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Person: "grad62304977"
not much happened today
claude-4.6 claude-opus-4.6 claude-sonnet-4.6 qwen-3.5 qwen3.5-397b-a17b glm-5 gemini-3.1-pro minimax-m2.5 anthropic alibaba scaling01 arena artificial-analysis benchmarking token-efficiency ai-agent-autonomy reinforcement-learning asynchronous-learning model-performance open-weights reasoning software-engineering agentic-engineering eshear theo omarsar0 grad62304977 scaling01
Anthropic released Claude Opus/Sonnet 4.6, showing a significant intelligence index jump but with increased token usage and cost. Anthropic also shared insights on AI agent autonomy, highlighting human-in-the-loop prevalence and software engineering tool calls. Alibaba launched Qwen 3.5 with discussions on reasoning efficiency and token bloat, plus open-sourced Qwen3.5-397B-A17B FP8 weights. The GLM-5 technical report introduced asynchronous agent reinforcement learning and compute-efficient techniques. Rumors about Gemini 3.1 Pro suggest longer reasoning capabilities, while MiniMax M2.5 appeared on community leaderboards. The community debates benchmark reliability and model performance nuances.
MiniMax M2 230BA10B — 8% of Claude Sonnet's price, ~2x faster, new SOTA open model
minimax-m2 hailuo-ai huggingface baseten vllm modelscope openrouter cline sparse-moe model-benchmarking model-architecture instruction-following tool-use api-pricing model-deployment performance-evaluation full-attention qk-norm gqa rope reach_vb artificialanlys akhaliq eliebakouch grad62304977 yifan_zhang_ zpysky1125
MiniMax M2, an open-weight sparse MoE model by Hailuo AI, launches with ≈200–230B parameters and 10B active parameters, offering strong performance near frontier closed models and ranking #5 overall on the Artificial Analysis Intelligence Index v3.0. It supports coding and agent tasks, is licensed under MIT, and is available via API at competitive pricing. The architecture uses full attention, QK-Norm, GQA, partial RoPE, and sigmoid routing, with day-0 support in vLLM and deployment on platforms like Hugging Face and Baseten. Despite verbosity and no tech report, it marks a significant win for open models.