What are the hardware requirements for MegaDolphin 120B AWQ?

MegaDolphin 120B AWQ requires approximately 63.3 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed MegaDolphin 120B AWQ and how large is it?

MegaDolphin 120B AWQ is developed by TheBloke, a model with 120b 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 MegaDolphin 120B AWQ?

MegaDolphin 120B AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

MegaDolphin 120B AWQ by TheBloke — VRAM 63.3GB, 4K context

Name: MegaDolphin 120B AWQ
Author: TheBloke

MegaDolphin 120B AWQ is an open-source language model by TheBloke. Features: 120b LLM, VRAM: 63.3GB, Context: 4K, License: llama2, Quantized, Instruction-Based, Merged, LLM Explorer Score: 0.1.

Merged Model 4-bit Awq Base model:quantized:quixiai/m... Base model:quixiai/megadolphin... Conversational Dataset:ehartford/dolphin Dataset:ehartford/samantha-dat... Dataset:ehartford/wizardlm evo... Dataset:jondurbin/airoboros-2.... En Instruct Llama Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/TheBloke/MegaDolphin-120b-AWQ

MegaDolphin 120B AWQ Parameters and Internals

Model Type

llama

LLM Name	MegaDolphin 120B AWQ
Repository 🤗	https://huggingface.co/TheBloke/MegaDolphin-120b-AWQ
Model Name	Megadolphin 120B
Model Creator	Cognitive Computations
Base Model(s)	MegaDolphin 120B cognitivecomputations/MegaDolphin-120b
Merged Model	Yes
Model Size	120b
Required VRAM	63.3 GB
Updated	2026-07-20
Maintainer	TheBloke
Model Type	llama
Instruction-Based	Yes
Model Files	9.9 GB: 1-of-7 9.9 GB: 2-of-7 9.9 GB: 3-of-7 10.0 GB: 4-of-7 9.9 GB: 5-of-7 9.9 GB: 6-of-7 3.8 GB: 7-of-7
Supported Languages	en
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	LlamaForCausalLM
License	llama2
Context Length	4096
Model Max Length	4096
Transformers Version	4.37.0.dev0
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32002
Torch Data Type	float16

Rank the MegaDolphin 120B AWQ 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 MegaDolphin 120B AWQ

Best Alternatives	Context / RAM	Downloads	Likes
...t 120B Cat A Llama EXL2 5.5bpw	8K / 85.3 GB	5	0
...t 120B Cat A Llama EXL2 4.5bpw	8K / 70.3 GB	4	1
...egaDolphin 120B 2.9bpw H6 EXL2	4K / 44.3 GB	2	3
...gaDolphin 120B 2.65bpw H6 EXL2	4K / 40.5 GB	3	2
...egaDolphin 120B 4.0bpw H6 EXL2	4K / 60.8 GB	4	1
...ma 3 Instruct 120B Cat A Llama	8K / 243.9 GB	2	1
Meta Llama 3 225B Instruct	8K / 443.2 GB	274	18
...0B Instruct Abliterated Merged	8K / 243.7 GB	1	1
MegaDolphin 120B GPTQ	4K / 61.1 GB	25	4
Koishi 120B Qlora Gptq	4K / 59.8 GB	4	1

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/MegaDolphin-120b-AWQ.