Key-Value Heads
2
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
2,048
Number of Layers
40
FFN Intermediate Size (Dense)
512
Multi-Token Prediction Heads
1
Tokenizer
Vocabulary Size
248,320
Mixture of Experts
Total Expert Parameters
3.0B
Number of Experts
256
Active Experts
9
Shared Experts
-
FFN Intermediate Size (per Expert)
512
Dense Layers Before MoE
-
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.