What are the hardware requirements for Swift 1.5 Qwen3.8 27B Heretic MXFP4 GPTQ?

Swift 1.5 Qwen3.8 27B Heretic MXFP4 GPTQ requires approximately 19 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Swift 1.5 Qwen3.8 27B Heretic MXFP4 GPTQ and how large is it?

Swift 1.5 Qwen3.8 27B Heretic MXFP4 GPTQ is developed by slybase, a model with 27b 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 Swift 1.5 Qwen3.8 27B Heretic MXFP4 GPTQ?

Swift 1.5 Qwen3.8 27B Heretic MXFP4 GPTQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Swift 1.5 Qwen3.8 27B Heretic MXFP4 GPTQ by slybase — VRAM 19GB

Name: Swift 1.5 Qwen3.8 27B Heretic MXFP4 GPTQ
Author: slybase

Swift 1.5 Qwen3.8 27B Heretic MXFP4 GPTQ is an open-source language model by slybase. Features: 27b LLM, VRAM: 19GB, License: other, Quantized, LLM Explorer Score: 0.29.

8-bit Abliterated Base model:akumaburn/swift-1.5... Base model:quantized:akumaburn... Compressed-tensors Conversational Endpoints compatible Gfx1201 Gptq Heretic Image-text-to-text Llm-compressor Mxfp4 Quantized Qwen3.8 Qwen3 5 Region:us Research-only Rocm Safetensors Sharded Swift-1.5 Tensorflow Uncensored

Model Card on HF 🤗: https://huggingface.co/slybase/Swift-1.5-Qwen3.8-27B-heretic-MXFP4-GPTQ

Swift 1.5 Qwen3.8 27B Heretic MXFP4 GPTQ Parameters and Internals

LLM Name	Swift 1.5 Qwen3.8 27B Heretic MXFP4 GPTQ
Repository 🤗	https://huggingface.co/slybase/Swift-1.5-Qwen3.8-27B-heretic-MXFP4-GPTQ
Base Model(s)	akumaburn/Swift-1.5-Qwen3.8-27b-heretic akumaburn/Swift-1.5-Qwen3.8-27b-heretic
Model Size	27b
Required VRAM	19 GB
Updated	2026-10-12
Maintainer	slybase
Model Type	qwen3_5
Model Files	2.5 GB: 1-of-9 2.0 GB: 2-of-9 2.0 GB: 3-of-9 2.0 GB: 4-of-9 2.0 GB: 5-of-9 2.0 GB: 6-of-9 2.0 GB: 7-of-9 2.5 GB: 8-of-9 2.0 GB: 9-of-9 0.8 GB
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	Qwen3_5ForConditionalGeneration
License	other
Model Max Length	262144
Transformers Version	5.6.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Swift 1.5 Qwen3.8 27B Heretic MXFP4 GPTQ 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 Swift 1.5 Qwen3.8 27B Heretic MXFP4 GPTQ

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.6 27B GPTQ Pro 4bit	0K / 18.8 GB	415407	39
Qwen3.5 27B GPTQ Int4	0K / 30.1 GB	105381	57
Qwen3.8 27B GPTQ INT4 FP8KV	0K / 20.2 GB	6488	2
...en3.8 27B W4A16 AutoRound GPTQ	0K / 19.2 GB	3748	5
Qwen3.8 27B GPTQ 4bit	0K / 21 GB	2433	5
Qwen3.8 27B GPTQ Int4	0K / 20.2 GB	2267	3
... 27B Abliterated GPTQ Int4 MTP	0K / 19.6 GB	103	1
...7B GPTQ Int4 Sym G128 MTP BF16	0K / 19.6 GB	175	3
Qwen3.8 27B GPTQ Int4	0K / 19.6 GB	881	1
... GPTQ Int4 Baked V1 Embed Int8	0K / 16.2 GB	39	4

Note: green Score (e.g. "73.2") means that the model is better than slybase/Swift-1.5-Qwen3.8-27B-heretic-MXFP4-GPTQ.