What are the hardware requirements for Equall Saul Instruct V1?

Equall Saul Instruct V1 requires approximately 5.1 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 Equall Saul Instruct V1 and how large is it?

Equall Saul Instruct V1 is developed by mpesce. 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 Equall Saul Instruct V1?

Equall Saul Instruct V1 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Equall Saul Instruct V1 by mpesce — VRAM 5.1GB, 32K context

Name: Equall Saul Instruct V1
Author: mpesce

Equall Saul Instruct V1 is an open-source language model by mpesce. Features: LLM, VRAM: 5.1GB, Context: 32K, License: mit, Quantized, Instruction-Based, LLM Explorer Score: 0.11.

Endpoints compatible Gguf Instruct Mistral Q5 Quantized Region:us

Model Card on HF 🤗: https://huggingface.co/mpesce/Equall-Saul-Instruct-v1

Equall Saul Instruct V1 Parameters and Internals

LLM Name	Equall Saul Instruct V1
Repository 🤗	https://huggingface.co/mpesce/Equall-Saul-Instruct-v1
Required VRAM	5.1 GB
Updated	2026-08-02
Maintainer	mpesce
Model Type	mistral
Instruction-Based	Yes
Model Files	5.1 GB
GGUF Quantization	Yes
Quantization Type	gguf\|q5\|q5_k
Model Architecture	MistralForCausalLM
License	mit
Context Length	32768
Model Max Length	32768
Transformers Version	4.37.0
Vocabulary Size	32000
Torch Data Type	float32

Rank the Equall Saul Instruct V1 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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...istral Nemo Instruct 2407 GGUF	1000K / 4.8 GB	1139	66
...istral Nemo Instruct 2407 GGUF	1000K / 4.8 GB	1293	11
...istral C64Wizard Instruct GGUF	32K / 4.4 GB	19	0
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...eZephir Sft Instruct Ead 16bit	32K / 14.4 GB	56	0
... Instruct Unsloth Merged 16bit	4K / 7.6 GB	6	1
... Mini 4K Instruct Bnb 4bit Ita	4K / 7.6 GB	1181	0
... Mini 4K Instruct Bnb 4bit Ita	4K / 7.6 GB	1527	0
...ini New Model With Lora Merged	4K / 7.6 GB	16	0
Phired	4K / 7.6 GB	12	0

Note: green Score (e.g. "73.2") means that the model is better than mpesce/Equall-Saul-Instruct-v1.