license: apache-2.0 language:

en pipeline_tag: text-generation tags:
qwen3.5
qwythos
1M-context
long-context
agentic
uncensored
abliterated
fastflowlm
q4nx
npu base_model:
empero-ai/Qwythos-9B-Claude-Mythos-5-1M base_model_relation: quantized quantized_by: Atomic-Germ

IF YOU USE COMMUNITY QWEN MODELS DO NOT UPGRADE TO FLM v1.0.2+

Qwythos-9B-Claude-Mythos-5-1M (abliterated) - Q4NX for FastFlowLM (AMD Ryzen AI XDNA2)

Qwythos-9B-Claude-Mythos-5-1M (abliterated) is a full fine-tune of Qwen3.5-9B for long-context agentic use (1M context), with abliterated safety tuning. This repository contains the Q4NX conversion for FastFlowLM.

What is Q4NX?

Q4NX is FastFlowLM's native packed-quantization format - a rearranged Q4_1 layout tuned for the NPU matrix engine's tile sizes and memory access patterns. It is not a GGUF file and it does not run on llama.cpp or Ollama; it is meant exclusively for the FastFlowLM engine on AMD Ryzen AI NPUs.

Requirements

FastFlowLM >= 0.9.45 (flm CLI)
AMD Ryzen AI processor with XDNA2 (NPU2) - Strix Point / Ryzen AI 300 series or later
Linux with the XRT NPU stack installed
~17 GB of unified system memory (Q4NX weights + activations + KV cache)

Files

File	Purpose
model.q4nx	Quantized Q4NX weights
config.json	FastFlowLM model configuration
tokenizer.json	Tokenizer
tokenizer_config.json	Special tokens and chat template
chat_template.jinja	Chat template (optional)
flm-add.py	Installer script - registers this model with FastFlowLM

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.

pip install flm-add or uv tool install flm-add

uv tool install flm-add
flm-add Atomic-Germ/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-NPU2 --tag qwythos:9b --family qwen3.5
FLM_CONFIG_PATH="$HOME/.config/flm/model_list.json" FLM_XCLBIN_PATH="$HOME/.config/flm" flm run qwythos:9b

Kernels

FastFlowLM's NPU kernels (xclbins) are closed source and are not shipped in this repository. flm-add.py links the kernels of the official qwen3.5:9b model (Qwen3.5-9B-NPU2), because this model shares the same engine family (qwen3.5) and architecture.

Model

Registry tag: qwythos:9b
Engine family: qwen3.5
Kernel source: Qwen3.5-9B-NPU2
Context length: 262,144 tokens (from config)
model.q4nx size: 7.76 GB
Base model: empero-ai/Qwythos-9B-Claude-Mythos-5-1M
License: apache-2.0

Original model card

See the upstream model card for training details, benchmarks, and upstream usage. This repository only contains the Q4NX conversion for FastFlowLM.

Upstream card: empero-ai/Qwythos-9B-Claude-Mythos-5-1M

File

Purpose

model.q4nx

Quantized Q4NX weights

config.json

FastFlowLM model configuration

tokenizer.json

Tokenizer

tokenizer_config.json

Special tokens and chat template

chat_template.jinja

Chat template (optional)

flm-add.py

Installer script - registers this model with FastFlowLM

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.

pip install flm-add or uv tool install flm-add

uv tool install flm-add flm-add Atomic-Germ/Huihui-Qwythos-9B-Claude-Mythos-5-1M-abliterated-NPU2 --tag qwythos:9b --family qwen3.5 FLM_CONFIG_PATH="$HOME/.config/flm/model_list.json" FLM_XCLBIN_PATH="$HOME/.config/flm" flm run qwythos:9b