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What is Qwen3.5?

Qwen3.5 is an advanced open-weight multimodal AI system built to serve as the foundation for native digital agents capable of reasoning across text, images, and video. The primary release, Qwen3.5-397B-A17B, introduces a hybrid architecture that combines Gated DeltaNet linear attention with a sparse mixture-of-experts design, activating just 17 billion parameters per inference pass while maintaining a total parameter count of 397 billion. This selective activation dramatically improves decoding throughput and cost efficiency without sacrificing benchmark-level performance. Qwen3.5 demonstrates strong results across knowledge, multilingual reasoning, coding, STEM tasks, search agents, visual question answering, document understanding, and spatial intelligence benchmarks. The hosted Qwen3.5-Plus variant offers a default one-million-token context window and integrated tool usage such as web search and code interpretation for adaptive problem-solving. Expanded multilingual support now covers 201 languages and dialects, backed by a 250k vocabulary that enhances encoding and decoding efficiency across global use cases. The model is natively multimodal, using early fusion techniques and large-scale visual-text pretraining to outperform prior Qwen-VL systems in scientific reasoning and video analysis. Infrastructure innovations such as heterogeneous parallel training, FP8 precision pipelines, and disaggregated reinforcement learning frameworks enable near-text baseline throughput even with mixed multimodal inputs. Extensive reinforcement learning across diverse and generalized environments improves long-horizon planning, multi-turn interactions, and tool-augmented workflows. Designed for developers, researchers, and enterprises, Qwen3.5 supports scalable deployment through Alibaba Cloud Model Studio while paving the way toward persistent, economically aware, autonomous AI agents.

What is K2 Horizon?

K2 Horizon consists of a collection of six open models, namely the 375B-A23B, 36B-A4B, 32B, 7B, 3.7B, and 0.9B, each meticulously designed to excel in specific areas such as reasoning, mathematics, coding, agentic tasks, and overall functional capabilities. These models are built upon a cohesive architecture that incorporates a shared vocabulary, training methodologies, interfaces, evaluation frameworks, and deployment tools, which enable smooth transitions between different model sizes and effective management of varying workloads. Leading the lineup, the 375B-A23B model excels in complex reasoning, software development, research endeavors, and long-term agentic operations, whereas the 32B and 36B-A4B models emphasize strong local deployment capabilities. The 36B-A4B model is distinguished by its cutting-edge Mixture-of-Value Attention mechanism, which fuses sparse attention with Mixture-of-Experts layers, enabling it to utilize around 4 billion parameters per token, thereby closely rivaling the performance of the denser 32B model. This innovative architecture not only enhances versatility but also optimizes resource utilization across a diverse array of applications, making K2 Horizon a formidable presence in the field of model technology. Additionally, the collective strengths of these models allow for a comprehensive approach to tackling various challenges within their respective domains.

Media

Media

Integrations Supported

APIFree
Alibaba Cloud Model Studio
BaseRT
Claw Code
Microsoft-Decision-1
Ollama
OpenClaw
Qwen
Qwen3.5-Plus
Tev1
Together AI
ZooClaw

Integrations Supported

API Availability

Has API

API Availability

Pricing Information

Free
Open source
Free Version

Pricing Information

Pricing not provided

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS

Customer Service / Support

Not specified

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Alibaba

Date Founded

1999

Company Location

China

Company Website

qwen.ai

Company Facts

Organization Name

Institute of Foundation Models

Date Founded

2025

Company Location

United States

Company Website

ifm.ai/blog/k2/

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

AI Reasoning Models

Not specified

AI Vision Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Multimodal Models

Not specified

Open-Weight AI Models

Not specified

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Large Language Models

Not specified

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