No official torrent yet — requesting it tells the flock what to host next. You cannot seed a catalog-only page.
Cataloged from Jackrong/Qwen3.5-9B-Gemini-3.1-Pro-Reasoning-Distill-GGUF
All models by Jackrong →Qwen3.5-9B-Gemini-3.1-Pro-Reasoning-Distill is a reasoning model fine-tuned on top of Qwen3.5-9B.
The model is primarily optimized through high-density reasoning distillation sourced from Gemini 3.1, while also incorporating additional reasoning traces distilled from Qwen3.5-27B and a broader Gemini 3.0 Pro reasoning corpus.
Through Supervised Fine-Tuning focused on structured analytical behavior, this model aims to reshape the base model’s reasoning style into a more coherent, better-organized, and higher-density Chain-of-Thought (CoT) pattern.
It is especially designed to improve decomposition, planning, abstraction, and response cleanliness on complex multi-step tasks.
This model inherits a more structured reasoning style influenced by Gemini 3.1-style analytical planning.
Compared with more loosely exploratory reasoning patterns, this model tends to organize the problem before answering:
The dataset consists of multiple reasoning distillation sources:
⚠️ Distillation & Task-Specific Fine-Tuning Effects: This model has been distilled and further fine-tuned on top of the base model for reasoning-oriented tasks. These techniques may improve performance on certain specialized tasks, but they can also influence the model’s generalization ability in broader scenarios and may lead to partial forgetting of some pretraining knowledge. The extent of these effects depends on factors such as the quality, scale, and distribution of the datasets used during distillation and fine-tuning. As a result, the model’s behavior may differ from the base model across different tasks or application contexts. Users are encouraged to evaluate the model according to their specific requirements before deployment. Thank you for your understanding～
Special thanks to the Qwen team for the strong base architecture, and to the broader open-source ecosystem for enabling efficient reasoning distillation workflows. We also acknowledge the value of the distilled reasoning corpora derived from Gemini 3.1 Pro, Qwen3.5, and Gemini 3 Pro, which made this model possible.
My Thought Process / My Analysis of the problem:
1. Restate the task and identify the true objective.2. Abstract the problem into a higher-level reasoning frame.3. Identify the key mechanism, failure mode, or constraint.4. Separate likely misconceptions from the actual core issue.5. Plan the structure of the final response.6. Deliver a cleaner, more direct, and higher-density answer....Base Model (Qwen3.5-9B) │ ▼Supervised Fine-Tuning (SFT) + LoRA + Reasoning Distillation(Response-Only Training masked on "<|im_start|>assistant\n<think>") │ ▼Final Model Text Only (Jackrong/Qwen3.5-9B-Gemini-3.1-Pro-Reasoning-Distill)