The author compares MiniMax-M2.7 and Qwen3.5-122B-A10B GGUF models for local full offload on a 96GB VRAM rig. For their purposes, Qwen3.5-122B is preferred, despite MiniMax being more quantized, highlighting the trade-offs in performance for local LLM inference.
Minimax is expected to release the open weights of its M2.7 model soon, generating high anticipation. It is highly anticipated as an excellent local model due to its potential viability with quantized versions.
The content announces the launch of the MiniMax M2.7 AI model, available in 63GB and 89GB versions, optimized for Mac. It highlights its promising performance, suggesting it approaches levels of models like Sonnet 4.5 and mentions the MMLU benchmark.
Minimax m2.7 still doesn't allow direct product coding, but Ryan Lee confirmed that the sale of products built with it is permitted. The team is actively working on the license for future functionalities.
Chinese startup MiniMax claimed a 26% improvement on the BU Bench, a benchmark for embodied AI task planning. However, the company released no details, data, or methodology, leaving the claim unverifiable.
The release of Minimax M2.7 has been confirmed.
This content announces the release of Minimax version M2.7. The news was submitted by user /u/decrement-- and includes links for further details.