What are the hardware requirements for Qwen1.5 MoE A2.7B Wikihow?

Qwen1.5 MoE A2.7B Wikihow requires approximately 28.7 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen1.5 MoE A2.7B Wikihow and how large is it?

Qwen1.5 MoE A2.7B Wikihow is developed by MaziyarPanahi, a model with 14.3b 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 Qwen1.5 MoE A2.7B Wikihow?

Qwen1.5 MoE A2.7B Wikihow is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen1.5 MoE A2.7B Wikihow by MaziyarPanahi — VRAM 28.7GB, 8K context

Name: Qwen1.5 MoE A2.7B Wikihow
Author: MaziyarPanahi

Qwen1.5 MoE A2.7B Wikihow is an open-source language model by MaziyarPanahi. Features: 14.3b LLM, VRAM: 28.7GB, Context: 8K, License: apache-2.0, MoE, LLM Explorer Score: 0.15.

Base model:finetune:qwen/qwen1... Base model:qwen/qwen1.5-moe-a2... Conversational Cosmopedia Dataset:huggingfacetb/cosmoped... Endpoints compatible Finetuned Generated from trainer Moe Qwen Qwen2 moe Region:us Safetensors Sharded Tensorflow Wikihow

Model Card on HF 🤗: https://huggingface.co/MaziyarPanahi/Qwen1.5-MoE-A2.7B-Wikihow

Qwen1.5 MoE A2.7B Wikihow Parameters and Internals

Model Type

text-generation

Additional Notes

Refer to the latest leaderboard evaluation and training config for more in-depth insights.

Training Details

Data Sources:

HuggingFaceTB/cosmopedia

Data Volume:

Not Specified

Methodology:

Fine-tuned

Context Length:

2048

Training Time:

Not Specified

Hardware Used:

multi-GPU

Model Architecture:

Qwen1.5-MoE-A2.7B

Input Output

Input Format:

Not specified

Accepted Modalities:

text

Output Format:

text

Performance Tips:

Gradient checkpointing: enabled, Flash attention: enabled

LLM Name	Qwen1.5 MoE A2.7B Wikihow
Repository 🤗	https://huggingface.co/MaziyarPanahi/Qwen1.5-MoE-A2.7B-Wikihow
Base Model(s)	Qwen/Qwen1.5-MoE-A2.7B Qwen/Qwen1.5-MoE-A2.7B
Model Size	14.3b
Required VRAM	28.7 GB
Updated	2026-07-26
Maintainer	MaziyarPanahi
Model Type	qwen2_moe
Model Files	5.0 GB: 1-of-6 5.0 GB: 2-of-6 5.0 GB: 3-of-6 5.0 GB: 4-of-6 5.0 GB: 5-of-6 3.7 GB: 6-of-6
Model Architecture	Qwen2MoeForCausalLM
License	apache-2.0
Context Length	8192
Model Max Length	8192
Transformers Version	4.40.0.dev0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen1.5 MoE A2.7B Wikihow 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 Qwen1.5 MoE A2.7B Wikihow

Best Alternatives	Context / RAM	Downloads	Likes
Qwen1.5 MoE A2.7B Chat	32K / 28.7 GB	40226	133
Qwen1.5 MoE A2.7B	8K / 28.7 GB	209172	227
...Aux Free Sft Math7k 1e 3 Gamma	8K / 28.7 GB	6	1
Qwen1.5 MoE Sft Math7k	8K / 57.3 GB	5	1
...en1.5 MoE A2.7B Chat GPTQ Int4	32K / 8.4 GB	2155	50

Note: green Score (e.g. "73.2") means that the model is better than MaziyarPanahi/Qwen1.5-MoE-A2.7B-Wikihow.