Tootfinder

📊 Leads every instruction-following benchmark and nearly all tool-use benchmarks against models up to 4x its size, trailing only #Qwen3_5 9B on BFCLv4 — coding remains the weaker area
🔧 Day-one support for #llamacpp (GGUF),

📏 262,144 tokens of native context, validated up to 1,048,576. 40 of 50 layers use 512-token sliding-window attention, every 5th layer attends to everything. RULER at 1M tokens: 63.2 vs 57.5 for #Qwen3.5 35B-A3B
🇩🇪 Reasons in German on German prompts, with 4 reasoning effort levels (none, low, medium, high). AIME 2025: 87.5 in German, 96.9 in English. Trained with the Merlin-Arthur protoc…

🚀 #Alibaba launches #Qwen3.8, a 2.4-trillion-parameter flagship #LLM with open weights promised soon #AI