Qwen3.8-27B-Humanlike-Chat 2.0 Released with Tool Calling and Improved Instruction Following
Developer /u/kvyb released version 2.0 of the Qwen3.8-27B-Humanlike-Chat model, combining a natural human texting tone with functional tool calling and improved instruction following. The updated model uses on-policy distillation to smoothly switch between casual texting, character roleplay, and formal tasks. Standard LLMs often suffer from overly robotic 'assistant speak,' while previous conversational fine-tunes lacked practical functions like tool integration. This release demonstrates that open models can maintain a humanlike tone without sacrificing practical utility like calling APIs or asking clarifying questions. Trained via on-policy distillation using two teacher models, version 2.0 achieved 23.5% on the creator's 'ishuman' benchmark compared to 0.3% for the base model, alongside higher scores on instruction benchmarks like IFBench and When2Call. However, it shows minor performance drops in complex knowledge (MMLU-Pro dropped to 72.5) and competitive coding (LiveCodeBench dropped to 51).
## BACKGROUND
Fine-tuning large language models frequently relies on Low-Rank Adaptation (LoRA), a parameter-efficient technique that trains task-specific adaptations without modifying all base parameters. Additionally, AI chat interfaces often rely on character cards, which structure prompts to define personality traits, example dialogs, and response rules for models.