What are the hardware requirements for Kittylm Minicpm5 2B?

Kittylm Minicpm5 2B requires approximately 0.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Kittylm Minicpm5 2B and how large is it?

Kittylm Minicpm5 2B is developed by KittyLM, a model with 2b 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 Kittylm Minicpm5 2B?

Kittylm Minicpm5 2B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Kittylm Minicpm5 2B by KittyLM — VRAM 0.2GB

Name: Kittylm Minicpm5 2B
Author: KittyLM

Kittylm Minicpm5 2B is an open-source language model by KittyLM. Features: 2b LLM, VRAM: 0.2GB, License: apache-2.0.

Base model:adapter:openbmb/min... Base model:openbmb/minicpm5-2b Conversational Dataset:kittylm/kittylm-data-r... Endpoints compatible Kittylm Llama Lora Persona Region:us Roleplay Safetensors

Model Card on HF 🤗: https://huggingface.co/KittyLM/kittylm-minicpm5-2b

Kittylm Minicpm5 2B Parameters and Internals

LLM Name	Kittylm Minicpm5 2B
Repository 🤗	https://huggingface.co/KittyLM/kittylm-minicpm5-2b
Base Model(s)	MiniCPM5 2B openbmb/MiniCPM5-2B
Model Size	2b
Required VRAM	0.2 GB
Updated	2026-10-05
Maintainer	KittyLM
Model Files	0.2 GB 5.0 GB
Model Architecture	AutoModelForCausalLM
License	apache-2.0
Model Max Length	131072
Is Biased	none
Tokenizer Class	TokenizersBackend
Padding Token	</s>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	q_proj\|up_proj\|gate_proj\|v_proj\|k_proj\|down_proj\|o_proj
LoRA Alpha	32
LoRA Dropout	0.05
R Param	32

Rank the Kittylm Minicpm5 2B 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

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Note: green Score (e.g. "73.2") means that the model is better than KittyLM/kittylm-minicpm5-2b.