REPOGEO REPORT · LITE

OpenRouterTeam/openrouter-runner

Default branch main · commit 93e51b1c · scanned 5/12/2026, 5:17:45 AM

GitHub: 1,233 stars · 120 forks

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

highreadme#1

Clarify README to explicitly state archived status and guide to current solutions

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. No longer in use, but preserved here for historical purposes. Check out the current models list here, or head over to our docs to learn more about our modern features for growing startups and enterprises alike.

COPY-PASTE FIX

This repository is an **archived artifact** from the early days of OpenRouter and is **no longer maintained or intended for active use**. It is preserved here for historical context only. For current OpenRouter features, models, and integration methods, please visit our main site at [https://openrouter.ai](https://openrouter.ai) and our documentation.

hightopics#2
Add relevant topics to the repository
Why:
COPY-PASTE FIX
```
["deprecated", "archive", "llm-inference", "openrouter", "vllm", "historical"]
```

mediumabout#3

Update the repository description to reflect its archived status

Why:

CURRENT

Deprecated inference engine

COPY-PASTE FIX

Archived: Historical OpenRouter inference engine (vLLM-based), no longer maintained or for active use.

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

huggingface/transformers

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

huggingface/transformers · recommended 1×
huggingface/accelerate · recommended 1×
vllm-project/vllm · recommended 1×
triton-inference-server/server · recommended 1×
openvinotoolkit/openvino · recommended 1×

CATEGORY QUERY
How to run custom large language models for specialized applications?
you: not recommended
AI recommended (in order):
1. Hugging Face Transformers (huggingface/transformers)
2. Accelerate (huggingface/accelerate)
3. vLLM (vllm-project/vllm)
4. NVIDIA Triton Inference Server (triton-inference-server/server)
5. OpenVINO (openvinotoolkit/openvino)
6. ONNX Runtime (microsoft/onnxruntime)
7. MLflow (mlflow/mlflow)
8. Ray Serve (ray-project/ray)
AI recommended 8 alternatives but never named OpenRouterTeam/openrouter-runner. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are efficient inference engines for serving custom LLMs with high throughput?
you: not recommended
AI recommended (in order):
1. vLLM
2. NVIDIA TensorRT-LLM
3. DeepSpeed-MII
4. TGI (Text Generation Inference)
5. OpenVINO
6. ONNX Runtime
7. TorchServe
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

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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>

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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