What are the hardware requirements for Qwen3.8 27B FP8 KVcal?

Qwen3.8 27B FP8 KVcal requires approximately 0.4 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.8 27B FP8 KVcal and how large is it?

Qwen3.8 27B FP8 KVcal is developed by stoyani, 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 FP8 KVcal?

Qwen3.8 27B FP8 KVcal is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3.8 27B FP8 KVcal by stoyani — VRAM 0.4GB

Name: Qwen3.8 27B FP8 KVcal
Author: stoyani

Qwen3.8 27B FP8 KVcal is an open-source language model by stoyani. Features: 27b LLM, VRAM: 0.4GB, License: apache-2.0, LLM Explorer Score: 0.28.

Arxiv:2404.06654 Base model:quantized:qwen/qwen... Base model:qwen/qwen3.8-27b-fp... Calibration Conversational Endpoints compatible Fp8 Image-text-to-text Kv-cache Qwen3 Qwen3 5 Region:us Safetensors Vllm

Model Card on HF 🤗: https://huggingface.co/stoyani/Qwen3.8-27B-FP8-KVcal

Qwen3.8 27B FP8 KVcal Parameters and Internals

LLM Name	Qwen3.8 27B FP8 KVcal
Repository 🤗	https://huggingface.co/stoyani/Qwen3.8-27B-FP8-KVcal
Base Model(s)	Qwen/Qwen3.8-27B-FP8 Qwen/Qwen3.8-27B-FP8
Model Size	27b
Required VRAM	0.4 GB
Updated	2026-09-26
Maintainer	stoyani
Model Type	qwen3_5
Model Files	0.0 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB 0.4 GB
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Transformers Version	5.8.0.dev0

Rank the Qwen3.8 27B FP8 KVcal 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 FP8 KVcal

Best Alternatives	Context / RAM	Downloads	Likes
...wopus3.8 27B Flash Mlx OQ4e 1M	1024K / 16.9 GB	211	1
Agens Pilot	1024K / 54.7 GB	172	1
Qwen3.6 27B	0K / 55.4 GB	6728138	2197
Qwen3.8 27B	0K / 55.6 GB	2	8753
Qwen3.8 27B FP8	0K / 0.4 GB	123157	416
Qwen3.8 27B	0K / 55.6 GB	2727	21
Qwen3.8 27B MLX	0K / 16 GB	1411	18
Qwen3.6 27B NVFP4	0K / 22 GB	1887525	419
Qwen3.5 27B	0K / 55.2 GB	2536294	1028
Qwen3.6 27B FP8	0K / 0.4 GB	7740472	342

Note: green Score (e.g. "73.2") means that the model is better than stoyani/Qwen3.8-27B-FP8-KVcal.