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Mitiskuma/Qwen3.5-9B-q0f16-MLC
Qwen3.5-9B-q0f16-MLC is a machine learning model from Mitiskuma. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for mlc-llm.
This is the Qwen3.5-9B model in MLC format q0f16.
Downloads · 30 days
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13% of all-time downloads
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From the Hugging Face model README
This is the Qwen3.5-9B model in MLC format q0f16.
Qwen3.5 is a hybrid architecture: 75% GatedDeltaNet recurrent linear attention layers, 25% standard GQA softmax attention layers. This requires the kHybrid KVStateKind in MLC-LLM which manages both PagedKVCache and RNNState simultaneously.
Compiled with mlc-llm using the hybrid KVStateKind branch.
from mlc_llm import MLCEngine
model = "HF://Mitiskuma/Qwen3.5-9B-q0f16-MLC"
engine = MLCEngine(model, device="metal")
for response in engine.chat.completions.create(
messages=[{"role": "user", "content": "What is the meaning of life?"}],
model=model,
stream=True,
):
for choice in response.choices:
print(choice.delta.content, end="", flush=True)
print()
engine.terminate()
mlc_llm chat HF://Mitiskuma/Qwen3.5-9B-q0f16-MLC
| Parameter | Value |
|---|---|
| Base model | Qwen3.5-9B |
| Architecture | Qwen3.5 GatedDeltaNet (hybrid recurrent + attention) |
| Quantization | q0f16 |
| KV state kind | hybrid (PagedKVCache + RNNState) |
| Context window | 1024 (compile-time setting) |
| Conversation template | chatml |