Qwen seems to be moving away from smaller models. What does it mean for Local AI

<!-- SC_OFF --><div class="md"><p>Hey <a href="/r/LocalLLaMA">r/LocalLLaMA</a>,</p> <p>We’re living through something wild: “intelligence density” / capability density is scaling

<!-- SC_OFF --><div class="md"><p>All the major open-weight models released recently are huge, including <a href="https://qwen.ai/blog?id=qwen3.8">Qwen-3.8 soon to be released as

<!-- SC_OFF --><div class="md"><p>Hi. What do you think is the smallest Open model, as of Spring 2026, that can match/beat OpenAI GPT 4o Mini in the broadest sense possible?</p>

<!-- SC_OFF --><div class="md"><p>A noticeable trend is happening: more users are moving away from heavily aligned cloud models (like ChatGPT, Claude, Gemini) toward local or

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1sskmhv/recent_open_models_from_last_6_months_nov_2025/"> <img alt="Recent Open models from last 6 Months -

<!-- SC_OFF --><div class="md"><p>I need SOTA ai at like 2k TPS with tiny latency so that I can get time to first answer token under 3 seconds for real time replies with full COT

<!-- SC_OFF --><div class="md"><p>Long time Claude Opus user, but after the recent session limit changes by Anthropic, I am seriously considering trying Chinese models for coding.

<!-- SC_OFF --><div class="md"><p>I have experience using llama.cpp on Windows/Linux with 8GB NVIDIA card (384 GB/s bandwidth) and offloading to CPU to run MoE models. I typically