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

Qwen3.6-35B-A3B-AWQ

Name: Qwen3.6-35B-A3B-AWQ
Author: QuantTrio

Then, create a fresh Python environment (e.g. python3.12 venv) and run: bash pip install vllm==0.19.0 pip install transformers==5.5.4 vLLM Official Guide

Params

36.0 B

Context

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Downloads 30d

841 K

Likes

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

Download history

daily snapshots · 56 days

▲ 30 K in the last 30 days (3.5%)

1.2 M841 K

Jul 28Aug 15Sep 3Sep 21

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	i32	25.5 GB	33.9 GB	❌ Won’t fit

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

Specifications

Architecture: Qwen3_5MoeForConditionalGeneration
Parameters: 36.0 B
Tensor type: I32
Licence: apache-2.0
First seen on the Hub: 2026-04-17
Base model: Qwen3.6-35B-A3B
Training datasets: undisclosed
Added to our catalog: 2026-07-28

Family

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

Base Qwen3.6-35B-A3B Qwen 3.3 M

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