What are the hardware requirements for QWQ Stock?

QWQ Stock requires approximately 65.8 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed QWQ Stock and how large is it?

QWQ Stock is developed by wanlige, a model with 32b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate QWQ Stock?

QWQ Stock is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

QWQ Stock by wanlige — VRAM 65.8GB, 32K context

Name: QWQ Stock
Author: wanlige

QWQ Stock is an open-source language model by wanlige. Features: 32b LLM, VRAM: 65.8GB, Context: 32K, Instruction-Based, Merged, LLM Explorer Score: 0.17.

Merged Model Arxiv:2403.19522 Ara Base model:huihui-ai/deepseek-... Base model:maldv/awqward2.5-32... Base model:qwen/qwen2.5-32b Base model:qwen/qwen2.5-32b-in... Base model:qwen/qwq-32b Base model:qwen/qwq-32b-previe... Base model:tanliboy/lambda-qwe... Conversational Deu Endpoints compatible Eng Fra Instruct Ita Jpn Kor Por Qwen2 Region:us Rus Safetensors Sharded Spa Tensorflow Tha Vie Zho

Model Card on HF 🤗: https://huggingface.co/wanlige/QWQ-stock

QWQ Stock Parameters and Internals

LLM Name	QWQ Stock
Repository 🤗	https://huggingface.co/wanlige/QWQ-stock
Base Model(s)	Qwen/Qwen2.5-32B QwQ 32B maldv/Awqward2.5-32B-Instruct ...1 Distill Qwen 32B Abliterated QwQ 32B Preview Qwen/Qwen2.5-32B-Instruct tanliboy/lambda-qwen2.5-32b-dpo-test Qwen/Qwen2.5-32B Qwen/QwQ-32B maldv/Awqward2.5-32B-Instruct huihui-ai/DeepSeek-R1-Distill-Qwen-32B-abliterated Qwen/QwQ-32B-Preview Qwen/Qwen2.5-32B-Instruct tanliboy/lambda-qwen2.5-32b-dpo-test
Merged Model	Yes
Model Size	32b
Required VRAM	65.8 GB
Updated	2026-07-30
Maintainer	wanlige
Model Type	qwen2
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-14 5.0 GB: 2-of-14 4.9 GB: 3-of-14 4.9 GB: 4-of-14 4.9 GB: 5-of-14 4.9 GB: 6-of-14 4.9 GB: 7-of-14 4.9 GB: 8-of-14 4.9 GB: 9-of-14 4.9 GB: 10-of-14 4.9 GB: 11-of-14 4.9 GB: 12-of-14 4.9 GB: 13-of-14 1.9 GB: 14-of-14
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.48.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the QWQ Stock capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to QWQ Stock

Best Alternatives	Context / RAM	Downloads	Likes
...y Qwen2.5coder 32B V24.1q 200K	195K / 65.8 GB	9	2
...wen2.5 32B Inst BaseMerge TIES	128K / 65.8 GB	19	17
...wen2.5 32B Inst BaseMerge TIES	128K / 65.8 GB	18	4
Franqwenstein 35B	128K / 69.8 GB	5	8
ELYZA Thinking 1.0 Qwen 32B	128K / 65.8 GB	23	10
Archaeo 32B KTO	128K / 65.8 GB	15	4
Hamanasu Magnum QwQ 32B	128K / 65.8 GB	295	9
Qwen2.5 32B Gokgok Step3	128K / 65.7 GB	6	0
Openthaigpt R1 32B Instruct	128K / 65.8 GB	33	8
Qwen2.5 32B Dark Days Stage2	128K / 65.8 GB	9	0

Note: green Score (e.g. "73.2") means that the model is better than wanlige/QWQ-stock.