The Data Center (ZDV) has activated two new AI models and two image generation models in the university's AI chat. You have until the end of September to explore the new capabilities of these models.
Shortly before the start of the semester, the models will likely be updated again or replaced with more powerful versions. We will inform you in due course about the specific model versions we will be using for the winter semester.
The models: MiniMax M3 and Qwen3.6 35B
MiniMax M3 is flexible and can be used like a traditional AI assistant. It is suitable for complex and agent-based tasks in which the model must independently plan and execute multiple steps. MiniMax M3 is also suitable for coding: It can solve programming tasks in common languages, explain code, find errors, and assist with debugging.
Qwen3.6 35B, a mixture-of-experts model with reasoning mode enabled, is suitable for tasks that require multi-step logical reasoning. Thanks to their multimodal capabilities, both models can process images, diagrams, tables, and screenshots.
Create and edit images
Z-Image-Turbo is a simplified and optimized version of the Z-Image image creation model. With just a few computational steps per image, the model achieves results comparable to or better than those of leading competing models. The reduced number of computational steps lowers computational effort and energy costs without compromising image quality. The Lightning variant of the Qwen-Image-Edit-2511 model allows users to modify existing images.
The new MiniMax M3 and Qwen3.6 35B models automatically access the Z-Image-Turbo and Qwen-Image-Edit-2511 image models as needed.
Strong benchmark results for the models
Established benchmark tests help put the performance of the new models into perspective. MiniMax M3 achieved a score of 59.0 percent on the SWE-Bench Pro benchmark, a test designed to evaluate practical programming skills. This places it ahead of GPT-5.5 and Gemini 3.1 Pro and just slightly behind Opus 4.7. In Terminal-Bench 2.1, another standard test for AI systems, MiniMax M3 achieved 66.0 percent, exactly the same level as Opus 4.7.
The developer of Qwen3.6 35B has also published benchmarks in which agent-based programming emerges as a strength of the model. On SWE-Bench Pro, a test in which the model must independently solve real-world software problems in actual code repositories, Qwen3.6 scored 49.5 points, placing it well ahead of Google’s Gemma 4 31B, which scored 35.7 points in the same test series.
In the MMMU-Pro benchmark, which tests multimodal understanding and reasoning based on technical texts, images, diagrams, and tables from various disciplines, Qwen3.6 scored 75.3 points, placing it just behind Gemma 4 31B (76.9) but well ahead of Claude Sonnet 4.5, which scored 68.4 points in the same evaluation.
Current models will be discontinued at the end of September
The MiniMax M3 and Qwen3.6 35B models are intermediate versions. Shortly before the start of the semester, the models will likely be updated again or replaced with more powerful versions. We will inform you in due course about the specific model versions we will be using for the winter semester.
The models GPT OSS 120B, Qwen3 235B (VL/Thinking) and Qwen3 Coder 30B will be discontinued at the end of September. In the application, these are currently marked as “retires in October”.
Until the end of September, we recommend not starting any new extensive or longer research experiments using the existing models and complete any experiments already started with the respective model.
Model updates every semester
In the future, we plan to update the models once per semester. These updates will take place during the break between semesters and will be announced in advance. The model switch will not result in any fundamental changes for users. The models will become more powerful, more reliable, and of higher quality. In addition, the ZDV will update the AI chat user interface (OpenWebUI) during breaks between semesters and add new features. Predefined prompts that have already been created can normally continue to be used.
For more information about the models and other important notes, please visit our website:
https://www.en-zdv.uni-mainz.de/ai-at-jgu/
More news from the Data Center → may be found here.