What are the hardware requirements for NQLSG Qwen2.5 14B MegaFusion V9.3 Coder?

NQLSG Qwen2.5 14B MegaFusion V9.3 Coder 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 V9.3 Coder and how large is it?

NQLSG Qwen2.5 14B MegaFusion V9.3 Coder 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 V9.3 Coder?

NQLSG Qwen2.5 14B MegaFusion V9.3 Coder 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 V9.3 Coder by Lunzima — VRAM 29.7GB, 32K context

Name: NQLSG Qwen2.5 14B MegaFusion V9.3 Coder
Author: Lunzima

NQLSG Qwen2.5 14B MegaFusion V9.3 Coder is an open-source language model by Lunzima. Features: 14b LLM, VRAM: 29.7GB, Context: 32K, Code Generating, Merged, LLM Explorer Score: 0.17.

Merged Model Arxiv:2403.19522 Base model:lunzima/nqlsg-qwen2... Codegen Conversational Dataset:lunzima/c cpp coder Endpoints compatible Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Lunzima/NQLSG-Qwen2.5-14B-MegaFusion-v9.3-Coder

NQLSG Qwen2.5 14B MegaFusion V9.3 Coder Parameters and Internals

LLM Name	NQLSG Qwen2.5 14B MegaFusion V9.3 Coder
Repository 🤗	https://huggingface.co/Lunzima/NQLSG-Qwen2.5-14B-MegaFusion-v9.3-Coder
Base Model(s)	Lunzima/NQLSG-Qwen2.5-14B-MegaFusion-v9.3 Lunzima/NQLSG-Qwen2.5-14B-MegaFusion-v9.3-coder-convos-2 Lunzima/NQLSG-Qwen2.5-14B-MegaFusion-v9.3 Lunzima/NQLSG-Qwen2.5-14B-MegaFusion-v9.3 Lunzima/NQLSG-Qwen2.5-14B-MegaFusion-v9.3-coder-convos-1 Lunzima/NQLSG-Qwen2.5-14B-MegaFusion-v9.3 Lunzima/NQLSG-Qwen2.5-14B-MegaFusion-v9.3-coder-convos-2 Lunzima/NQLSG-Qwen2.5-14B-MegaFusion-v9.3 Lunzima/NQLSG-Qwen2.5-14B-MegaFusion-v9.3 Lunzima/NQLSG-Qwen2.5-14B-MegaFusion-v9.3-coder-convos-1
Merged Model	Yes
Model Size	14b
Required VRAM	29.7 GB
Updated	2026-07-25
Maintainer	Lunzima
Model Type	qwen2
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
Generates Code	Yes
Model Architecture	Qwen2ForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.49.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151665
Torch Data Type	bfloat16
Errors	replace

Rank the NQLSG Qwen2.5 14B MegaFusion V9.3 Coder 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 V9.3 Coder

Best Alternatives	Context / RAM	Downloads	Likes
...hts Qwen2.5 14B Coder Creative	986K / 29.3 GB	267	0
ZYH LLM Qwen2.5 14B V4	986K / 29.7 GB	27	8
Qwen2.5 14B YOYO V4	986K / 29.7 GB	20	5
ZYH LLM Qwen2.5 14B V2	986K / 29.7 GB	14	1
ZYH LLM Qwen2.5 14B V5	986K / 29.7 GB	12	8
Qwen2.5 14B YOYO V5	986K / 29.7 GB	10	4
Mergekit Model Stock Ggfjmyf	986K / 29.7 GB	14	0
Mergekit Model Stock Injkqri	986K / 29.7 GB	5	1
Primal Opus 14B Optimus V2	128K / 29.7 GB	12	4
Qwen2.5 14B ReasoningMerge	128K / 29.7 GB	24	3

Note: green Score (e.g. "73.2") means that the model is better than Lunzima/NQLSG-Qwen2.5-14B-MegaFusion-v9.3-Coder.