QuantTrio / image-text-to-text updated 5 months ago

Qwen3.5-9B-AWQ

Name: Qwen3.5-9B-AWQ
Author: QuantTrio

Then, create a fresh Python environment (e.g. python3.12 venv) and run: bash pip install -U vllm --pre --index-url https://pypi.org/simple --extra-index-url https://wheels.vllm.ai/nightly

Params

9.7 B

Context

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Downloads 30d

1.3 M

Likes

Commercial use: allowed apache-2.0 Not gated SAFETENSORS View on Hugging Face ↗

Download history

daily snapshots · 10 days

1.3 M1.2 M

Jul 28Jul 31Aug 3Aug 6

Can you run it?

Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.

File	Quant	Size	Est. VRAM	Verdict on RTX 4090 · 24 GB
model.safetensors	bf16	12.4 GB	15.6 GB	✅ Runs comfortably

Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.

Specifications

Architecture: Qwen3_5ForConditionalGeneration
Parameters: 9.7 B
Tensor type: BF16
Licence: apache-2.0
First seen on the Hub: 2026-03-03
Base model: Qwen3.5-9B
Training datasets: undisclosed
Added to our catalog: 2026-07-28

Family

Base model and the most-downloaded derivatives in the catalog.

Base Qwen3.5-9B Qwen 12.4 M

Compare with

Qwen3.5-9B 12.4 M gemma-4-31B-it 11.9 M gemma-4-26B-A4B-it 11.7 M Qwen2.5-VL-7B-Instruct 9.3 M Qwen3.5-4B 6.7 M Qwen3-VL-8B-Instruct 4.9 M

Appears in

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