RRepoGEO

REPOGEO REPORT · LITE

johnma2006/mamba-minimal

Default branch master · commit 03de542a · scanned 6/26/2026, 7:32:46 PM

GitHub: 2,958 stars · 220 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface johnma2006/mamba-minimal, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    pytorch, mamba, ssm, state-space-models, sequence-modeling, deep-learning, minimal-implementation
  • highreadme#2
    Reposition README H1 to explicitly state the architecture and purpose

    Why:

    CURRENT
    ## mamba-minimal

Simple, minimal implementation of Mamba in one file of PyTorch.
    COPY-PASTE FIX
    ## mamba-minimal: A Minimal PyTorch Implementation of the Mamba State Space Model (SSM)

This repository provides a simple, readable, and minimal implementation of the Mamba architecture, a modern linear-time sequence modeling architecture, in a single PyTorch file.
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/johnma2006/mamba-minimal

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface johnma2006/mamba-minimal
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
state-spaces/s4
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. state-spaces/s4 · recommended 1×
  2. LSSL (Linear State Space Layers) · recommended 1×
  3. Vanilla RNN/LSTM/GRU · recommended 1×
  4. HiPPO (High-order Polynomial Projection Operator) · recommended 1×
  5. huggingface/transformers · recommended 1×
  • CATEGORY QUERY
    Seeking a minimal PyTorch implementation for learning state space sequence model architecture.
    you: not recommended
    AI recommended (in order):
    1. S4 (Structured State Space Sequence Models) (state-spaces/s4)
    2. LSSL (Linear State Space Layers)
    3. Vanilla RNN/LSTM/GRU
    4. HiPPO (High-order Polynomial Projection Operator)

    AI recommended 4 alternatives but never named johnma2006/mamba-minimal. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Are there readable PyTorch examples for modern linear-time sequence modeling architectures?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers Library (huggingface/transformers)
    2. PyTorch Official Examples (pytorch/pytorch)
    3. Annotated Transformer
    4. The Illustrated Transformer
    5. lucidrains

    AI recommended 5 alternatives but never named johnma2006/mamba-minimal. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of johnma2006/mamba-minimal?
    pass
    AI named johnma2006/mamba-minimal explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts johnma2006/mamba-minimal in production, what risks or prerequisites should they evaluate first?
    pass
    AI named johnma2006/mamba-minimal explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo johnma2006/mamba-minimal solve, and who is the primary audience?
    pass
    AI named johnma2006/mamba-minimal explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of johnma2006/mamba-minimal. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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johnma2006/mamba-minimal — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite