What are the hardware requirements for NeuralBeagle14 7B?

NeuralBeagle14 7B requires approximately 14.4 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 NeuralBeagle14 7B and how large is it?

NeuralBeagle14 7B is developed by mlabonne, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does NeuralBeagle14 7B perform on standard benchmarks?

NeuralBeagle14 7B has the following published scores: MMLU 64.55. Compare against reference models on this page or on the LLM Explorer leaderboards.

NeuralBeagle14 7B by mlabonne — VRAM 14.4GB, 32K context

Name: NeuralBeagle14 7B
Author: mlabonne

NeuralBeagle14 7B is an open-source language model by mlabonne. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: cc-by-nc-4.0, HF Score: 74.7, LLM Explorer Score: 0.18, Arc: 73, HellaSwag: 88.3, MMLU: 64.6, TruthfulQA: 69.9, WinoGrande: 82.4, GSM8K: 70.3.

Base model:finetune:mlabonne/b... Base model:mlabonne/beagle14-7... Conversational Dpo Endpoints compatible Lazymergekit Merge Mergekit Mistral Model-index Region:us Rlhf Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/mlabonne/NeuralBeagle14-7B

NeuralBeagle14 7B Benchmarks

IFEval: 49.35 vs 88 (so35)^-43.9%

ARC: 72.95 vs 96.7 (so35)^-24.6%

HellaSwag: 88.34 vs 95.3 (gpt4)^-7.3%

MMLU: 64.55 vs 88.3 (so35)^-26.9%

TruthfulQA: 69.93 vs 59 (gpt4)^18.5%

WinoGrande: 82.4 vs 87.5 (gpt4)^-5.8%

GSM8K: 70.28 vs 96.4 (so35)^-27.1%

MATH Lvl 5: 5.21

LLME Score: 0.18197

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

NeuralBeagle14 7B (mlabonne/NeuralBeagle14-7B)

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NeuralBeagle14 7B Parameters and Internals

Model Type

text generation

Use Cases

Primary Use Cases:

Instruction following, Reasoning tasks, Roleplay (RP), Storytelling

Additional Notes

NeuralBeagle14-7B is considered one of the best models in its parameter size category due to its strong performance in benchmarks.

Training Details

Data Sources:

argilla/distilabel-intel-orca-dpo-pairs

Methodology:

Direct Preference Optimization (DPO) fine-tuning

Context Length:

8000

LLM Name	NeuralBeagle14 7B
Repository 🤗	https://huggingface.co/mlabonne/NeuralBeagle14-7B
Base Model(s)	Beagle14 7B mlabonne/Beagle14-7B
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-04-28
Maintainer	mlabonne
Model Type	mistral
Model Files	4.9 GB: 1-of-3 5.0 GB: 2-of-3 4.5 GB: 3-of-3
Model Architecture	MistralForCausalLM
License	cc-by-nc-4.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.35.2
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32000
Torch Data Type	float16

Quantized Models of the NeuralBeagle14 7B

Model	Likes	Downloads	VRAM
NeuralBeagle14 7B GGUF	1	92	2 GB
NeuralBeagle14 7B GGUF	26	190	2 GB
NeuralBeagle14 7B GGUF	0	57	2 GB
NeuralBeagle14 7B AWQ	3	15	4 GB
NeuralBeagle14 7B GPTQ	5	8	4 GB

Best Alternatives to NeuralBeagle14 7B

Best Alternatives	Context / RAM	Downloads	Likes
...Nemo Instruct 2407 Abliterated	1000K / 24.5 GB	254	20
MegaBeam Mistral 7B 512K	512K / 14.4 GB	11443	54
SpydazWeb AI HumanAI RP	512K / 14.4 GB	21	1
SpydazWeb AI HumanAI 002	512K / 14.4 GB	18	1
...daz Web AI ChatML 512K Project	512K / 14.5 GB	12	0
MegaBeam Mistral 7B 300K	282K / 14.4 GB	3779	16
MegaBeam Mistral 7B 300K	282K / 14.4 GB	7968	16
Hebrew Mistral 7B 200K	256K / 30 GB	1316	15
Astral 256K 7B V2	250K / 14.4 GB	10	0
Astral 256K 7B	250K / 14.4 GB	5	0

Note: green Score (e.g. "73.2") means that the model is better than mlabonne/NeuralBeagle14-7B.

Rank the NeuralBeagle14 7B Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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Release v20260328a

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NeuralBeagle14 7B by mlabonne