# MzeroMiko/VMamba

VMamba: Visual State Space Models，code is based on mamba

Repository: https://github.com/MzeroMiko/VMamba
Canonical: https://ross.abutalabs.com/products/vmamba
Language: Python
License: MIT
License Family: permissive
Last push: 2025-03-07T15:14:15+00:00

## Health v2 (maintenance only)
Score: 21/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 10, release rhythm 8, longevity 68
- inputs: {"age_days": 965, "days_push": 544, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3219, forks 237 (observed 2026-08-28T04:07:49.701955+00:00)

## What it is
VMamba is a PyTorch implementation of a visual state space model (SSM) vision backbone based on Mamba, featuring 2D Selective Scan (SS2D) for linear-complexity image feature extraction. It provides pretrained model weights and a single-file implementation for easy use in downstream vision tasks.

## Use cases
- build image classification models with linear-complexity backbones
- use state space models for computer vision tasks
- replace ViT or CNN backbones with Mamba-based vision models
- run object detection or segmentation with a VMamba backbone
- experiment with 2D selective scan architectures

## When to choose
- you need an efficient vision backbone with linear time complexity
- you want to experiment with state space models in vision
- you need pretrained weights for downstream vision tasks

## When to avoid
- you need a battle-tested production backbone with broad ecosystem support
- you lack a CUDA-capable GPU since mamba_ssm requires GPU kernels
- you only need standard CNN or transformer architectures

## Facets
- artifact type: library
- maturity: active
- function: machine-learning, deep-learning
- domain: computer-vision, deep-learning, machine-learning
- platform: python
- tags: state-space-models, vision-backbone, mamba, image-classification, neural-architecture, linux, gpu

## Member repositories
- MzeroMiko/VMamba (main) score 21

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:49.701955+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:44:28.609981+00:00, confidence not recorded.
  - readme: https://github.com/MzeroMiko/VMamba (fetched 2026-08-28T04:07:49.701955+00:00, sha 94d3bced33ed)
- Data as of 2026-08-30T08:39:29.467469+00:00.