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A Reddit user reports that Qwen3.8-27B autonomously retrieved a university class schedule through 80 tool calls using only credentials and a university name. In another test, it downloaded and analyzed a social-media video, installed Whisper for transcription, and enhanced video frames without human intervention.
A community developer created Qwen3.8-23B-Mini-Me by strategically removing layers from Qwen3.8-27B, reducing the model to approximately 22.7B parameters without severe reasoning degradation. The model is reported to work well for coding, agentic tasks, and multi-turn chats, but it has not yet been benchmarked and struggles more with edge cases and underspecified prompts.
Ornith AI has released three new Ornith 1.5 model variants: 9B, 35B-A3B, and 397B. Hugging Face listings are available for both the original model formats and GGUF versions.
The post argues that Qwen3.8 intermediate tokens should not be interpreted as human-like reasoning. Citing research, it highlights that trace validity often does not correlate with answer correctness, and that models trained on corrupted or irrelevant traces can perform as well as or better than models trained on valid traces.
In an interview, Llama Ventures partner and Yidao founder Zhou Hang discusses how AI will reshape careers, entrepreneurship, and traditional industries. He argues that workers should develop commercial judgment and seek AI opportunities in overlooked sectors rather than simply compete for shrinking technical roles.
QwenMix-3.7 is an experimental merge of the Qwen3.8-27B and Qwen3.6-27B models. The creator reports that it passed a basic smoke test, but no meaningful evaluation has been performed yet.