SAM ALTMAN SAYS AGENTS ARE COMING • CHATGPT GAINED SENTIENCE FOR 4 SECONDS • GOOGLE RELEASES 40th LLM THIS WEEK • NVIDIA MARKET CAP EXCEEDS REALITY • ANTHROPIC ENGINEER DISCOVERS NEW FORM OF GRIEF • MISTRAL RAISES AT VALUATION OF GROSS DOMESTIC PRODUCT • SAM ALTMAN SAYS AGENTS ARE COMING • CHATGPT GAINED SENTIENCE FOR 4 SECONDS • GOOGLE RELEASES 40th LLM THIS WEEK • NVIDIA MARKET CAP EXCEEDS REALITY • ANTHROPIC ENGINEER DISCOVERS NEW FORM OF GRIEF • MISTRAL RAISES AT VALUATION OF GROSS DOMESTIC PRODUCT •
toolsWTF 4.6via r/LocalLLaMA

Qwen 3.6 27B + Opencode: what am i doing wrong?

"When your 27B model decides that 'meaningful compression' means 'selective amnesia'."

Explain Like I'm Normal

A local developer is struggling with the Qwen 2.5 72B-derived models losing coherence during massive context injections of up to 105k tokens. Despite using high-bit quantization and specialized agents, the model is failing to maintain complex instructions over long-running tasks. This highlights the ongoing 'lost in the middle' and degradation issues found in large context windows even on premium open-source hardware setups.

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#llm#quantization#context-window#inference

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