[!NOTE] Includes Unsloth chat template fixes ! For llama.cpp , use jinja Unsloth Dynamic 2.0 achieves superior accuracy & outperforms other leading quants. Qwen3 30B A3B Instruct 2507 Highlights We introduce the updated version of the Qwen3 30B A3B non thinking mode , named Qwen3 30B A3B Instruct 2507 , featuring the following key enhancements: Significant improvements in general capabilities, including instruction following, logical reasoning, text comprehension, mathematics, science, coding and tool usage . Substantial gains in long tail knowledge coverage across multiple languages . Markedly better alignment with user preferences in subjective and open ended tasks , enabling more helpful responses and higher quality text generation. Enhanced capabilities in 256K long context understanding . Model Overview Qwen3 30B A3B Instruct 2507 has the following features: Type: Causal Language Models Training Stage: Pretraining & Post training Number of Parameters: 30.5B in total and 3.3B activated Number of Paramaters (Non Embedding): 29.9B Number of Layers: 48 Number of Attention Heads (GQA): 32 for Q and 4 for KV Number of Experts: 128 Number of Activated Experts: 8 Context Length: 262,1…
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