REPOGEO REPORT · LITE

algorithmicsuperintelligence/optillm

Default branch main · commit df018d64 · scanned 6/23/2026, 2:36:54 AM

GitHub: 4,157 stars · 365 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

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 algorithmicsuperintelligence/optillm, 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

Reposition README to clarify core value proposition

Why:

CURRENT

OptiLLM** is an OpenAI API-compatible optimizing inference proxy that implements 20+ state-of-the-art techniques to dramatically improve LLM accuracy and performance on reasoning tasks - without requiring any model training or fine-tuning.

COPY-PASTE FIX

OptiLLM** is an OpenAI API-compatible inference proxy that dramatically improves LLM accuracy and performance on reasoning tasks (2-10x better) without requiring any model training or fine-tuning. Unlike traditional LLM optimization tools focused on compression or efficiency, OptiLLM specifically targets reasoning accuracy by implementing 20+ state-of-the-art techniques.

mediumabout#2

Refine the 'About' description to emphasize accuracy

Why:

CURRENT

Optimizing inference proxy for LLMs

COPY-PASTE FIX

An OpenAI API-compatible inference proxy that dramatically improves LLM accuracy and performance on reasoning tasks without fine-tuning, using 20+ state-of-the-art techniques.

lowhomepage#3
Add a homepage URL to the repository metadata
Why:
COPY-PASTE FIX
```
https://github.com/algorithmicsuperintelligence/optillm
```

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 algorithmicsuperintelligence/optillm

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Pinecone

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

Pinecone · recommended 1×
weaviate/weaviate · recommended 1×
chroma-core/chroma · recommended 1×
OpenAI Function Calling · recommended 1×
Anthropic Tools · recommended 1×

CATEGORY QUERY
How to improve LLM reasoning accuracy and performance without fine-tuning models?
you: not recommended
AI recommended (in order):
1. Pinecone
2. Weaviate (weaviate/weaviate)
3. ChromaDB (chroma-core/chroma)
4. OpenAI Function Calling
5. Anthropic Tools
6. LangChain (langchain-ai/langchain)
7. LlamaIndex (run-llama/llama_index)
8. Google Search API
9. SerpApi
10. GPT-4
11. Claude 3 Opus
12. Llama 3 70B
AI recommended 12 alternatives but never named algorithmicsuperintelligence/optillm. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Looking for an inference proxy to optimize OpenAI API calls for better reasoning tasks.
you: not recommended
AI recommended (in order):
1. LiteLLM
2. OpenRouter
3. Portkey.ai
4. Mithril
5. Helicone
6. Vellum
AI recommended 6 alternatives but never named algorithmicsuperintelligence/optillm. 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 algorithmicsuperintelligence/optillm?
pass
AI named algorithmicsuperintelligence/optillm explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts algorithmicsuperintelligence/optillm in production, what risks or prerequisites should they evaluate first?
pass
AI named algorithmicsuperintelligence/optillm 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 algorithmicsuperintelligence/optillm solve, and who is the primary audience?
pass
AI named algorithmicsuperintelligence/optillm 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 algorithmicsuperintelligence/optillm. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/algorithmicsuperintelligence/optillm.svg)](https://repogeo.com/en/r/algorithmicsuperintelligence/optillm)

HTML

<a href="https://repogeo.com/en/r/algorithmicsuperintelligence/optillm"><img src="https://repogeo.com/badge/algorithmicsuperintelligence/optillm.svg" alt="RepoGEO" /></a>

Pro

Subscribe to Pro for deep diagnoses

algorithmicsuperintelligence/optillm — 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