What are the hardware requirements for NQLSG Qwen2.5 14B MegaFusion V8.7?

NQLSG Qwen2.5 14B MegaFusion V8.7 requires approximately 29.7 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed NQLSG Qwen2.5 14B MegaFusion V8.7 and how large is it?

NQLSG Qwen2.5 14B MegaFusion V8.7 is developed by Lunzima, a model with 14b 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 NQLSG Qwen2.5 14B MegaFusion V8.7?

NQLSG Qwen2.5 14B MegaFusion V8.7 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

NQLSG Qwen2.5 14B MegaFusion V8.7 by Lunzima — VRAM 29.7GB, 32K context

Name: NQLSG Qwen2.5 14B MegaFusion V8.7
Author: Lunzima

NQLSG Qwen2.5 14B MegaFusion V8.7 is an open-source language model by Lunzima. Features: 14b LLM, VRAM: 29.7GB, Context: 32K, License: apache-2.0, Instruction-Based, Merged, LLM Explorer Score: 0.29.

Merged Model Arxiv:2403.19522 Base model:jpacifico/chocolati... Base model:lunzima/nqlsg-qwen2... Base model:prithivmlmods/equul... Base model:prithivmlmods/messi... Base model:sakalti/saka-14b Base model:sometimesanotion/la... Base model:sometimesanotion/qw... Conversational Endpoints compatible Instruct Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Lunzima/NQLSG-Qwen2.5-14B-MegaFusion-v8.7

NQLSG Qwen2.5 14B MegaFusion V8.7 Parameters and Internals

LLM Name	NQLSG Qwen2.5 14B MegaFusion V8.7
Repository 🤗	https://huggingface.co/Lunzima/NQLSG-Qwen2.5-14B-MegaFusion-v8.7
Base Model(s)	sometimesanotion/Lamarck-14B-v0.7-Fusion Qwenvergence 14B V11 Messier Opus 14B Elite7 jpacifico/Chocolatine-2-14B-Instruct-v2.0b3 Equuleus Opus 14B Exp Saka 14B Lunzima/NQLSG-Qwen2.5-14B-MegaFusion-v8 sometimesanotion/Lamarck-14B-v0.7-Fusion sometimesanotion/Qwenvergence-14B-v11 prithivMLmods/Messier-Opus-14B-Elite7 jpacifico/Chocolatine-2-14B-Instruct-v2.0b3 prithivMLmods/Equuleus-Opus-14B-Exp Sakalti/Saka-14B Lunzima/NQLSG-Qwen2.5-14B-MegaFusion-v8
Merged Model	Yes
Model Size	14b
Required VRAM	29.7 GB
Updated	2026-08-06
Maintainer	Lunzima
Model Type	qwen2
Instruction-Based	Yes
Model Files	4.9 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 4.8 GB: 6-of-6
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.48.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151665
Torch Data Type	bfloat16
Errors	replace

Rank the NQLSG Qwen2.5 14B MegaFusion V8.7 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

Best Alternatives to NQLSG Qwen2.5 14B MegaFusion V8.7

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 14B Instruct 1M	986K / 29.6 GB	10388	342
T3Q Qwen2.5 14B V1.0 E3	986K / 29.7 GB	852	28
ZYH LLM Qwen2.5 14B V4	986K / 29.7 GB	27	8
Qwen2.5 14B 1M YOYO V3	986K / 29.7 GB	254	4
Qwen2.5 14B YOYO V4	986K / 29.7 GB	20	5
Qwen2.5 14B YOYO Latest V2	986K / 29.7 GB	129	0
ZYH LLM Qwen2.5 14B V3	986K / 29.7 GB	23	8
...14B Instruct 1M GRPO Reasoning	986K / 29.7 GB	11	4
Impish QWEN 14B 1M	986K / 29.7 GB	56	26
Q2.5 14B Instruct 1M Harmony	986K / 29.7 GB	3	1

Note: green Score (e.g. "73.2") means that the model is better than Lunzima/NQLSG-Qwen2.5-14B-MegaFusion-v8.7.