What are the hardware requirements for BWork LLM?

BWork LLM requires approximately 0.3 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed BWork LLM and how large is it?

BWork LLM is developed by Dimonomi, a model with 134.5m 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 BWork LLM?

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

BWork LLM by Dimonomi — VRAM 0.3GB, 8K context

Name: BWork LLM
Author: Dimonomi

BWork LLM is an open-source language model by Dimonomi. Features: 134.5m LLM, VRAM: 0.3GB, Context: 8K, License: apache-2.0, LLM Explorer Score: 0.24.

Arxiv:2502.02737 Base model:dimonomi/bwork-llm Base model:quantized:dimonomi/... Conversational En Endpoints compatible Llama Onnx Region:us Safetensors Tensorboard Transformers.js

Model Card on HF 🤗: https://huggingface.co/Dimonomi/BWork-LLM

BWork LLM Parameters and Internals

LLM Name	BWork LLM
Repository 🤗	https://huggingface.co/Dimonomi/BWork-LLM
Base Model(s)	BWork LLM Dimonomi/BWork-LLM
Model Size	134.5m
Required VRAM	0.3 GB
Updated	2026-08-24
Maintainer	Dimonomi
Model Type	llama
Model Files	0.3 GB 0.0 GB
Supported Languages	en
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	8192
Model Max Length	8192
Transformers Version	4.42.3
Tokenizer Class	GPT2Tokenizer
Padding Token	<\|im_end\|>
Vocabulary Size	49152
Torch Data Type	bfloat16

Rank the BWork LLM capabilities

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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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