What are the hardware requirements for Regulus Qwen3 R1 Llama Distill 1.7B?

Regulus Qwen3 R1 Llama Distill 1.7B requires approximately 3.4 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 Regulus Qwen3 R1 Llama Distill 1.7B and how large is it?

Regulus Qwen3 R1 Llama Distill 1.7B is developed by prithivMLmods, a model with 70b 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 Regulus Qwen3 R1 Llama Distill 1.7B?

Regulus Qwen3 R1 Llama Distill 1.7B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Regulus Qwen3 R1 Llama Distill 1.7B by prithivMLmods — VRAM 3.4GB, 40K context

Name: Regulus Qwen3 R1 Llama Distill 1.7B
Author: prithivMLmods

Regulus Qwen3 R1 Llama Distill 1.7B is an open-source language model by prithivMLmods. Features: 70b LLM, VRAM: 3.4GB, Context: 40K, License: apache-2.0, LLM Explorer Score: 0.2.

Base model:finetune:qwen/qwen3... Base model:qwen/qwen3-1.7b Conversational Dataset:magpie-align/magpie-re... Distill En Endpoints compatible Experimental Llama Qwen3 Region:us Safetensors Trl

Model Card on HF 🤗: https://huggingface.co/prithivMLmods/Regulus-Qwen3-R1-Llama-Distill-1.7B

Regulus Qwen3 R1 Llama Distill 1.7B Parameters and Internals

LLM Name	Regulus Qwen3 R1 Llama Distill 1.7B
Repository 🤗	https://huggingface.co/prithivMLmods/Regulus-Qwen3-R1-Llama-Distill-1.7B
Base Model(s)	Qwen/Qwen3-1.7B Qwen/Qwen3-1.7B
Model Size	70b
Required VRAM	3.4 GB
Updated	2026-08-07
Maintainer	prithivMLmods
Model Type	qwen3
Model Files	3.4 GB
Supported Languages	en
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	40960
Model Max Length	40960
Transformers Version	4.55.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
Vocabulary Size	151936
Torch Data Type	float16
Errors	replace

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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 Regulus Qwen3 R1 Llama Distill 1.7B

Model	Likes	Downloads	VRAM
...us Qwen3 R1 Llama Distill GGUF	2	63	0 GB