What are the hardware requirements for Tinybrainbot 360M A75m V5.1 Base?

Tinybrainbot 360M A75m V5.1 Base requires approximately 0.2 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Tinybrainbot 360M A75m V5.1 Base and how large is it?

Tinybrainbot 360M A75m V5.1 Base is developed by nkthebass, a model with 400b 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 Tinybrainbot 360M A75m V5.1 Base?

Tinybrainbot 360M A75m V5.1 Base is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Tinybrainbot 360M A75m V5.1 Base by nkthebass — VRAM 0.2GB, 2K context

Name: Tinybrainbot 360M A75m V5.1 Base
Author: nkthebass

Tinybrainbot 360M A75m V5.1 Base is an open-source language model by nkthebass. Features: 400b LLM, VRAM: 0.2GB, Context: 2K, License: apache-2.0, Quantized, LLM Explorer Score: 0.34.

Dataset:arrowlabs/dclm-ultra-1... Dataset:axiomiclabs/factbase-d... Dataset:huggingfacefw/finephra... Dataset:huggingfacefw/fineweb-... Dataset:huggingfacetb/cosmoped... Dataset:huggingfacetb/smollm-c... Dataset:karpathy/climbmix-400b... Dataset:microsoft/orca-math-wo... Dataset:nkthebass/tinybrainbot... Dataset:openbmb/ultradata-math Dataset:sentence-transformers/... Dataset:sentence-transformers/... Dataset:wikimedia/wikipedia En Endpoints compatible From-scratch Gguf Mixtral Mixture-of-experts Model-index Moe Q4 Quantized Region:us Safetensors Small-language-model

Model Card on HF 🤗: https://huggingface.co/nkthebass/tinybrainbot-360m-a75m-v5.1-base

Tinybrainbot 360M A75m V5.1 Base Parameters and Internals

LLM Name	Tinybrainbot 360M A75m V5.1 Base
Repository 🤗	https://huggingface.co/nkthebass/tinybrainbot-360m-a75m-v5.1-base
Model Size	400b
Required VRAM	0.2 GB
Updated	2026-11-03
Maintainer	nkthebass
Model Type	mixtral
Model Files	1.5 GB 0.8 GB 0.2 GB 0.4 GB
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf\|q4\|q4_k
Model Architecture	MixtralForCausalLM
License	apache-2.0
Context Length	2048
Model Max Length	2048
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	32000
Torch Data Type	float32

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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

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Mixtral GQA 400M V2	4K / 4.3 GB	169	1
Mixtral GQA 400M V4.4096	4K / 8.1 GB	24	2
Mixtral Smol 400M	4K / 25.1 GB	11	0