What are the hardware requirements for RA Reasoner2.0?

RA Reasoner2.0 requires approximately 20.5 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 RA Reasoner2.0 and how large is it?

RA Reasoner2.0 is developed by Daemontatox, a model with 10.3b 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 RA Reasoner2.0?

RA Reasoner2.0 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

RA Reasoner2.0 by Daemontatox — VRAM 20.5GB, 32K context

Name: RA Reasoner2.0
Author: Daemontatox

RA Reasoner2.0 is an open-source language model by Daemontatox. Features: 10.3b LLM, VRAM: 20.5GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.24.

Autotrain compatible Base model:daemontatox/ra reas... Base model:finetune:daemontato... Conversational Cot Dataset:daemontatox/deepthinki... En Endpoints compatible Llama Model-index Pytorch Reasoning Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Daemontatox/RA_Reasoner2.0

RA Reasoner2.0 Parameters and Internals

LLM Name	RA Reasoner2.0
Repository 🤗	https://huggingface.co/Daemontatox/RA_Reasoner2.0
Base Model(s)	RA Reasoner Daemontatox/RA_Reasoner
Model Size	10.3b
Required VRAM	20.5 GB
Updated	2025-09-23
Maintainer	Daemontatox
Model Type	llama
Model Files	4.9 GB: 1-of-5 4.9 GB: 2-of-5 4.9 GB: 3-of-5 4.9 GB: 4-of-5 0.9 GB: 5-of-5 4.9 GB: 1-of-5 4.9 GB: 2-of-5 4.9 GB: 3-of-5 4.9 GB: 4-of-5 0.9 GB: 5-of-5
Supported Languages	en
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.47.1
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|pad\|>
Vocabulary Size	131072
Torch Data Type	float16

Rank the RA Reasoner2.0 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 RA Reasoner2.0

Best Alternatives	Context / RAM	Downloads	Likes
Virtuoso Lite Tensopolis V1	32K / 20.5 GB	17	0
Virtuoso Lite Tensopolis V2	32K / 20.5 GB	17	0
Helpingai3 Raw	32K / 20.5 GB	6	8
HelpingAI 3	32K / 20.5 GB	9	8

Note: green Score (e.g. "73.2") means that the model is better than Daemontatox/RA_Reasoner2.0.