A user has conducted real-world coding benchmark tests on several 35B MoE-class local large language models, comparing Qwen 3.6, Ornith 1.0, and KAT Coder 2.5 Dev. While Qwen 3.6 served as a baseline with good initial performance, it showed tendencies to hallucinate confidence and drift in longer tasks. Ornith 1.0, despite impressive benchmarks, often overthought simple tasks and exhibited similar reasoning loop issues to Qwen. KAT Coder 2.5 Dev, however, surprised the user with more decisive outputs, better performance in practical coding scenarios, and fewer recurring issues, marking a perceived step forward in local model utility for serious coding workloads. AI
IMPACT Highlights KAT Coder 2.5 Dev as a promising local model for serious coding tasks, potentially influencing developer tool choices.
RANK_REASON User-generated comparison of local LLMs for coding tasks, not a primary release or research paper.
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