Tracked topic
MiniMax M3 is a new open-weight model for coding, agentic, and multimodal workloads. MiniMax describes M3 as combining three frontier capabilities in one model: strong coding and agentic task performance, long-context MiniMax Sparse Attention (MSA), and native multimodality for text, image, and video understanding. The 1M-token context window of MiniMax M3 enables sophisticated, long-horizon application workflows, including autonomous software engineering agents, repository-wide reasoning, and native multimodal document analysis alongside tool-driven automation. The AMD day-zero enablement foc
Day 0 Support for MiniMax M3 on AMD Instinct GPUs… Additional Resources Learn more about MiniMax M3: https://www.minimax.io/models/text/m3 Read the MiniMax M3 launch blog: https://www.minimax.io/blog/minimax-m3 Minimax Model on HuggingFace: https://huggingface.co/MiniMaxAI/MiniMax-M3 vLLM recipes: https://recipes.vllm.ai/MiniMaxAI/MiniMax-M3 SGLang… …
… Our inference kernel is available at: https://github.com/MiniMax-AI/MSA. A production-grade natively multimodal model powered by MSA has been publicly released at: https://huggingface.co/MiniMaxAI/MiniMax-M3. …
… H3 uses 8-way sequence parallelism across all visible GPUs; ROCm PyTorch honors HIP VISIBLE DEVICES and maps CUDA VISIBLE DEVICES , so export both: export CUDA VISIBLE DEVICES=0,1,2,3,4,5,6,7 export HIP VISIBLE DEVICES=0,1,2,3,4,5,6,7 export MINIMAX H3 FL2VA MODEL PATH=/models/MiniMax-H3/FL2VA serv… …
… For more information, see the vLLM Recipe . vllm serve MiniMaxAI/MiniMax-M3 \ --tensor-parallel-size 8 \ --enable-expert-parallel \ --block-size 128 \ --mm-encoder-attn-backend FLASHINFER \ --mm-processor-cache-type shm \ --tool-call-parser minimax m3 \ --enable-auto-tool-choice \ --reasoning-parse… …
… MiniMax behauptet, dass das M3-Modell damit Prompts fast zehnmal schneller auswerten kann als MiniMax M2 und bei der Generierung sogar um den Faktor 15 schneller ist . …
… MiniMax describes M3 as combining three frontier capabilities in one model: strong coding and agentic task performance, long-context MiniMax Sparse Attention MSA , and native multimodality for text, image, and video understanding. …
… Generated by Qwen/Qwen2.5-Coder-32B-Instruct We present MaxProof, a population-level test-time scaling framework for competition-level mathematical proof in the MiniMax-M3 series . …
… Along with this change to our evaluation, in this July release we’re adding 8 new models Claude Fable 5, Claude Sonnet 5, Claude Opus 4.8, GLM 5.2, Kimi K2.7 Code, MiniMax M3, Qwen 3.7 Plus and Qwen 3.7 Max to the leaderboard. …
… While we have only evaluated SparDA on 8B models, we hope it can shed light on inference optimization for larger frontier models with sparse attention capability, including DeepSeek-V4, GLM-5.1, and MiniMax M3. …
… For demonstration, he used MiniMax M2.7 , which is a 230B AI inference model & ran it through four different test setups, all powered by NVIDIA GPUs. …
To show you the most relevant results, we’ve omitted some entries very similar to those already shown. Repeat the search with the omitted results included.
