Metadata from the upstream Hugging Face repository:
Item
Value
License
apache-2.0
Base model
Qwen/Qwen3.5-9B
Library
transformers
Model type
qwen3_5
Pipeline
text-generation
Downloads
128
Repo revision
0934f3d2327ff2df2197495278c4c46ae5a56bd9
Files
File
Description
model.q4nx
Quantized weights (Q8_0 / Q4_1 / BF16)
config.json
FLM runtime configuration
tokenizer.json
Tokenizer vocabulary
tokenizer_config.json
Tokenizer configuration
chat_template.jinja
Chat template
vision_weight.q4nx
Vision model
Install and run
This repository works with
flm-add
, a small installer that copies the model
into the FastFlowLM user directory and registers the tag. It never
modifies the system FastFlowLM install.
This repository contains model weights and configuration files in the Hugging Face Transformers format.
These artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, and other standard runtimes with Qwen3.5 architecture support.
Qwen3.8-9B
is a full-parameter distillation of
Qwen3.8 2.4T A95B
into the Qwen3.5-9B architecture. The student was trained on
~70,000 curated teacher traces
from our internal Qwen3.8 distillation datasets — dense chain-of-thought spanning mathematics, code, general reasoning, instruction following, and tool use, quality-filtered before training.
The objective: bring the reasoning behavior of a frontier-scale teacher into a dense 9B that deploys on a single GPU.
Highlights
Distilled chain-of-thought
— every answer opens with a
<think>
block learned directly from Qwen3.8 2.4T A95B traces rather than synthetic self-generated reasoning.
Mathematics and code emphasis
— the trace mix is deliberately weighted toward hard math and competitive programming, the domains where distillation moves the needle most at this scale.
Native function calling
per Qwen3.5's specification — no wrapper or tool-specific fine-tune required.
262,144-token native context
, inherited from the Qwen3.5 base.
Full fine-tune
— every parameter updated; not an adapter.
Model Overview
Type: Causal Language Model (text path of a vision-language base)
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