REPOGEO REPORT · LITE

argmaxinc/argmax-oss-swift

Default branch main · commit 984ab42f · scanned 5/20/2026, 11:52:06 AM

GitHub: 6,134 stars · 560 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)

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

AI VISIBILITY SCORE

28 /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

2 / 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 argmaxinc/argmax-oss-swift, 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

highreadme#1

Clarify the open-source SDK's role as a standalone on-device solution

Why:

CURRENT

Argmax Open-Source SDK Swift is a collection of turn-key on-device inference frameworks: WhisperKit for speech-to-text with OpenAI Whisper, SpeakerKit for speaker diarization Pyannote, TTSKit for text-to-speech with Qwen-TTS

COPY-PASTE FIX

The Argmax Open-Source SDK Swift provides turn-key, *standalone* on-device inference frameworks for Apple platforms, including WhisperKit (speech-to-text), SpeakerKit (speaker diarization), and TTSKit (text-to-speech). *Unlike API clients, this SDK runs models directly on-device, leveraging Apple Silicon for high performance.*

mediumhomepage#2
Add a homepage URL to the repository's About section
Why:
COPY-PASTE FIX
```
https://argmax.ai
```

mediumtopics#3

Expand repository topics to highlight on-device ML and Apple Silicon

Why:

CURRENT

inference, ios, macos, pyannote, qwen3-tts, speaker-diarization, speakerkit, speech-recognition, speech-to-text, swift, text-to-speech, transformers, ttskit, whisper, whisperkit

COPY-PASTE FIX

inference, ios, macos, pyannote, qwen3-tts, speaker-diarization, speakerkit, speech-recognition, speech-to-text, swift, text-to-speech, transformers, ttskit, whisper, whisperkit, on-device-ml, apple-silicon, coreml, ml-frameworks

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 argmaxinc/argmax-oss-swift

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

AVSpeechSynthesizer

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

AVSpeechSynthesizer · recommended 1×
SFSpeechRecognizer · recommended 1×
OpenAI Whisper · recommended 1×
Picovoice Rhino · recommended 1×
Picovoice Porcupine · recommended 1×

CATEGORY QUERY
How can I integrate on-device speech-to-text and text-to-speech into my Swift iOS app?
you: not recommended
AI recommended (in order):
1. AVSpeechSynthesizer
2. SFSpeechRecognizer
3. OpenAI Whisper
4. Picovoice Rhino
5. Picovoice Porcupine
6. Google Cloud Speech-to-Text
7. Google Cloud Text-to-Speech
AI recommended 7 alternatives but never named argmaxinc/argmax-oss-swift. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Seeking a Swift library for robust speaker diarization on macOS and iOS devices.
you: not recommended
AI recommended (in order):
1. Speech Framework
2. Kaldi
3. OpenVINO
4. PyTorch Mobile
5. TensorFlow Lite
6. Microsoft Azure Cognitive Services Speech SDK
7. Google Cloud Speech-to-Text API
AI recommended 7 alternatives but never named argmaxinc/argmax-oss-swift. 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 argmaxinc/argmax-oss-swift?
pass
AI did not name argmaxinc/argmax-oss-swift — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts argmaxinc/argmax-oss-swift in production, what risks or prerequisites should they evaluate first?
pass
AI named argmaxinc/argmax-oss-swift 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 argmaxinc/argmax-oss-swift solve, and who is the primary audience?
pass
AI named argmaxinc/argmax-oss-swift 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 argmaxinc/argmax-oss-swift. 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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MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/argmaxinc/argmax-oss-swift.svg)](https://repogeo.com/en/r/argmaxinc/argmax-oss-swift)

HTML

<a href="https://repogeo.com/en/r/argmaxinc/argmax-oss-swift"><img src="https://repogeo.com/badge/argmaxinc/argmax-oss-swift.svg" alt="RepoGEO" /></a>

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argmaxinc/argmax-oss-swift — 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