What are the hardware requirements for Tennda Nano?

Tennda Nano requires approximately 9.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Tennda Nano and how large is it?

Tennda Nano is developed by MLA299, a model with 4.6b 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 Tennda Nano?

Tennda Nano is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Tennda Nano by MLA299 — VRAM 9.2GB

Name: Tennda Nano
Author: MLA299

Tennda Nano is an open-source language model by MLA299. Features: 4.6b LLM, VRAM: 9.2GB, License: other.

Code Conversational Gemma4 Mlx Region:us Safetensors Sharded Sql Tennda Tensorflow

Model Card on HF 🤗: https://huggingface.co/MLA299/Tennda-Nano

Tennda Nano Parameters and Internals

LLM Name	Tennda Nano
Repository 🤗	https://huggingface.co/MLA299/Tennda-Nano
Model Size	4.6b
Required VRAM	9.2 GB
Updated	2026-08-23
Maintainer	MLA299
Model Type	gemma4
Model Files	4.5 GB: 1-of-2 4.7 GB: 2-of-2
Model Architecture	Gemma4ForConditionalGeneration
License	other
Transformers Version	5.5.0.dev0
Tokenizer Class	GemmaTokenizer
Padding Token	<pad>

Rank the Tennda Nano 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 Tennda Nano

Best Alternatives	Context / RAM	Downloads	Likes
Gemma 4 E2B It NVFP4	0K / 5.5 GB	5388	8

Note: green Score (e.g. "73.2") means that the model is better than MLA299/Tennda-Nano.