What are the hardware requirements for Limbic Tool Use 0.5B 32K?

Limbic Tool Use 0.5B 32K requires approximately 1 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Limbic Tool Use 0.5B 32K and how large is it?

Limbic Tool Use 0.5B 32K is developed by quotientai, a model with 0.5b 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 Limbic Tool Use 0.5B 32K?

Limbic Tool Use 0.5B 32K is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Limbic Tool Use 0.5B 32K by quotientai — VRAM 1GB, 32K context

Name: Limbic Tool Use 0.5B 32K
Author: quotientai

Limbic Tool Use 0.5B 32K is an open-source language model by quotientai. Features: 0.5b LLM, VRAM: 1GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.19.

Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-0.5b-i... Conversational Dataset:quotientai/limbic-eval... En Endpoints compatible Instruct Qwen2 Region:us Safetensors Unsloth

Model Card on HF 🤗: https://huggingface.co/quotientai/limbic-tool-use-0.5B-32K

Limbic Tool Use 0.5B 32K Parameters and Internals

LLM Name	Limbic Tool Use 0.5B 32K
Repository 🤗	https://huggingface.co/quotientai/limbic-tool-use-0.5B-32K
Base Model(s)	Qwen/Qwen2.5-0.5B-Instruct Qwen/Qwen2.5-0.5B-Instruct
Model Size	0.5b
Required VRAM	1 GB
Updated	2026-04-21
Maintainer	quotientai
Model Type	qwen2
Instruction-Based	Yes
Model Files	1.0 GB
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.53.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Limbic Tool Use 0.5B 32K 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

Best Alternatives to Limbic Tool Use 0.5B 32K

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2 0.5B Abyme Merge3	128K / 1.3 GB	18	1
Qwen2 0.5B Abyme Merge2	128K / 0.3 GB	13	0
Qwen2.5 0.5B Instruct	64K / 1 GB	16	0
Rifa Nano 0.5B	32K / 1 GB	703	0
Qwen2.5 0.5B Instruct	32K / 1 GB	6324790	572
Pulsar AI Final	32K / 1 GB	185	2
Chichu 2.0 500M Instruct	32K / 1 GB	212	2
Sakthai Context 0.5B Tools	32K / 1 GB	474	0
Qwen R1 0.5B	32K / 1 GB	202	2
Veda Labs 0.5B Instruct Base	32K / 1 GB	30	2

Note: green Score (e.g. "73.2") means that the model is better than quotientai/limbic-tool-use-0.5B-32K.