What are the hardware requirements for MiniCPM4.1 8B?

MiniCPM4.1 8B requires approximately 16.3 GB of VRAM and supports a context window of 64K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed MiniCPM4.1 8B and how large is it?

MiniCPM4.1 8B is developed by openbmb, a model with 8b 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 MiniCPM4.1 8B?

MiniCPM4.1 8B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

MiniCPM4.1 8B by openbmb — VRAM 16.3GB, 64K context

Name: MiniCPM4.1 8B
Author: openbmb

MiniCPM4.1 8B is an open-source language model by openbmb. Features: 8b LLM, VRAM: 16.3GB, Context: 64K, License: apache-2.0, LLM Explorer Score: 0.3.

Arxiv:2506.07900 Arxiv:2509.24663 Conversational Custom code En Minicpm Region:us Safetensors Sharded Tensorflow Zh

Model Card on HF 🤗: https://huggingface.co/openbmb/MiniCPM4.1-8B

MiniCPM4.1 8B Parameters and Internals

LLM Name	MiniCPM4.1 8B
Repository 🤗	https://huggingface.co/openbmb/MiniCPM4.1-8B
Model Size	8b
Required VRAM	16.3 GB
Updated	2026-08-01
Maintainer	openbmb
Model Type	minicpm
Model Files	5.0 GB: 1-of-4 4.5 GB: 2-of-4 4.9 GB: 3-of-4 1.9 GB: 4-of-4
Supported Languages	zh en
Model Architecture	MiniCPMForCausalLM
License	apache-2.0
Context Length	65536
Model Max Length	65536
Transformers Version	4.56.1
Tokenizer Class	LlamaTokenizer
Vocabulary Size	73448
Torch Data Type	bfloat16

Rank the MiniCPM4.1 8B 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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