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

Qwen3.8 27B MLA FP8 requires approximately 29.8 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

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

Qwen3.8 27B MLA FP8 is developed by TelperionAI, 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 MLA FP8?

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

Qwen3.8 27B MLA FP8 by TelperionAI — VRAM 29.8GB

Name: Qwen3.8 27B MLA FP8
Author: TelperionAI

Qwen3.8 27B MLA FP8 is an open-source language model by TelperionAI. Features: 27b LLM, VRAM: 29.8GB, License: apache-2.0, LLM Explorer Score: 0.29.

Base model:quantized:telperion... Base model:telperionai/qwen3.8... Compressed-tensors Conversational Fp8 Kv-cache-compression Long-context Mla Multi-head-latent-attention Qwen3 Qwen3 5 Region:us Safetensors Sharded Tensorflow

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

Qwen3.8 27B MLA FP8 Parameters and Internals

LLM Name	Qwen3.8 27B MLA FP8
Repository 🤗	https://huggingface.co/TelperionAI/Qwen3.8-27B-MLA-FP8
Base Model(s)	TelperionAI/Qwen3.8-27B-MLA TelperionAI/Qwen3.8-27B-MLA
Model Size	27b
Required VRAM	29.8 GB
Updated	2026-10-09
Maintainer	TelperionAI
Model Type	qwen3_5
Model Files	2.5 GB: 1-of-7 5.0 GB: 2-of-7 5.0 GB: 3-of-7 5.0 GB: 4-of-7 5.0 GB: 5-of-7 5.0 GB: 6-of-7 2.3 GB: 7-of-7 0.8 GB 0.9 GB
Model Architecture	Qwen3_5MLAForConditionalGeneration
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 MLA FP8 capabilities

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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

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