Qwen 3.5 The GREATEST Opensource AI Model That Beats Opus 4.5 and Gemini 3? (Fully Tested)

2026-02-17 · Source: WorldofAI · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Intermediate, long

Summary

Alibaba has released the Qwen 3.5 series, a new flagship open-source, openweight multimodal AI model featuring 397 billion parameters with 17 billion active parameters. This model incorporates a hybrid linear attention architecture combined with sparse mixture of experts and is scaled with large reinforcement learning environments, designed for real-world agents. It reportedly operates 19 times faster than Qwen 3 Max and supports 201 languages. Qwen 3.5 achieves strong performance, scoring 87.88 on MMLU Pro and 87.5 on video MME, and surpasses Claude Opus 4.5 on browser comp and Gemini 3 Pro in several multimodal tasks. While it keeps pace with Opus in coding and beats Gemini 3 Pro on sway bench, it trails on terminal bench. The model is available under the Apache 2.0 license, offering free weights, a chatbot, and API access through cloud services or third-party platforms like Kilo Code and Open Router.

Key takeaway

For CTOs or VPs of Engineering evaluating open-source multimodal AI solutions, Qwen 3.5 presents a compelling option due to its strong benchmark performance, Apache 2.0 license, and reported speed. While it shows weaknesses in complex spatial tasks and real-world stability compared to top closed rivals, its capabilities in vision-plus-reasoning and code generation make it a viable alternative for specific use cases, especially where cost-efficiency and open access are priorities.

Key insights

Qwen 3.5 is a powerful open-source, multimodal AI model excelling in speed and diverse applications.

Principles

• Hybrid architectures enhance multimodal performance.
• Open-source models can rival proprietary benchmarks.

Method

Qwen 3.5 combines hybrid linear attention with sparse mixture of experts and large reinforcement learning for an all-purpose, multimodal system designed for real-world agents.

In practice

• Utilize Qwen 3.5 for vision-plus-reasoning tasks.
• Employ for complex code generation, despite inconsistencies.
• Access via Apache 2.0 weights or various APIs.

Topics

• Qwen 3.5
• Multimodal AI
• Open-source Models
• Code Generation
• Sparse Mixture of Experts

Best for: CTO, VP of Engineering/Data, Director of AI/ML, AI Engineer, Machine Learning Engineer, Software Engineer

Related on AIssential

• Alibaba's Qwen 3.5 397B-A17 beats its larger trillion-parameter model — at a fraction of the cost — Sparse Mixture-of-Experts models can surpass larger predecessors in performance and efficiency.
• Qwen 3.6 Plus: GREATEST Opensource AI Model EVER! Beats Opus 4.5 and Gemini 3 (Fully Tested) — Qwen 3.6 Plus is a multimodal agentic coding model with a 1 million context window, excelling in complex project generation.
• Qwen3.5-397B-A17B: the smallest Open-Opus class, very efficient model — Qwen3.5 offers multimodal, long-context capabilities with efficient sparse MoE architecture, enabling local deployment despite its large scale.
• Qwen 3.7 Max & Plus First Test | Coding, Game Dev, OCR, Image Understanding Testing — Qwen 3.7 Max and Plus models show improved performance and reduced 'overthinking' compared to previous iterations.
• Qwen 3.5 Local Test with Ollama | Coding, OCR, Data Extraction, Image Understanding — Qwen 3.5 MoE model offers strong multimodal capabilities and efficient local inference.
• Alibaba's open Qwen 3.5 takes aim at GPT-5 mini and Claude Sonnet 4.5 at a fraction of the cost — Alibaba's Qwen 3.5 models achieve competitive performance against top Western LLMs at lower computational cost.

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Editorial summary, takeaway, and curation by AIssential. Original article published by WorldofAI.