What are the hardware requirements for Peagle 9B?

Peagle 9B requires approximately 18 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 Peagle 9B and how large is it?

Peagle 9B is developed by eldogbbhed, a model with 9b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Peagle 9B perform on standard benchmarks?

Peagle 9B has the following published scores: MMLU 64.36. Compare against reference models on this page or on the LLM Explorer leaderboards.

Peagle 9B by eldogbbhed — VRAM 18GB, 32K context

Name: Peagle 9B
Author: eldogbbhed

Peagle 9B is an open-source language model by eldogbbhed. Features: 9b LLM, VRAM: 18GB, Context: 32K, License: cc-by-nc-4.0, Merged, LLM Explorer Score: 0.16, Arc: 71.5, HellaSwag: 87.3, MMLU: 64.4, GSM8K: 66.1.

Merged Model Autotrain compatible Conversational Eldogbbhed/neuralpearlbeagle Endpoints compatible Mistral Mlabonne/neuralbeagle14-7b Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/eldogbbhed/Peagle-9b

Peagle 9B Parameters and Internals

LLM Name	Peagle 9B
Repository 🤗	https://huggingface.co/eldogbbhed/Peagle-9b
Merged Model	Yes
Model Size	9b
Required VRAM	18 GB
Updated	2025-09-29
Maintainer	eldogbbhed
Model Type	mistral
Model Files	2.0 GB: 1-of-10 1.9 GB: 2-of-10 2.0 GB: 3-of-10 1.9 GB: 4-of-10 2.0 GB: 5-of-10 2.0 GB: 6-of-10 1.9 GB: 7-of-10 2.0 GB: 8-of-10 1.9 GB: 9-of-10 0.4 GB: 10-of-10
Model Architecture	MistralForCausalLM
License	cc-by-nc-4.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.39.0.dev0
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32000
Torch Data Type	float16

Rank the Peagle 9B 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

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