REPOGEO REPORT · LITE

tile-ai/tilelang

Default branch main · commit ed00dfcd · scanned 6/29/2026, 1:32:11 AM

GitHub: 6,562 stars · 616 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 tile-ai/tilelang, 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

domain-specific-language, dsl, gpu, cpu, accelerators, high-performance-computing, hpc, ai, machine-learning, deep-learning, kernel-development, tvm, cutlass, pythonic

highreadme#2

Strengthen README opening to clarify AI/ML DSL positioning

Why:

CURRENT

Tile Language (**tile-lang**) is a concise domain-specific language designed to streamline the development of high-performance GPU/CPU kernels (e.g., GEMM, Dequant GEMM, FlashAttention, LinearAttention).

COPY-PASTE FIX

Tile Language (**tile-lang**) is a concise domain-specific language (DSL) designed to streamline the development of high-performance **AI/ML kernels** (e.g., GEMM, Dequant GEMM, FlashAttention, LinearAttention) for GPU/CPU/Accelerators. It provides a Pythonic syntax with an underlying compiler infrastructure on top of TVM, allowing developers to focus on productivity without sacrificing the low-level optimizations necessary for state-of-the-art performance in AI workloads.

mediumreadme#3

Add a clear statement about the repository's license in the README

Why:

COPY-PASTE FIX

## License
This project is licensed under [Specify License Name(s) and terms here, e.g., 'a custom license combining Apache 2.0 and MIT terms']. Please see the [LICENSE](LICENSE) file for full details.

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 tile-ai/tilelang

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

CUDA C++

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

CUDA C++ · recommended 1×
OpenCL · recommended 1×
SYCL · recommended 1×
HIP (Heterogeneous-compute Interface for Portability) · recommended 1×
OpenMP · recommended 1×

CATEGORY QUERY
How can I efficiently develop high-performance GPU/CPU kernels without sacrificing optimization?
you: not recommended
AI recommended (in order):
1. CUDA C++
2. OpenCL
3. SYCL
4. HIP (Heterogeneous-compute Interface for Portability)
5. OpenMP
6. Intel oneAPI DPC++
7. Raja/Kokkos
AI recommended 7 alternatives but never named tile-ai/tilelang. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What tools help write optimized accelerator kernels using a Pythonic DSL for performance?
you: not recommended
AI recommended (in order):
1. Taichi (taichi-dev/taichi)
2. Numba (numba/numba)
3. JAX (google/jax)
4. PyTorch (pytorch/pytorch)
5. TensorFlow (tensorflow/tensorflow)
6. CuPy (cupy/cupy)
AI recommended 6 alternatives but never named tile-ai/tilelang. 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 tile-ai/tilelang?
pass
AI named tile-ai/tilelang explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts tile-ai/tilelang in production, what risks or prerequisites should they evaluate first?
pass
AI named tile-ai/tilelang 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 tile-ai/tilelang solve, and who is the primary audience?
pass
AI named tile-ai/tilelang 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 tile-ai/tilelang. 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/tile-ai/tilelang.svg)](https://repogeo.com/en/r/tile-ai/tilelang)

HTML

<a href="https://repogeo.com/en/r/tile-ai/tilelang"><img src="https://repogeo.com/badge/tile-ai/tilelang.svg" alt="RepoGEO" /></a>

Pro

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tile-ai/tilelang — 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