What are the hardware requirements for TinyEnsemble 3x1.1B TinyMoE?

TinyEnsemble 3x1.1B TinyMoE requires approximately 5.3 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 TinyEnsemble 3x1.1B TinyMoE and how large is it?

TinyEnsemble 3x1.1B TinyMoE is developed by JoPmt, 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 TinyEnsemble 3x1.1B TinyMoE?

TinyEnsemble 3x1.1B TinyMoE is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

TinyEnsemble 3x1.1B TinyMoE by JoPmt — VRAM 5.3GB, 4K context

Name: TinyEnsemble 3x1.1B TinyMoE
Author: JoPmt

TinyEnsemble 3x1.1B TinyMoE is an open-source language model by JoPmt. Features: 2.6b LLM, VRAM: 5.3GB, Context: 4K, License: apache-2.0, MoE, LLM Explorer Score: 0.13.

78health/tinyllama 1.1b-functi... Base model:daertml/tinygauss-1... Base model:merge:daertml/tinyg... Base model:merge:quixiai/tinyd... Base model:quixiai/tinydolphin... Cognitivecomputations/tinydolp... Daertml/tinygauss-1.1b Endpoints compatible Frankenmoe Lazymergekit Merge Mergekit Mixtral Moe Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/JoPmt/TinyEnsemble-3x1.1B-TinyMoE

TinyEnsemble 3x1.1B TinyMoE Parameters and Internals

Model Type

Mixture of Experts (MoE)

Additional Notes

The model is built using LazyMergekit technology, combining three different models. It employs positive prompts for routing inputs to the appropriate expert model within the ensemble.

LLM Name	TinyEnsemble 3x1.1B TinyMoE
Repository 🤗	https://huggingface.co/JoPmt/TinyEnsemble-3x1.1B-TinyMoE
Base Model(s)	cognitivecomputations/TinyDolphin-2.8-1.1b 78health/TinyLlama_1.1B-function-calling DaertML/TinyGauss-1.1B cognitivecomputations/TinyDolphin-2.8-1.1b 78health/TinyLlama_1.1B-function-calling DaertML/TinyGauss-1.1B
Model Size	2.6b
Required VRAM	5.3 GB
Updated	2026-07-15
Maintainer	JoPmt
Model Type	mixtral
Model Files	1.0 GB: 1-of-6 1.0 GB: 2-of-6 1.0 GB: 3-of-6 1.0 GB: 4-of-6 1.0 GB: 5-of-6 0.3 GB: 6-of-6
Model Architecture	MixtralForCausalLM
License	apache-2.0
Context Length	4096
Model Max Length	4096
Transformers Version	4.41.2
Tokenizer Class	LlamaTokenizer
Padding Token	<s>
Vocabulary Size	32002
Torch Data Type	bfloat16

Rank the TinyEnsemble 3x1.1B TinyMoE 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 TinyEnsemble 3x1.1B TinyMoE

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
EuroMoE 2.6B A0.6B 2512	4K / 5.2 GB	139	11
...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 JoPmt/TinyEnsemble-3x1.1B-TinyMoE.