What are the hardware requirements for WPAIGPT Fse Patterns 1?

WPAIGPT Fse Patterns 1 requires approximately 65.8 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 WPAIGPT Fse Patterns 1 and how large is it?

WPAIGPT Fse Patterns 1 is developed by WPAI-INC, a model with 32b 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 WPAIGPT Fse Patterns 1?

WPAIGPT Fse Patterns 1 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

WPAIGPT Fse Patterns 1 by WPAI-INC — VRAM 65.8GB, 32K context

Name: WPAIGPT Fse Patterns 1
Author: WPAI-INC

WPAIGPT Fse Patterns 1 is an open-source language model by WPAI-INC. Features: 32b LLM, VRAM: 65.8GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.15.

4bit Base model:quantized:qwen/qwen... Base model:qwen/qwen2.5-32b-in... Code Conversational Dataset:wpai-inc/wp-pattern-in... En Endpoints compatible Gguf Instruct Q4 Quantized Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/WPAI-INC/WPAIGPT-fse-patterns-1

WPAIGPT Fse Patterns 1 Parameters and Internals

LLM Name	WPAIGPT Fse Patterns 1
Repository 🤗	https://huggingface.co/WPAI-INC/WPAIGPT-fse-patterns-1
Base Model(s)	Qwen/Qwen2.5-32B-Instruct Qwen/Qwen2.5-32B-Instruct
Model Size	32b
Required VRAM	65.8 GB
Updated	2026-07-27
Maintainer	WPAI-INC
Model Type	qwen2
Instruction-Based	Yes
Model Files	19.9 GB 18.4 GB 34.8 GB 4.9 GB: 1-of-14 4.9 GB: 2-of-14 4.9 GB: 3-of-14 4.9 GB: 4-of-14 4.9 GB: 5-of-14 4.9 GB: 6-of-14 4.9 GB: 7-of-14 4.9 GB: 8-of-14 4.9 GB: 9-of-14 4.9 GB: 10-of-14 4.9 GB: 11-of-14 4.9 GB: 12-of-14 4.9 GB: 13-of-14 2.1 GB: 14-of-14
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	q4\|4bit\|gguf\|q4_k\|q5_k
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.44.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|PAD_TOKEN\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the WPAIGPT Fse Patterns 1 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 WPAIGPT Fse Patterns 1

Best Alternatives	Context / RAM	Downloads	Likes
EVA Instruct 32B EXL2 4.0	128K / 17.7 GB	4	3
....5 Coder 32B Instruct Bnb 4bit	32K / 19.2 GB	5519	6
...wen2.5 Coder 32B Instruct 3bit	32K / 14.3 GB	144	4
Qwen 32B Incorrect Trivia 2	32K / 65.8 GB	12	0
Qwen2.5 32B Instruct Bnb 4bit	32K / 19.2 GB	49427	15
...wen2.5 Coder 32B Instruct 4bit	32K / 18.5 GB	2357	12
Cogito R1	32K / 65.8 GB	8	5
...wen2.5 Coder 32B Instruct 8bit	32K / 34.9 GB	934	14
Qwen2.5 32B Instruct 4bit	32K / 18.5 GB	1502	4
Qwen2.5 32B Instruct 8bit	32K / 34.9 GB	979	7

Note: green Score (e.g. "73.2") means that the model is better than WPAI-INC/WPAIGPT-fse-patterns-1.