What are the hardware requirements for QwQ LCoT 7B Instruct?

QwQ LCoT 7B Instruct requires approximately 15.2 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 LCoT 7B Instruct and how large is it?

QwQ LCoT 7B Instruct is developed by prithivMLmods, a model with 7b 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 LCoT 7B Instruct?

QwQ LCoT 7B Instruct is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

QwQ LCoT 7B Instruct by prithivMLmods — VRAM 15.2GB, 32K context

Name: QwQ LCoT 7B Instruct
Author: prithivMLmods

QwQ LCoT 7B Instruct is an open-source language model by prithivMLmods. Features: 7b LLM, VRAM: 15.2GB, Context: 32K, License: creativeml-openrail-m, Instruction-Based, LLM Explorer Score: 0.25.

7b Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-7b-ins... Conversational Dataset:amphora/qwq-longcot-13... En Endpoints compatible Instruct Long-cot Math Qwen with questions Qwen2 Qwen2.5 Qwq Region:us Safetensors Sft Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/prithivMLmods/QwQ-LCoT-7B-Instruct

QwQ LCoT 7B Instruct Parameters and Internals

LLM Name	QwQ LCoT 7B Instruct
Repository 🤗	https://huggingface.co/prithivMLmods/QwQ-LCoT-7B-Instruct
Base Model(s)	Qwen/Qwen2.5-7B-Instruct Qwen/Qwen2.5-7B-Instruct
Model Size	7b
Required VRAM	15.2 GB
Updated	2026-08-02
Maintainer	prithivMLmods
Model Type	qwen2
Instruction-Based	Yes
Model Files	4.9 GB: 1-of-4 4.9 GB: 2-of-4 4.3 GB: 3-of-4 1.1 GB: 4-of-4
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
License	creativeml-openrail-m
Context Length	32768
Model Max Length	32768
Transformers Version	4.46.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|PAD_TOKEN\|>
Vocabulary Size	152064
Torch Data Type	float16
Errors	replace

Rank the QwQ LCoT 7B Instruct 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

Quantized Models of the QwQ LCoT 7B Instruct

Model	Likes	Downloads	VRAM
QwQ LCoT 7B Instruct GGUF	3	37	4 GB

Best Alternatives to QwQ LCoT 7B Instruct

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 7B Instruct 1M	986K / 15.4 GB	52534	373
Hush Qwen2.5 7B RP V1.4 1M	986K / 15.2 GB	10	2
Qwen2.5 7B RRP 1M	986K / 15.2 GB	5	6
Qwen2.5 7B CelestialHarmony 1M	986K / 14.8 GB	8	7
Q2.5 Instruct 1M Harmony	986K / 15.2 GB	4	2
Impish QWEN 7B 1M	986K / 15.2 GB	4	6
COCO 7B Instruct 1M	986K / 15.2 GB	9	4
Apollo 7B	986K / 15.2 GB	8	0
Graph R1 7B	986K / 15.3 GB	7	3
Qwen2.5 7B Sky R1 Mini	986K / 15.2 GB	6	0

Note: green Score (e.g. "73.2") means that the model is better than prithivMLmods/QwQ-LCoT-7B-Instruct.