What are the hardware requirements for ReasoningCore Llama 3.2 1B R1?

ReasoningCore Llama 3.2 1B R1 requires approximately 2.5 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed ReasoningCore Llama 3.2 1B R1 and how large is it?

ReasoningCore Llama 3.2 1B R1 is developed by EpistemeAI, a model with 1b 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 ReasoningCore Llama 3.2 1B R1?

ReasoningCore Llama 3.2 1B R1 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

ReasoningCore Llama 3.2 1B R1 by EpistemeAI — VRAM 2.5GB, 128K context

Name: ReasoningCore Llama 3.2 1B R1
Author: EpistemeAI

ReasoningCore Llama 3.2 1B R1 is an open-source language model by EpistemeAI. Features: 1b LLM, VRAM: 2.5GB, Context: 128K, License: llama3.2, LLM Explorer Score: 0.17.

Base model:epistemeai/reasonin... Base model:finetune:epistemeai... Conversational En Endpoints compatible Llama Pytorch Region:us Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/EpistemeAI/ReasoningCore-Llama-3.2-1B-r1

ReasoningCore Llama 3.2 1B R1 Parameters and Internals

LLM Name	ReasoningCore Llama 3.2 1B R1
Repository 🤗	https://huggingface.co/EpistemeAI/ReasoningCore-Llama-3.2-1B-r1
Base Model(s)	EpistemeAI/ReasoningCore-1B-r1-0 EpistemeAI/ReasoningCore-1B-r1-0
Model Size	1b
Required VRAM	2.5 GB
Updated	2026-07-31
Maintainer	EpistemeAI
Model Type	llama
Model Files	2.5 GB
Supported Languages	en
Model Architecture	LlamaForCausalLM
License	llama3.2
Context Length	131072
Model Max Length	131072
Transformers Version	4.48.2
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|finetune_right_pad_id\|>
Vocabulary Size	128256
Torch Data Type	float16

Rank the ReasoningCore Llama 3.2 1B R1 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 ReasoningCore Llama 3.2 1B R1

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ISA 02 Nano Llama 3.2 1B	1024K / 2.5 GB	47	3
LWM Text 1M	1024K / 13.5 GB	1149	29
LWM Text Chat 1M	1024K / 13.5 GB	57	173
JOSIE 1M Base	1024K / 13.5 GB	12	1
JOSIE 1M Base	1024K / 13.5 GB	6	1
MiniCPM5 1B MegaMerge Final	512K / 2.2 GB	0	1
MiniCPM5 1B	128K / 2.2 GB	354385	868
Llama 3.2 1B Instruct	128K / 2.5 GB	212072	100
...1B Claude Opus Fable5 Thinking	128K / 2.2 GB	6165	166
Llama 3.2 1B Instruct	128K / 2.5 GB	10114634	1549

Note: green Score (e.g. "73.2") means that the model is better than EpistemeAI/ReasoningCore-Llama-3.2-1B-r1.