REPOGEO REPORT · LITE

OpenRouterTeam/openrouter-runner

Default branch main · commit 93e51b1c · scanned 6/22/2026, 11:27:54 AM

GitHub: 1,243 stars · 123 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 OpenRouterTeam/openrouter-runner, 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 specific topics to clarify the repository's historical and deprecated status
Why:
COPY-PASTE FIX
```
openrouter, llm-inference, vllm, deprecated, historical-artifact, machine-learning, python
```
mediumabout#2
Refine the repository description to emphasize its historical artifact status
Why:
CURRENT
```
Deprecated inference engine
```
COPY-PASTE FIX
```
Historical artifact: a deprecated inference engine from OpenRouter's early days, preserved for reference.
```

lowreadme#3

Slightly rephrase the README's opening sentence to immediately signal its historical nature

Why:

CURRENT

This repo is an artifact from the early days of OpenRouter, when the opensource LLM provider ecosystem was much more nascent. Early adopters wanted to chat with niche fine-tunes, so we built this with vllm to serve them.

COPY-PASTE FIX

This repository is a historical artifact from the early days of OpenRouter, when the open-source LLM provider ecosystem was much more nascent. It was built with vLLM to serve niche fine-tunes for early adopters.

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 OpenRouterTeam/openrouter-runner

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

vLLM

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

vLLM · recommended 2×
TGI (Text Generation Inference) · recommended 2×
NVIDIA Triton Inference Server · recommended 1×
OpenLLM · recommended 1×
FastAPI · recommended 1×

CATEGORY QUERY
What are the best tools for self-hosting and serving custom fine-tuned large language models?
you: not recommended
AI recommended (in order):
1. vLLM
2. TGI (Text Generation Inference)
3. NVIDIA Triton Inference Server
4. OpenLLM
5. FastAPI
6. Transformers (Hugging Face)
7. optimum
8. Ray Serve
AI recommended 8 alternatives but never named OpenRouterTeam/openrouter-runner. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Looking for an open-source inference engine to deploy and manage various LLM models efficiently.
you: not recommended
AI recommended (in order):
1. vLLM
2. TGI (Text Generation Inference)
3. TensorRT-LLM
4. OpenVINO (Open Visual Inference & Neural Network Optimization)
5. ONNX Runtime
6. DeepSpeed-MII (Model Inference Interface)
7. llama.cpp
AI recommended 7 alternatives but never named OpenRouterTeam/openrouter-runner. 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 OpenRouterTeam/openrouter-runner?
pass
AI named OpenRouterTeam/openrouter-runner explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts OpenRouterTeam/openrouter-runner in production, what risks or prerequisites should they evaluate first?
pass
AI named OpenRouterTeam/openrouter-runner 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 OpenRouterTeam/openrouter-runner solve, and who is the primary audience?
pass
AI named OpenRouterTeam/openrouter-runner 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 OpenRouterTeam/openrouter-runner. 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/OpenRouterTeam/openrouter-runner.svg)](https://repogeo.com/en/r/OpenRouterTeam/openrouter-runner)

HTML

<a href="https://repogeo.com/en/r/OpenRouterTeam/openrouter-runner"><img src="https://repogeo.com/badge/OpenRouterTeam/openrouter-runner.svg" alt="RepoGEO" /></a>

Pro

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OpenRouterTeam/openrouter-runner — 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