Downloads · 30 days
23
6% of all-time downloads
Qwen3-14B-AWQ-INT4
drawais/Qwen3-14B-AWQ-INT4
Qwen3-14B-AWQ-INT4 is a text generation model from drawais. Use it when you need the model to write or continue text. The card lists the license as apache-2.0.
INT4 quantization of Qwen/Qwen3-14B. Built to run on a single consumer GPU (≥10 GB VRAM).
All-time downloads
382
Public
Parameters
14.8B
10 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors10 GB · 100%
Parameter types
How the weights are stored.
I3213.2B · 89%
Try a prompt
Base models
Model card
From the Hugging Face model README
Qwen3-14B-AWQ-INT4
INT4 quantization of Qwen/Qwen3-14B. Built to run on a single consumer GPU (≥10 GB VRAM).
Footprint
| Source params | 14B |
| Quantized weights | ~9.4 GB on disk |
| Inference VRAM (incl. KV cache @ 32K context) | ~16 GB |
Fits any 16 GB+ consumer card. No homelab needed.
Bench
Scored on drawais/needle-1M-bench-mvp (50K-token haystack, real arxiv text):
| Metric | Score |
|---|---|
| Overall recall | 90.0% |
| Paper-anchored | 80.0% |
| Synthetic codes | 100.0% |
Quick start
vllm serve drawais/Qwen3-14B-AWQ-INT4 --quantization awq_marlin --max-model-len 32768
from transformers import AutoTokenizer, AutoModelForCausalLM
tok = AutoTokenizer.from_pretrained("drawais/Qwen3-14B-AWQ-INT4")
model = AutoModelForCausalLM.from_pretrained("drawais/Qwen3-14B-AWQ-INT4", device_map="auto")
Context length
Native: 40,960 tokens (inherits from base model). For longer contexts, enable YaRN rope-scaling per the base model's config — supported by vLLM and Transformers.
License
Apache 2.0 (inherits from base model).
- Task
- Text Generation
- Type
- qwen3
- License
- apache-2.0
- Languages
- en
- Created
- Apr 27, 2026
- Updated
- Apr 27, 2026