What are the hardware requirements for Qwen3.8 27B OBLITERATED NVFP4?

Qwen3.8 27B OBLITERATED NVFP4 requires approximately 1.8 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.8 27B OBLITERATED NVFP4 and how large is it?

Qwen3.8 27B OBLITERATED NVFP4 is developed by Joestar79, 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 Qwen3.8 27B OBLITERATED NVFP4?

Qwen3.8 27B OBLITERATED NVFP4 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3.8 27B OBLITERATED NVFP4 by Joestar79 — VRAM 1.8GB

Name: Qwen3.8 27B OBLITERATED NVFP4
Author: Joestar79

Qwen3.8 27B OBLITERATED NVFP4 is an open-source language model by Joestar79. Features: 27b LLM, VRAM: 1.8GB, License: apache-2.0, LLM Explorer Score: 0.33.

8-bit Abliterated Base model:obliteratus/qwen3.8... Base model:quantized:obliterat... Blackwell Conversational Image-text-to-text Modelopt Mtp Nvfp4 Quantization Qwen3 5 Region:us Rtx-5090 Safetensors Speculative-decoding Uncensored Vllm

Model Card on HF 🤗: https://huggingface.co/Joestar79/Qwen3.8-27B-OBLITERATED-NVFP4

Qwen3.8 27B OBLITERATED NVFP4 Parameters and Internals

LLM Name	Qwen3.8 27B OBLITERATED NVFP4
Repository 🤗	https://huggingface.co/Joestar79/Qwen3.8-27B-OBLITERATED-NVFP4
Base Model(s)	OBLITERATUS/Qwen3.8-27B-OBLITERATED Qwen/Qwen3.8-27B OBLITERATUS/Qwen3.8-27B-OBLITERATED Qwen/Qwen3.8-27B
Model Size	27b
Required VRAM	1.8 GB
Updated	2026-08-27
Maintainer	Joestar79
Model Type	qwen3_5
Model Files	19.7 GB 1.8 GB
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Transformers Version	5.8.0.dev0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Qwen3.8 27B OBLITERATED NVFP4 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 Qwen3.8 27B OBLITERATED NVFP4

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.8 27B MLX	0K / 16 GB	1411	18
Qwen3.8 27B	0K / 55.6 GB	2727	21
Qwen3.8 27B FP8	0K / 0.4 GB	123157	416
Qwen3.6 27B	0K / 55.4 GB	6728138	2197
Qwen3.8 27B	0K / 55.6 GB	2	8753
Qwen3.6 27B NVFP4	0K / 22 GB	1887525	419
Qwen3.6 27B FP8	0K / 0.4 GB	7740472	342
ThinkingCap Qwen3.6 27B	0K / 54.7 GB	35947	614
Qwen3.5 27B	0K / 55.2 GB	2536294	1028
Qwen3.5 27B	0K / 55.2 GB	8115	16

Note: green Score (e.g. "73.2") means that the model is better than Joestar79/Qwen3.8-27B-OBLITERATED-NVFP4.