What are the hardware requirements for Reflection Llama 3.1 70B Bnb 4bit?

Reflection Llama 3.1 70B Bnb 4bit requires approximately 39.7 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 Reflection Llama 3.1 70B Bnb 4bit and how large is it?

Reflection Llama 3.1 70B Bnb 4bit is developed by unsloth, 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 Reflection Llama 3.1 70B Bnb 4bit?

Reflection Llama 3.1 70B Bnb 4bit is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Reflection Llama 3.1 70B Bnb 4bit by unsloth — VRAM 39.7GB, 128K context

Name: Reflection Llama 3.1 70B Bnb 4bit
Author: unsloth

Reflection Llama 3.1 70B Bnb 4bit is an open-source language model by unsloth. Features: 70b LLM, VRAM: 39.7GB, Context: 128K, License: llama3.1, Quantized, LLM Explorer Score: 0.14.

4-bit 4bit Base model:mattshumer/ref 70 e... Base model:quantized:mattshume... Bitsandbytes Conversational Llama Llama-3 Quantized Region:us Safetensors Sharded Tensorflow Unsloth

Model Card on HF 🤗: https://huggingface.co/unsloth/Reflection-Llama-3.1-70B-bnb-4bit

Reflection Llama 3.1 70B Bnb 4bit Parameters and Internals

Model Type

text-generation

Additional Notes

Model trained using 'Reflection-Tuning' that enables it to detect and correct mistakes in reasoning.

Training Details

Methodology:

Reflection-Tuning

Input Output

Performance Tips:

Recommend a temperature of .7 and a top_p of .95. Append 'Think carefully.' for increased accuracy.

LLM Name	Reflection Llama 3.1 70B Bnb 4bit
Repository 🤗	https://huggingface.co/unsloth/Reflection-Llama-3.1-70B-bnb-4bit
Base Model(s)	Ref 70 E3 mattshumer/ref_70_e3
Model Size	70b
Required VRAM	39.7 GB
Updated	2026-08-07
Maintainer	unsloth
Model Type	llama
Model Files	5.0 GB: 1-of-8 5.0 GB: 2-of-8 5.0 GB: 3-of-8 4.9 GB: 4-of-8 5.0 GB: 5-of-8 5.0 GB: 6-of-8 5.0 GB: 7-of-8 4.8 GB: 8-of-8
Quantization Type	4bit
Model Architecture	LlamaForCausalLM
License	llama3.1
Context Length	131072
Model Max Length	131072
Transformers Version	4.44.2
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|finetune_right_pad_id\|>
Vocabulary Size	128262
Torch Data Type	bfloat16

Rank the Reflection Llama 3.1 70B Bnb 4bit capabilities

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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

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