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Qwen3.5-9B-Claude-4.8-Opus-NPU2
Atomic-Germ/Qwen3.5-9B-Claude-4.8-Opus-NPU2
Qwen3.5-9B-Claude-4.8-Opus-NPU2 is a text generation model from Atomic-Germ. Use it when you need the model to write or continue text. The card lists the license as apache-2.0.
A focused Qwen3.5-9B fine-tune with trace-inverted CoT from Claude-Opus-4.8, specialized for coding, mathematics, and cybersecurity reasoning - roughly 20% shorter thinking traces than the base model. Converted to Q4N…
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.q4nx8.8 GB · 100%
At a glance
- Task
- Text Generation
- License
- apache-2.0
- Model type
- qwen3_5_text
- Access
- Public
- Created
- Jun 27, 2026
- Updated
- Sep 17, 2026
- SHA
- e6bb94c4
Try a prompt
Base models
Model card
From the Hugging Face model README
IF YOU USE COMMUNITY QWEN MODELS DO NOT UPGRADE TO FLM v1.0.2+
Qwen3.5-9B-Claude-4.8-Opus - Q4NX for FastFlowLM (AMD Ryzen AI XDNA2)
A focused Qwen3.5-9B fine-tune with trace-inverted CoT from Claude-Opus-4.8, specialized for coding, mathematics, and cybersecurity reasoning - roughly 20% shorter thinking traces than the base model. Converted to Q4NX 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 (
flmCLI) - 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) |
| vision_weight.q4nx | Vision tower weights (multimodal input) |
| 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 qwen3.5-claude:9b. It never
modifies the system FastFlowLM install.
uv tool install flm-add
flm-add Atomic-Germ/Qwen3.5-9B-Claude-4.8-Opus-NPU2 --family qwen3.5
FLM_CONFIG_PATH="$HOME/.config/flm/model_list.json" FLM_XCLBIN_PATH="$HOME/.config/flm" flm run qwen3.5-claude: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:
qwen3.5-claude:9b - Engine family:
qwen3.5 - Kernel source: Qwen3.5-9B-NPU2
- Context length: 262,144 tokens (from config)
model.q4nxsize: 7.76 GB- Base model: Qwen/Qwen3.5-9B
- License: apache-2.0
GhostWriter Influence Test (Arbitrary but repeatable benchmark)
Tested on an AMD Ryzen AI 340 Framework 13 laptop.
| Metric | Value |
|---|---|
| Prompt Tokens | 9,210 |
| Completion Tokens | 1,537 |
| Total Tokens | 10,747 |
| Active KV Tokens | 10,747 |
| Max KV Token Capacity | 32,768 |
| KV Token Occupancy | 32.80% |
| Load Duration | 0.000000621 seconds |
| Prefill Duration (TTFT) | 33.71 ms |
| Decoding Duration | 268.54 ms |
| Prefill Speed | 273.21 tokens/sec |
| Decoding Speed | 5.72 tokens/sec |
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: Qwen/Qwen3.5-9B
- Task
- Text Generation
- Type
- qwen3_5_text
- License
- apache-2.0
- Languages
- en
- Created
- Jun 27, 2026
- Updated
- Sep 17, 2026