What are the hardware requirements for FranQwen3.8 27B NVFP4 DFlash2?

FranQwen3.8 27B NVFP4 DFlash2 requires approximately 20.8 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed FranQwen3.8 27B NVFP4 DFlash2 and how large is it?

FranQwen3.8 27B NVFP4 DFlash2 is developed by TH-44, 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 FranQwen3.8 27B NVFP4 DFlash2?

FranQwen3.8 27B NVFP4 DFlash2 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

FranQwen3.8 27B NVFP4 DFlash2 by TH-44 — VRAM 20.8GB

Name: FranQwen3.8 27B NVFP4 DFlash2
Author: TH-44

FranQwen3.8 27B NVFP4 DFlash2 is an open-source language model by TH-44. Features: 27b LLM, VRAM: 20.8GB, License: apache-2.0, LLM Explorer Score: 0.29.

Abliterated Base model:merge:qwen/qwen3.8-... Base model:qwen/qwen3.8-27b Compressed-tensors Conversational Dflash2 Dgx-spark Image-text-to-text Nvfp4 Qwen3.8 Qwen3 5 Region:us Safetensors Sharded Speculative-decoding Tensorflow Vllm

Model Card on HF 🤗: https://huggingface.co/TH-44/FranQwen3.8-27B-NVFP4-DFlash2

FranQwen3.8 27B NVFP4 DFlash2 Parameters and Internals

LLM Name	FranQwen3.8 27B NVFP4 DFlash2
Repository 🤗	https://huggingface.co/TH-44/FranQwen3.8-27B-NVFP4-DFlash2
Base Model(s)	Qwen/Qwen3.8-27B Qwen/Qwen3.8-27B
Model Size	27b
Required VRAM	20.8 GB
Updated	2026-08-26
Maintainer	TH-44
Model Type	qwen3_5
Model Files	5.0 GB: 1-of-5 5.0 GB: 2-of-5 5.0 GB: 3-of-5 5.0 GB: 4-of-5 1.4 GB: 5-of-5 0.8 GB: 1-of-1 2.5 GB
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Transformers Version	5.15.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Errors	replace

Rank the FranQwen3.8 27B NVFP4 DFlash2 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 FranQwen3.8 27B NVFP4 DFlash2

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.8 27B MLX	0K / 16 GB	1411	18
Qwen3.8 27B FP8	0K / 0.4 GB	123157	416
Qwen3.8 27B	0K / 55.6 GB	2727	21
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 TH-44/FranQwen3.8-27B-NVFP4-DFlash2.