What are the hardware requirements for Occamy 1.0 GPTQ Int4 W4A16?

Occamy 1.0 GPTQ Int4 W4A16 requires approximately 22.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Occamy 1.0 GPTQ Int4 W4A16 and how large is it?

Occamy 1.0 GPTQ Int4 W4A16 is developed by Krexoz, a model with 35.1b 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 Occamy 1.0 GPTQ Int4 W4A16?

Occamy 1.0 GPTQ Int4 W4A16 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Occamy 1.0 GPTQ Int4 W4A16 by Krexoz — VRAM 22.2GB

Name: Occamy 1.0 GPTQ Int4 W4A16
Author: Krexoz

Occamy 1.0 GPTQ Int4 W4A16 is an open-source language model by Krexoz. Features: 35.1b LLM, VRAM: 22.2GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.28.

Arxiv:2609.11977 4-bit Base model:accio-lab/occamy-1.... Base model:quantized:accio-lab... Battlemage Conversational Endpoints compatible Gptq Image-text-to-text Int4 Intel-arc Moe Quantized Qwen3 5 moe Region:us Safetensors Sharded Tensorflow Vllm W4a16 Xpu

Model Card on HF 🤗: https://huggingface.co/Krexoz/occamy-1.0-GPTQ-Int4-W4A16

Occamy 1.0 GPTQ Int4 W4A16 Parameters and Internals

LLM Name	Occamy 1.0 GPTQ Int4 W4A16
Repository 🤗	https://huggingface.co/Krexoz/occamy-1.0-GPTQ-Int4-W4A16
Base Model(s)	Accio-Lab/occamy-1.0 Accio-Lab/occamy-1.0
Model Size	35.1b
Required VRAM	22.2 GB
Updated	2026-09-19
Maintainer	Krexoz
Model Type	qwen3_5_moe
Model Files	4.0 GB: 1-of-6 4.3 GB: 2-of-6 4.3 GB: 3-of-6 4.3 GB: 4-of-6 4.3 GB: 5-of-6 1.0 GB: 6-of-6
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	Qwen3_5MoeForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Transformers Version	5.15.0
Tokenizer Class	Qwen2TokenizerFast
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Occamy 1.0 GPTQ Int4 W4A16 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 Occamy 1.0 GPTQ Int4 W4A16

Best Alternatives	Context / RAM	Downloads	Likes
Nex N2.5 Mini MLX 8bit	0K / 37.8 GB	156	1
Nex N2.5 Mini MLX 6bit	0K / 28.9 GB	86	1
Nex N2.5 Mini	0K / 70.4 GB	3121	685
Agents A1	0K / 70.6 GB	23272	629
Thomson 1.0 Small	0K / 70.5 GB	214	109
Nex N2 Mini	0K / 70.4 GB	2289	294
Huihui Agents A1 Abliterated	0K / 70.6 GB	3339	29
Occamy 1.0 FP8	0K / 36.8 GB	61	2
Nex N2.5 Mini MLX OQ6	0K / 29.4 GB	158	1
Nex N2.5 Mini FP8 Calibrated	0K / 36.6 GB	40	1

Note: green Score (e.g. "73.2") means that the model is better than Krexoz/occamy-1.0-GPTQ-Int4-W4A16.