RRepoGEO

REPOGEO REPORT · LITE

google/flax

Default branch main · commit dcfabd05 · scanned 6/24/2026, 6:47:01 AM

GitHub: 7,247 stars · 819 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
93 /100
Healthy
Category recall
2 / 2
Avg rank #1.0 when recommended
Rule findings
2 pass · 0 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 google/flax, 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
  • mediumtopics#1
    Expand repository topics for broader discoverability

    Why:

    CURRENT
    jax
    COPY-PASTE FIX
    jax, neural-networks, deep-learning, machine-learning, nnx, linen, deep-learning-framework, machine-learning-library
  • mediumreadme#2
    Add a link to a comparison guide in the README

    Why:

    COPY-PASTE FIX
    Add a sentence to your README, perhaps in the 'Overview' or 'Documentation' section, like: `For a detailed look at how Flax compares to other JAX neural network libraries like Haiku and Equinox, please see our [Comparison Guide](link-to-your-comparison-guide).` (You would need to create the Comparison Guide content separately).
  • lowabout#3
    Align repository description with README's H1

    Why:

    CURRENT
    Flax is a neural network library for JAX that is designed for flexibility.
    COPY-PASTE FIX
    Flax is a neural network library and ecosystem for JAX designed for flexibility.

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
2 / 2
100% of queries surface google/flax
Avg rank
#1.0
Lower is better. #1 = top recommendation.
Share of voice
20%
Of all named tools, what % are you?
Top rival
Haiku
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Haiku · recommended 2×
  2. Equinox · recommended 2×
  3. JAX/Stax · recommended 1×
  4. Elegy · recommended 1×
  5. Optax · recommended 1×
  • CATEGORY QUERY
    What are the best libraries for building neural networks using the JAX framework?
    you: #1
    AI recommended (in order):
    1. Flax ← you
    2. Haiku
    3. Equinox
    4. JAX/Stax
    5. Elegy
    Show full AI answer
  • CATEGORY QUERY
    Seeking a flexible deep learning library for JAX, emphasizing easy model inspection and debugging.
    you: #1
    AI recommended (in order):
    1. Flax ← you
    2. Haiku
    3. Equinox
    4. Optax
    5. JAX
    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 google/flax?
    pass
    AI named google/flax explicitly

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

  • If a team adopts google/flax in production, what risks or prerequisites should they evaluate first?
    pass
    AI named google/flax 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 google/flax solve, and who is the primary audience?
    pass
    AI named google/flax explicitly

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

Embed your GEO score

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google/flax — 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