Open-Source Kimi K2.5 Test: Joining the Top Multimodal Tier, Visual Programming Bringing Creative Visions to Life

Article Intro: Moonshot AI and Alibaba Qwen have released Kimi K2.5 and Qwen3-Max-Thinking, kicking off the 2026 Chinese LLM showdown. Based on 302.AI real-world data, we analyze their technical differences from logic to complex coding. Kimi K2.5 stuns with its “Swarm Intelligence” and aesthetic programming, acting as an all-around creative partner; Qwen3-Max-Thinking relies on deep engineering roots to build a robust production foundation. Who wins? Read on to find out.

On January 27, Moonshot AI officially released and open-sourced Kimi K2.5. Positioned as the “strongest open-source model,” it represents a high level of technical confidence.

Core Upgrades:

1. Swarm Intelligence: K2.5 uses an “Agent Swarm” architecture, auto-scheduling up to 100 sub-agents for parallel tasks. This reduces task time by 80% and increases efficiency by 4.5x, ideal for large-scale research and literature reviews.
2. Visual Programming: Moving from “recognition” to “creation,” its Aesthetic Coding capability allows users to upload screen recordings of web interactions. K2.5 then deconstructs the dynamic logic and visual style to generate complete frontend code with equal aesthetic quality.

According to official data, K2.5 achieves SOTA performance among open-source models in coding, agents, and multimodality. Its 76.8% score on SWE-Bench Verified and top ranking on HLE-Full place it alongside closed-source giants like GPT-5.2 and Gemini 3 Pro.

Meanwhile, Alibaba’s Qwen3-Max-Thinking, the largest and most powerful reasoning model in the Qwen series, boasts trillion-plus parameters and 36T tokens of training data, rivaling top international models in math reasoning and code editing.

I. Tested Model Information

(1) Pricing on 302.AI

(2) Evaluation Goals:

To test models on logic, math, programming, and human intuition to provide selection references for users.

(3) Evaluation Methodology:

Using the 302.AI test bank: 10 Logic/Math questions, 7 Human Intuition questions, and 12 Programming simulations. Scores are out of 10.

(4) Evaluation Tools:

• 302.AI Studio Client.
• Vibe Mode for programming (Claude Code sandbox + Skills like brand-guidelines and frontend-design).

II. Evaluation Overview

302.AI Test Results:

Kimi K2.5 slightly leads in overall average scores across logic, intuition, and programming.

Case 1: Logical Reasoning

Kimi K2.5 is more academic and rigorous, offering formal mathematical proofs and boundary discussions. Qwen3-Max-Thinking is pragmatic, focusing on simplified formula application.

Prompt: Solve the correct three-digit password.

• Kimi K2.5: Correct.

• Qwen3-Max-Thinking: Incorrect.

Case 2: Multimodal Reasoning

Qwen3-Max-Thinking does not participate as it lacks multimodal capabilities.

Prompt: Arrange the shuffled comic panels in logical order (Correct: E→F→A→C→B→D).

• Kimi K2.5: Provided a non-standard but self-consistent alternative interpretation.

Case 3: Frontend Programming — Brand Webpage

Kimi K2.5 shows a hybrid “Designer + Full-Stack Engineer” mindset, focusing on user experience, beautiful interfaces, and rich interactions. Qwen3-Max-Thinking shows traditional “Software Engineering” thinking, prioritizing code structure, modularity, and maintainability.

Prompt: Create a brand showcase page for Anthropic.

• Kimi K2.5: Created a stunning single-page site with animations, counters, and high brand fidelity.

• Qwen3-Max-Thinking: Cleaner, maintainable code but lacked company info and advanced interactions.

Case 4: Frontend Programming — Express Mini-App

Kimi K2.5: Better mobile experience with bottom navigation, shipping fee estimations, and rich interactions. Lacked component modularity.

Qwen3-Max-Thinking: Better code structure and modularity, but failed to include bottom navigation or deep functional details like shipping breakdowns.

Case 5: Frontend Programming — Webpage Replication

Kimi K2.5 was tested on replicating the Figma homepage via a screen recording. It produced a visually high-fidelity version with perfect “text fade-in” effects, showcasing its core Aesthetic Coding trait.

IV. Kimi K2.5 & Qwen3-Max-Thinking Conclusion

Summary:

• Qwen3-Max-Thinking is a “Rigorous Engineering Expert”: Focuses on stability and clean architecture. Best for production systems that require long-term maintenance.
• Kimi K2.5 is a “Full-Stack Creative Partner”: Focuses on aesthetics and user experience. Best for rapid prototyping, high-design marketing pages, and short-path visualization of ideas.

Kimi K2.5 reflects a shift in AI: from a tool you must master, to a “Work Buddy” that understands intent and collaborates autonomously.

V. How to Use on 302.AI

1. In Chatbots

App Store → Robots → Chatbot → Select kimi-k2.5.

2. Via API

API Store → LLM → Moonshot → kimi-k2.5.

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