Active Parameters
397B
Context Length
262K
Modality
Multimodal
Auxiliary Parameters
450M
Architecture
Mixture of Experts
KV Cache Rate
120 KB/tok
License
Apache 2.0
Release Date
24 Feb 2026
Knowledge Cutoff
-
API Pricing (per 1M)
Input: $0.50 · Output: $3.60
Precision
Context
Workload Memory: 774.57 GB
FP16 · 8K context
Base Weights: 771.14 GB
KV Cache: 0.94 GB
Runtime & Graphs: 2.50 GB
8x NVIDIA H200 141GB
774.6 / 1015.2 GB usable · TP 8
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Rank
#52
| Benchmark | Score | Rank |
|---|---|---|
Professional Knowledge | 0.878 | 4 |
StackUnseen | 0.763 | 16 |
Graduate-Level QA | 0.884 | 29 |
General Text | 1442 | 73 |
Web Development | 1400 | 81 |
Coding Index | 0.48 | 91 |
Agentic Index | auto 0.08 | 94 |
Intelligence Index | auto 0.18 Standard 0.21 | 175 142 |
Overall Rank
#52
Coding Rank
#85
Qwen3.5-397B-A17B is Alibaba Cloud's largest and most capable multimodal foundation model, released February 2026. With 397B total parameters and 17B activated through a Mixture-of-Experts architecture (512 experts), it achieves state-of-the-art scores on MMLU-Pro (87.8%), GPQA Diamond (88.4%), SWE-bench Verified (80.0%), and Terminal-Bench 2.0 (54.0%). It features unified vision-language capabilities, extended context up to 1M tokens, and excels in coding agents, general agents, multimodal reasoning, and multilingual understanding across 201 languages.
Attention
Attention Structure
Grouped-Query Attention
Attention Heads
32
Key-Value Heads
2
Attention Head Dimension
256
Position Embedding
ROPE
RoPE Theta
10,000,000
Linear Attention
Yes
Linear Attention Ratio
75.0%
Normalization
RMS Normalization
Activation Function
SwigLU
Dimensions
Auxiliary Parameters
450M
Hidden Dimension Size
4,096
Number of Layers
60
FFN Intermediate Size (Dense)
1,024
Multi-Token Prediction Heads
1
Tokenizer
Vocabulary Size
248,320
Mixture of Experts
Total Expert Parameters
17.0B
Number of Experts
512
Active Experts
11
FFN Intermediate Size (per Expert)
1,024
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.