What are the hardware requirements for Megatron V3 2x7B?

Megatron V3 2x7B requires approximately 25.8 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 Megatron V3 2x7B and how large is it?

Megatron V3 2x7B is developed by Eurdem, a model with 12.9b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Megatron V3 2x7B perform on standard benchmarks?

Megatron V3 2x7B has the following published scores: MMLU 61.53. Compare against reference models on this page or on the LLM Explorer leaderboards.

Megatron V3 2x7B by Eurdem — VRAM 25.8GB, 32K context

Name: Megatron V3 2x7B
Author: Eurdem

Megatron V3 2x7B is an open-source language model by Eurdem. Features: 12.9b LLM, VRAM: 25.8GB, Context: 32K, License: apache-2.0, MoE, Instruction-Based, LLM Explorer Score: 0.13, Arc: 66.4, HellaSwag: 83.7, MMLU: 61.5, GSM8K: 46.2.

Conversational En Endpoints compatible Instruct Merge Mixtral Moe Region:us Safetensors Sharded Tensorflow Tr

Model Card on HF 🤗: https://huggingface.co/Eurdem/megatron_v3_2x7B

Megatron V3 2x7B Parameters and Internals

Model Type

Mixture of Experts (MoE), bilingual, text generation

Use Cases

Areas:

general language understanding, multilingual applications

Primary Use Cases:

comprehending and responding to English/Turkish instructions

Additional Notes

Model uses mixture of experts (MoE) architecture for improved performance.

Supported Languages

en (Supported), tr (Supported)

Input Output

Accepted Modalities:

text

LLM Name	Megatron V3 2x7B
Repository 🤗	https://huggingface.co/Eurdem/megatron_v3_2x7B
Model Size	12.9b
Required VRAM	25.8 GB
Updated	2026-07-14
Maintainer	Eurdem
Model Type	mixtral
Instruction-Based	Yes
Model Files	9.9 GB: 1-of-3 10.0 GB: 2-of-3 5.9 GB: 3-of-3
Supported Languages	en tr
Model Architecture	MixtralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.39.1
Tokenizer Class	LlamaTokenizer
Padding Token	<s>
Vocabulary Size	32000
Torch Data Type	float16

Rank the Megatron V3 2x7B 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 Megatron V3 2x7B

Best Alternatives	Context / RAM	Downloads	Likes
Inf Silent Kunoichi V0.1 2x7B	32K / 25.6 GB	8	0
Inf Silent Kunoichi V0.2 2x7B	32K / 25.6 GB	9	1
NearalMistral 2x7B	32K / 25.8 GB	50	1
MistarlingMaid 2x7B Base	32K / 25.8 GB	52	0
MergedExpert 2x8b	32K / 25.8 GB	5	0
MergedExperts 2x8b	32K / 25.8 GB	6	0
...afted Hermetic Platypus C 2x7B	32K / 25.8 GB	49	0
...tral 7B Instruct V0.2 2x7B MoE	32K / 25.8 GB	1131	4
...tral Instruct MoE Experimental	32K / 25.8 GB	56	2
Mistral 2x7b V0.1	32K / 25.8 GB	6	1

Note: green Score (e.g. "73.2") means that the model is better than Eurdem/megatron_v3_2x7B.