MiniMax M2.7 vs Qwen Image 2512

MiniMax-M2.7 is a next-generation large language model built for autonomous, real-world productivity and continuous improvement. Designed to take an active role in its own development, M2.7 incorporates advanced agent capabilities through multi-agent collaboration, allowing it to plan, execute, and improve complex tasks across dynamic environments. Trained for production-level performance, M2.7 supports workflows such as live debugging, root cause analysis, financial modeling, and full document creation across Word, Excel, and PowerPoint. It delivers strong benchmark results, including 56.2% on SWE-Pro and 57.0% on Terminal Bench 2, while reaching 1495 ELO on GDPval-AA, setting a new benchmark for multi-agent systems in real-world digital workflows.

Qwen-Image-2512 is the latest open-source text-to-image foundational model from Qwen, delivering substantial upgrades over its predecessor, the August Qwen-Image release. This new version significantly enhances human realism—reducing the “AI-generated” look with richer facial detail, more accurate age cues, and better adherence to pose and context instructions. It also renders finer natural detail across landscapes and wildlife, improving textures such as water flow, foliage, mist, and animal fur with more precise strand- and material-level fidelity. In addition, Qwen-Image-2512 improves text rendering and multimodal composition, producing clearer, more accurate typography, stronger layout control, and more reliable generation of complex slide-like designs and infographics. Altogether, these improvements make Qwen-Image-2512 a more photorealistic, detail-faithful, and text-capable image generator suitable for both creative and practical visual production.