MiniMax Releases MiniMax M3 with MSA Architecture Supporting 1M-Token Context, Native Multimodality, and Agentic Coding
Quick Take
MiniMax has launched the MiniMax M3, featuring a 1M-token context window and MiniMax Sparse Attention architecture. This model supports native multimodality, including image and video processing, enhancing capabilities for developers and AI applications.
Key Points
- MiniMax M3 features a 1M-token context window for improved processing.
- The model incorporates MiniMax Sparse Attention architecture for efficiency.
- Supports native multimodality, including images and videos.
- Enhances coding capabilities for AI applications and developers.
- Targets developers looking for advanced AI model features.
Article Excerpt
From source RSS / original summaryMiniMax M3 introduces MiniMax Sparse Attention, a 1M-token context window, and native image, video, and computer use support. The post MiniMax Releases MiniMax M3 with MSA Architecture Supporting 1M-Token Context, Native Multimodality, and Agentic Coding appeared first on MarkTechPost.
Reader Mode unavailable (the site blocks scraping).
Want this in your inbox every morning?
Daily brief at your local 8am — bilingual EN/中文, free.
More from MarkTechPost
See more →Trajectory Releases a Concurrent Multi-LoRA Training Stack for Continual Learning, Reporting a 2.81× Experiment-Throughput Gain
Trajectory, in collaboration with UC Berkeley Sky Lab and Anyscale, has developed a concurrent multi-LoRA training stack that enhances continual learning, achieving a 2.81× throughput gain compared to single-tenant setups without reward regression. The open-source code is available in NovaSky-AI/SkyRL.

