What are the hardware requirements for EuroMoE 2.6B A0.6B 2512?

EuroMoE 2.6B A0.6B 2512 requires approximately 5.2 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 EuroMoE 2.6B A0.6B 2512 and how large is it?

EuroMoE 2.6B A0.6B 2512 is developed by utter-project, a model with 2.6b 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 EuroMoE 2.6B A0.6B 2512?

EuroMoE 2.6B A0.6B 2512 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

EuroMoE 2.6B A0.6B 2512 by utter-project — VRAM 5.2GB, 4K context

Name: EuroMoE 2.6B A0.6B 2512
Author: utter-project

EuroMoE 2.6B A0.6B 2512 is an open-source language model by utter-project. Features: 2.6b LLM, VRAM: 5.2GB, Context: 4K, License: apache-2.0, LLM Explorer Score: 0.19.

Ar Bg Ca Cs Da De El En Endpoints compatible Es Et Fi Fr Ga Gl Hi Hr Hu It Ja Ko Lt Lv Mixtral Mt Nl No Pl Pt Region:us Ro Ru Safetensors Sharded Sk Sl Sv Tensorflow Tr Uk Zh

Model Card on HF 🤗: https://huggingface.co/utter-project/EuroMoE-2.6B-A0.6B-2512

EuroMoE 2.6B A0.6B 2512 Parameters and Internals

LLM Name	EuroMoE 2.6B A0.6B 2512
Repository 🤗	https://huggingface.co/utter-project/EuroMoE-2.6B-A0.6B-2512
Model Size	2.6b
Required VRAM	5.2 GB
Updated	2026-07-16
Maintainer	utter-project
Model Type	mixtral
Model Files	5.0 GB: 1-of-2 0.2 GB: 2-of-2
Supported Languages	en de es fr it pt pl nl tr sv cs el hu ro fi uk sl sk da lt lv et bg no ca hr ga mt gl zh ru ko ja ar hi
Model Architecture	MixtralForCausalLM
License	apache-2.0
Context Length	4096
Model Max Length	4096
Transformers Version	4.47.1
Tokenizer Class	LlamaTokenizer
Vocabulary Size	128000
Torch Data Type	bfloat16

Rank the EuroMoE 2.6B A0.6B 2512 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 EuroMoE 2.6B A0.6B 2512

Best Alternatives	Context / RAM	Downloads	Likes
TinyExperts V0 4x1B	32K / 5.2 GB	1298	0
...oE 2.6B A0.6B Instruct Preview	4K / 5.2 GB	1764	11
Aquif 3.5 A0.6B Preview	4K / 5.2 GB	17	0
TinyEnsemble 3x1.1B TinyMoE	4K / 5.3 GB	6	0
...x MoE Samantha Chatml Therabot	4K / 5.2 GB	11	1
...Oasst2 ChatML Cluster 3 2 1 V1	4K / 5.2 GB	6	3
LiteLlamix 8x460M 1T	1K / 5.2 GB	9	4

Note: green Score (e.g. "73.2") means that the model is better than utter-project/EuroMoE-2.6B-A0.6B-2512.