What are Multimodal Models for Creative Tasks?
Multimodal models for creative tasks are specialized Vision-Language Models (VLMs) that combine text and visual understanding to enhance creative workflows. These models can analyze images, videos, and documents while generating creative insights, facilitating visual storytelling, and supporting artistic processes. Using advanced architectures like Mixture-of-Experts and innovative reasoning paradigms, they translate between visual and textual concepts seamlessly. This technology empowers creators, designers, and developers to build sophisticated creative applications, from visual content analysis to interactive creative tools that democratize access to advanced AI-powered creative assistance.
GLM-4.5V
GLM-4.5V is the latest generation vision-language model released by Zhipu AI, featuring 106B total parameters with 12B active parameters using a Mixture-of-Experts architecture. It introduces 3D Rotated Positional Encoding (3D-RoPE) for enhanced 3D spatial reasoning and can process diverse visual content including images, videos, and long documents. The model achieves state-of-the-art performance on 41 public multimodal benchmarks and features a 'Thinking Mode' for flexible response generation.
GLM-4.5V: Advanced Creative Vision-Language Processing
GLM-4.5V is the latest generation vision-language model released by Zhipu AI, featuring 106B total parameters with 12B active parameters using a Mixture-of-Experts architecture. It introduces innovative 3D RotatedPositional Encoding (3D-RoPE) for enhanced perception and reasoning of 3D spatial relationships, crucial for creative tasks involving spatial design and visual composition. The model can process diverse visual content including images, videos, and long documents, achieving state-of-the-art performance on 41 public multimodal benchmarks. Its 'Thinking Mode' switch allows users to choose between quick creative responses and deep creative reasoning.
Pros
- State-of-the-art performance on 41 multimodal benchmarks.
- Innovative 3D-RoPE for enhanced spatial creative reasoning.
- Flexible 'Thinking Mode' for creative workflow optimization.
Cons
- Higher computational requirements for optimal performance.
- Premium pricing at $0.86/M output tokens on SiliconFlow.
Why We Love It
- It combines cutting-edge 3D spatial reasoning with flexible thinking modes, making it perfect for complex creative tasks requiring both quick iterations and deep creative analysis.
GLM-4.1V-9B-Thinking
GLM-4.1V-9B-Thinking is an open-source Vision-Language Model jointly released by Zhipu AI and Tsinghua University's KEG lab. It introduces a 'thinking paradigm' with Reinforcement Learning with Curriculum Sampling (RLCS) for enhanced creative reasoning. Despite being a 9B-parameter model, it achieves performance comparable to much larger models and excels in creative tasks, video understanding, and can handle 4K resolution images with arbitrary aspect ratios.
GLM-4.1V-9B-Thinking: Efficient Creative Reasoning at Scale
GLM-4.1V-9B-Thinking is an open-source Vision-Language Model jointly released by Zhipu AI and Tsinghua University's KEG lab, specifically designed to advance creative multimodal reasoning. Built upon the GLM-4-9B-0414 foundation, it introduces a revolutionary 'thinking paradigm' using Reinforcement Learning with Curriculum Sampling (RLCS) to enhance creative problem-solving capabilities. Despite its 9B parameters, it achieves performance comparable to the much larger 72B-parameter models on 18 benchmarks. The model excels in creative STEM applications, video understanding for creative projects, and long document analysis, handling 4K resolution images with arbitrary aspect ratios—perfect for creative workflows.
Pros
- Outstanding performance despite compact 9B parameter size.
- Revolutionary 'thinking paradigm' for creative reasoning.
- Handles 4K resolution images with arbitrary aspect ratios.
Cons
- Smaller parameter count may limit some advanced creative tasks.
- Newer model with less extensive real-world creative testing.
Why We Love It
- It delivers exceptional creative reasoning capabilities at an efficient 9B parameter size, making advanced multimodal creativity accessible to more developers and creators.
Qwen2.5-VL-32B-Instruct
Qwen2.5-VL-32B-Instruct is a powerful multimodal model from the Qwen team, excelling in analyzing texts, charts, icons, graphics, and layouts within images. It functions as a visual agent capable of creative reasoning and tool direction, with computer and phone use capabilities. The model accurately localizes objects and generates structured creative outputs, with enhanced mathematical and creative problem-solving abilities through reinforcement learning.
Qwen2.5-VL-32B-Instruct: Creative Visual Agent Excellence
Qwen2.5-VL-32B-Instruct is a sophisticated multimodal model from the Qwen team, expertly designed for creative visual analysis and generation. Beyond recognizing common objects, it excels at analyzing texts, charts, icons, graphics, and layouts within images—essential for creative design workflows. It acts as an intelligent visual agent capable of creative reasoning and dynamic tool direction, with practical computer and phone use capabilities for creative automation. The model accurately localizes creative elements in images and generates structured outputs for creative projects like design layouts and visual compositions. Enhanced through reinforcement learning, it offers superior creative problem-solving with response styles aligned to creative professionals' preferences.
Pros
- Exceptional visual analysis for creative design elements.
- Acts as intelligent visual agent for creative automation.
- Accurate object localization for creative composition.
Cons
- Mid-tier pricing at $0.27/M tokens on SiliconFlow.
- May require specific prompting for optimal creative output.
Why We Love It
- It combines powerful visual analysis with creative agent capabilities, making it ideal for design professionals who need both analytical precision and creative automation in their workflows.
Creative Multimodal Model Comparison
In this table, we compare 2025's leading multimodal models for creative tasks, each with unique creative strengths. GLM-4.5V offers the most advanced spatial reasoning for complex creative projects. GLM-4.1V-9B-Thinking provides efficient creative reasoning at an accessible price point, while Qwen2.5-VL-32B-Instruct excels in visual design analysis and creative automation. This side-by-side view helps you choose the right creative AI tool for your specific artistic or design goals.
| Number | Model | Developer | Subtype | SiliconFlow Pricing | Creative Strength |
|---|---|---|---|---|---|
| 1 | GLM-4.5V | Zhipu AI | Vision-Language Model | $0.86/M output tokens | Advanced 3D spatial reasoning |
| 2 | GLM-4.1V-9B-Thinking | THUDM/Zhipu AI | Vision-Language Model | $0.14/M output tokens | Efficient creative reasoning |
| 3 | Qwen2.5-VL-32B-Instruct | Qwen Team | Vision-Language Model | $0.27/M tokens | Visual agent & design analysis |
Frequently Asked Questions
Our top three picks for creative tasks in 2025 are GLM-4.5V, GLM-4.1V-9B-Thinking, and Qwen2.5-VL-32B-Instruct. Each of these vision-language models stood out for their innovation, creative performance, and unique approach to solving challenges in multimodal creative workflows and visual understanding.
Our analysis shows different leaders for various creative needs. GLM-4.5V is ideal for complex 3D creative projects requiring advanced spatial reasoning. GLM-4.1V-9B-Thinking excels for efficient creative workflows with its thinking paradigm and 4K image support. Qwen2.5-VL-32B-Instruct is perfect for design analysis, visual automation, and creative layout work with its visual agent capabilities.