RRepoGEO

REPOGEO REPORT · LITE

google/flax

Default branch main · commit e9aaebe5 · scanned 5/13/2026, 7:52:07 PM

GitHub: 7,196 stars · 804 forks

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
  • mediumreadme#1
    Add a sentence to the README introduction emphasizing JAX's functional paradigm

    Why:

    CURRENT
    Released in 2024, Flax NNX is a new simplified Flax API that is designed to make it easier to create, inspect, debug, and analyze neural networks in JAX. It achieves this by adding first class support for Python reference semantics. This allows users to express their models using regular Python objects, enabling reference sharing and mutability.
    COPY-PASTE FIX
    Released in 2024, Flax NNX is a new simplified Flax API that is designed to make it easier to create, inspect, debug, and analyze neural networks in JAX. Leveraging JAX's functional programming paradigm, automatic differentiation, and XLA compilation, Flax enables high-performance and scalable neural network development. It achieves this by adding first class support for Python reference semantics. This allows users to express their models using regular Python objects, enabling reference sharing and mutability.
  • mediumtopics#2
    Expand repository topics to include common deep learning terms

    Why:

    CURRENT
    jax
    COPY-PASTE FIX
    jax, neural-networks, deep-learning, machine-learning, ai, research, google, python
  • lowabout#3
    Update repository description to reflect the new NNX API focus

    Why:

    CURRENT
    Flax is a neural network library for JAX that is designed for flexibility.
    COPY-PASTE FIX
    Flax is a neural network library for JAX, featuring the new NNX API for flexible and inspectable deep learning models.

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. Objax · recommended 1×
  • CATEGORY QUERY
    What are the best libraries for building and training neural networks using JAX?
    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 framework for JAX with easy model inspection and debugging.
    you: #1
    AI recommended (in order):
    1. Flax ← you
    2. Haiku
    3. Equinox
    4. Objax
    5. Trax
    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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  • Prioritized action items8 vs 3 in Lite