What are the hardware requirements for Mamba 130M Hf?

Mamba 130M Hf requires approximately 0.5 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Mamba 130M Hf and how large is it?

Mamba 130M Hf is developed by state-spaces, a model with 130m 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 Mamba 130M Hf?

Mamba 130M Hf is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mamba 130M Hf by state-spaces — VRAM 0.5GB

Name: Mamba 130M Hf
Author: state-spaces

Mamba 130M Hf is an open-source language model by state-spaces. Features: 130m LLM, VRAM: 0.5GB, LLM Explorer Score: 0.21.

Deploy:azure Endpoints compatible Mamba Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/state-spaces/mamba-130m-hf

Mamba 130M Hf Parameters and Internals

Model Type

causal language model, transformer

Additional Notes

The Mamba model is compatible with the 'transformers' library and uses a specialized configuration and tokenizer. The 'peft' library can be used for finetuning.

Input Output

Input Format:

Text input encoded as token IDs

Accepted Modalities:

text

Output Format:

Text output

Performance Tips:

Use 'causal_conv_1d' and 'mamba-ssm' for optimized CUDA kernel performance.

LLM Name	Mamba 130M Hf
Repository 🤗	https://huggingface.co/state-spaces/mamba-130m-hf
Model Size	130m
Required VRAM	0.5 GB
Updated	2026-05-29
Maintainer	state-spaces
Model Type	mamba
Model Files	0.5 GB
Model Architecture	MambaForCausalLM
Transformers Version	4.39.0.dev0
Tokenizer Class	GPTNeoXTokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	50280
Torch Data Type	float32

Rank the Mamba 130M Hf 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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