What are the hardware requirements for QwQ 32B?

QwQ 32B requires approximately 65.8 GB of VRAM and supports a context window of 40K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed QwQ 32B and how large is it?

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

How does QwQ 32B perform on standard benchmarks?

QwQ 32B has the following published scores: LMSYS ELO 1336. Compare against reference models on this page or on the LLM Explorer leaderboards.

QwQ 32B by Columbidae — VRAM 65.8GB, 40K context

Name: QwQ 32B
Author: Columbidae

QwQ 32B is an open-source language model by Columbidae. Features: 32b LLM, VRAM: 65.8GB, Context: 40K, License: apache-2.0, LLM Explorer Score: 0.3, ELO: 1336.

Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-32b Chat Conversational En Endpoints compatible Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Columbidae/QwQ-32B

QwQ 32B Benchmarks

LMSys ELO 1336 vs 1272 (so35) 5%

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

QwQ 32B Parameters and Internals

LLM Name	QwQ 32B
Repository 🤗	https://huggingface.co/Columbidae/QwQ-32B
Base Model(s)	Qwen/Qwen2.5-32B Qwen/Qwen2.5-32B
Model Size	32b
Required VRAM	65.8 GB
Updated	2026-08-24
Maintainer	Columbidae
Model Type	qwen2
Model Files	4.9 GB: 1-of-14 4.9 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 2.1 GB: 14-of-14
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	40960
Model Max Length	40960
Transformers Version	4.43.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the QwQ 32B 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 32B

Best Alternatives	Context / RAM	Downloads	Likes
Openbuddy Qwq 32B V24.2 200K	195K / 65.8 GB	9	3
Openbuddy Qwq 32B V24.1 200K	195K / 65.8 GB	10	3
Openbuddy Qwq 32B V25.2q 200K	195K / 65.8 GB	1	4
...y Qwen2.5coder 32B V24.1q 200K	195K / 65.8 GB	9	2
DeepSeek R1 Distill Qwen 32B	128K / 65.7 GB	841633	1584
Qwen2.5 32B	128K / 65.5 GB	49206	180
RomboUltima 32B	128K / 20.7 GB	12	6
...wen2.5 32B Inst BaseMerge TIES	128K / 65.8 GB	28	17
Ultiima 32B	128K / 65.8 GB	11	7
...wen2.5 32B Inst BaseMerge TIES	128K / 65.8 GB	22	4

Note: green Score (e.g. "73.2") means that the model is better than Columbidae/QwQ-32B.