RRepoGEO

REPOGEO REPORT · LITE

Trans-N-ai/swama

Default branch main · commit 12cfe3f1 · scanned 6/7/2026, 3:46:11 AM

GitHub: 565 stars · 31 forks

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 Trans-N-ai/swama, 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 specific topics to clarify project domain

    Why:

    COPY-PASTE FIX
    llm, inference, macos, apple-silicon, swift, mlx, openai-api, multimodal, local-llm, vlm
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/Trans-N-ai/swama
  • lowreadme#3
    Emphasize LLM/VLM inference earlier in the README's opening sentence

    Why:

    CURRENT
    **Swama** is a high-performance machine learning runtime written in pure Swift, designed specifically for macOS and built on Apple's MLX framework. It provides a powerful and easy-to-use solution for local LLM (Large Language Model) and VLM (Vision Language Model) inference.
    COPY-PASTE FIX
    **Swama** is a high-performance local LLM (Large Language Model) and VLM (Vision Language Model) inference engine, written in pure Swift for macOS and built on Apple's MLX framework. It provides a powerful and easy-to-use solution for running models locally.

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 Trans-N-ai/swama
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Ollama
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Ollama · recommended 2×
  2. LM Studio · recommended 2×
  3. Jan · recommended 2×
  4. llama.cpp · recommended 1×
  5. MLC LLM · recommended 1×
  • CATEGORY QUERY
    What's a good way to run large language models locally on macOS for Apple Silicon?
    you: not recommended
    AI recommended (in order):
    1. Ollama
    2. LM Studio
    3. Jan
    4. llama.cpp
    5. MLC LLM
    6. Hugging Face `transformers`
    7. OpenWebUI

    AI recommended 7 alternatives but never named Trans-N-ai/swama. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    I need an OpenAI API compatible solution for local LLM inference with multimodal capabilities on macOS.
    you: not recommended
    AI recommended (in order):
    1. LM Studio
    2. Ollama
    3. LocalAI
    4. Jan
    5. MLC LLM (mlc-ai/mlc-llm)

    AI recommended 5 alternatives but never named Trans-N-ai/swama. 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 Trans-N-ai/swama?
    pass
    AI named Trans-N-ai/swama explicitly

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

  • If a team adopts Trans-N-ai/swama in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Trans-N-ai/swama 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 Trans-N-ai/swama solve, and who is the primary audience?
    pass
    AI named Trans-N-ai/swama 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 Trans-N-ai/swama. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/Trans-N-ai/swama.svg)](https://repogeo.com/en/r/Trans-N-ai/swama)
HTML
<a href="https://repogeo.com/en/r/Trans-N-ai/swama"><img src="https://repogeo.com/badge/Trans-N-ai/swama.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

Trans-N-ai/swama — 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