What are the hardware requirements for Llama3.1 8B E2 Epoch3 Merged Fp16?

Llama3.1 8B E2 Epoch3 Merged Fp16 requires approximately 16.1 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 Llama3.1 8B E2 Epoch3 Merged Fp16 and how large is it?

Llama3.1 8B E2 Epoch3 Merged Fp16 is developed by johnpaulbin, a model with 8b 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 Llama3.1 8B E2 Epoch3 Merged Fp16?

Llama3.1 8B E2 Epoch3 Merged Fp16 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama3.1 8B E2 Epoch3 Merged Fp16 by johnpaulbin — VRAM 16.1GB, 128K context

Name: Llama3.1 8B E2 Epoch3 Merged Fp16
Author: johnpaulbin

Llama3.1 8B E2 Epoch3 Merged Fp16 is an open-source language model by johnpaulbin. Features: 8b LLM, VRAM: 16.1GB, Context: 128K, License: apache-2.0, Quantized, Instruction-Based, Merged, LLM Explorer Score: 0.13.

Merged Model 4bit Base model:finetune:unsloth/me... Base model:unsloth/meta-llama-... Conversational En Endpoints compatible Fp16 Instruct Llama Pytorch Quantized Region:us Safetensors Sft Sharded Tensorflow Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/johnpaulbin/llama3.1-8b-e2-epoch3-merged-fp16

Llama3.1 8B E2 Epoch3 Merged Fp16 Parameters and Internals

LLM Name	Llama3.1 8B E2 Epoch3 Merged Fp16
Repository 🤗	https://huggingface.co/johnpaulbin/llama3.1-8b-e2-epoch3-merged-fp16
Base Model(s)	unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit
Merged Model	Yes
Model Size	8b
Required VRAM	16.1 GB
Updated	2026-08-08
Maintainer	johnpaulbin
Model Type	llama
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-4 5.0 GB: 2-of-4 4.9 GB: 3-of-4 1.2 GB: 4-of-4 5.0 GB: 1-of-4 5.0 GB: 2-of-4 4.9 GB: 3-of-4 1.2 GB: 4-of-4
Supported Languages	en
Quantization Type	fp16\|4bit
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	131072
Model Max Length	131072
Transformers Version	4.43.3
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|finetune_right_pad_id\|>
Vocabulary Size	128256
Torch Data Type	bfloat16

Rank the Llama3.1 8B E2 Epoch3 Merged Fp16 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 Llama3.1 8B E2 Epoch3 Merged Fp16

Best Alternatives	Context / RAM	Downloads	Likes
...B Instruct Gradient 1048K 4bit	1024K / 4.5 GB	10	2
...B Instruct Gradient 1048K 8bit	1024K / 8.6 GB	11	1
...truct Gradient 1048K Bpw6 EXL2	1024K / 6.7 GB	2	2
...truct Gradient 1048K Bpw5 EXL2	1024K / 5.8 GB	5	0
Llama 3 8B Instruct 1048K 4bit	1024K / 4.5 GB	525	25
Llama 3 8B Instruct 1048K 8bit	1024K / 8.6 GB	213	17
... Gradient 1048K 8.0bpw H8 EXL2	1024K / 8.6 GB	2	3
...ct Gradient 1048K Bpw2.25 EXL2	1024K / 3.4 GB	5	1
Llama 3 8B Instruct 262K 2bit	256K / 2.5 GB	11	1
...B Instruct 262k V2 EXL2 5.0bpw	256K / 5.8 GB	5	1

Note: green Score (e.g. "73.2") means that the model is better than johnpaulbin/llama3.1-8b-e2-epoch3-merged-fp16.