REPOGEO REPORT · LITE
allenai/OLMoE
Default branch main · commit 357454f4 · scanned 6/19/2026, 9:53:13 AM
GitHub: 1,027 stars · 115 forks
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.
2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).
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 allenai/OLMoE, 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
2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- mediumreadme#1Refine README opening to highlight problem solved and audience
Why:
CURRENTFully open, state-of-the-art Mixture of Expert model with 1.3 billion active and 6.9 billion total parameters. All data, code, and logs released.
COPY-PASTE FIXOLMoE provides a fully open, state-of-the-art Mixture-of-Experts (MoE) language model designed to address the computational and scalability challenges of large language models. With 1.3 billion active and 6.9 billion total parameters, it offers a transparent and reproducible foundation for AI researchers and machine learning engineers, with all data, code, and logs released.
- lowcomparison#2Add a brief comparison section to the README
Why:
COPY-PASTE FIX## Comparison with Other MoE Models While models like Mixtral 8x7B, DeepSeek-MoE, and Qwen1.5-MoE offer powerful Mixture-of-Experts architectures, OLMoE distinguishes itself through its unparalleled commitment to **transparency and reproducibility**. As part of the broader OLMo project, we release all pretraining checkpoints, final GGUF models, code, data, and logs, providing a fully open foundation for research and adaptation. This allows researchers and engineers to deeply understand, replicate, and build upon our work without hidden components or data.
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.
- Mixtral 8x7B · recommended 1×
- DeepSeek-MoE · recommended 1×
- Qwen1.5-MoE · recommended 1×
- OpenMoE · recommended 1×
- Switch Transformers · recommended 1×
- CATEGORY QUERYLooking for an open-source mixture-of-experts model for efficient large language model inference.you: not recommendedAI recommended (in order):
- Mixtral 8x7B
- DeepSeek-MoE
- Qwen1.5-MoE
- OpenMoE
- Switch Transformers
AI recommended 5 alternatives but never named allenai/OLMoE. This is the gap to close.
Show full AI answer
- CATEGORY QUERYWhere can I find a fully transparent and reproducible large language model for research and adaptation?you: not recommendedAI recommended (in order):
- Llama 2
- Mistral 7B / Mixtral 8x7B
- Falcon
- Pythia Suite
- OpenLLaMA
AI recommended 5 alternatives but never named allenai/OLMoE. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesswarn
Suggestion:
- README presencepass
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 allenai/OLMoE?passAI named allenai/OLMoE explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts allenai/OLMoE in production, what risks or prerequisites should they evaluate first?passAI named allenai/OLMoE 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 allenai/OLMoE solve, and who is the primary audience?passAI named allenai/OLMoE 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 allenai/OLMoE. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.
[](https://repogeo.com/en/r/allenai/OLMoE)<a href="https://repogeo.com/en/r/allenai/OLMoE"><img src="https://repogeo.com/badge/allenai/OLMoE.svg" alt="RepoGEO" /></a>Subscribe to Pro for deep diagnoses
allenai/OLMoE — 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