What AI says about Jina AI
Jina AI provides search and inference tools, including reranking models and embeddings for text and multimodal data. It is among the brands most often named when teams need reranking services to boost retrieval accuracy in RAG pipelines.
AI calls itclean,llm-ready,multilingual,clean, structured,simple,high-performance
Since Jul 5Updated Nov 11, 2026Based on 22,966 AI answers
Reviewed by Dimitry Apollonsky
Mentioned in · Public index
1%
of AI answers about Jina AI and its rivals · since Jul 5
Based on 22,966 AI answers
- ChatGPT2%
- Google AI Mode1%
How often AI mentions Jina AI
of AI answers about Jina AI and its rivals
Track your brand free to see 13 weeks of history.
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Sep 14OctNov 2
- · ChatGPT switched to GPT-6 Luna
Jina AI products in AI answers
BrandMentioned in
Markets where AI mentions Jina AI
Mentioned inLowHighFew answers
All marketsChatGPTGoogle AI Mode
- Embedding Model APIs and ServicesChatGPTGoogle AI Mode
- RAG Platforms and Retrieval ToolsChatGPTGoogle AI Mode
- Vector Database PlatformsOutside both engines’ top 25
- Enterprise MLOps Model Registry PlatformsOutside both engines’ top 25
- Developer Backend & Vector Search ServicesOutside both engines’ top 25
- AI Document Processing and OCR ToolsOutside both engines’ top 25
- AI Research and Writing AssistantsOutside both engines’ top 25
- Visual Search and Auto-Tagging APIsOutside both engines’ top 25
- Web Scraping & Browser Automation APIsOutside both engines’ top 25
Topics where AI mentions Jina AI
TopicMentioned in · on this topicRank
- Most mentionedMentioned in
- Which reranking API most improves retrieval relevance for RAG?on this questionJina AI shares the lead for mentions with 2 more72%
Excerpts where Jina AI appeared in the AI's answer
Google AI ModeSep 27, 2026, Google AI Mode Jina AI (jina-reranker-v3): Stands out for utilizing a listwise approach
Google AI ModeSep 11, 2026, Google AI Mode Jina AI Rerank (incorporating newer listwise and multi-lingual architectures like v3) stands out for long-context RAG
- Our RAG (Retrieval-Augmented Generation) pipeline is retrieving irrelevant chunks of text. Who offers re-ranking services to improve retrieval accuracy?on this questionVoyage AI shares the lead for mentions with 2 more76%
Excerpts where Jina AI appeared in the AI's answer
Google AI ModeOct 1, 2026, Google AI Mode Jina AI Rerankers : Provides high-context, multilingual neural re-rankers
Google AI ModeSep 20, 2026, Google AI Mode Jina AI : Offers versatile, multimodal open-weight and managed re-rankers
- What’s the best reranker service to upgrade RAG answer quality?on this questionVoyage AI shares the lead for mentions with 1 more52%
Excerpts where Jina AI appeared in the AI's answer
Google AI ModeAug 10, 2026, Google AI Mode Jina AI Reranker (jina-reranker-v3): Best for: Ultra-low latency requirements and agentic code/function calling workflows.
Google AI ModeAug 6, 2026, Google AI Mode Jina AI Reranker (v2 / v3): Known for speed, long-context support, and exceptional multilingual/code capabilities.
- We are building a RAG pipeline and need a reliable managed embedding API that offers stable latency for real-time search. Which third-party embedding providers are currently leading the market for production-grade applications?on this questionVoyage AI is the most-mentioned brand56%
Excerpts where Jina AI appeared in the AI's answer
ChatGPTSep 25, 2026, ChatGPT Jina AI — compelling for multilingual/long-context retrieval and offers explicit API rate tiers.
ChatGPTSep 13, 2026, ChatGPT Jina AI — worth benchmarking if multilingual retrieval, efficient models, or very high throughput are important.
Jina AI in AI answers
1 of 8
Our semantic search misses queries using industry slang. Who provides domain-adaptation services for embedding models?
ChatGPTChatGPT· Oct 21, 2026
Jina AI Offers an Auto Fine-Tuning service that adapts embeddings to a domain
Google AI ModeGoogle AI Mode· Sep 24, 2026
Jina AI – Provides high-performance embedding and reranking models with strong modular support for task-specific adaptation and fine-tuning on specialized text corpora.
Sites AI cites
- Your site23%
- Jina AI - Your Search Foundation, Supercharged. (opens in a new tab) · 7%Leaves Jina AI out
- Reranker API - Jina AI (opens in a new tab) · 6%
- Maximizing Search Relevance and RAG Accuracy with Jina Reranker (opens in a new tab) · 1%
- Reranker API - Jina AI (opens in a new tab) · 1%
- Embedding API - Jina AI (opens in a new tab) · 1%
- Embedding API - Jina AI (opens in a new tab) · 1%
- jina-reranker-v3 - Search Foundation Models (opens in a new tab) · 1%
- Embedding API - Jina AI (opens in a new tab) · 1%Leaves Jina AI out
- Improving Search Quality with Reranker API in MyScale (opens in a new tab) · 1%
- Embedding API - Jina AI (opens in a new tab) · <1%
- Leaves Jina AI out6%
- Top Reranker Models: I tested them all so You don't have to (opens in a new tab) · 2%
- How does a reranker improve RAG accuracy, and when is it worth adding one? (opens in a new tab) · 1%
- Top Rerank Models and Rerank APIs Comparison (opens in a new tab) · <1%
- Which Web Search API gives the cleanest Markdown output for local RAG parsing? : r/LLMDevs (opens in a new tab) · <1%Leaves Jina AI out
- What Embedding Models Are You Using For RAG? (opens in a new tab) · <1%
- Open-source embedding models: which one to use? (opens in a new tab) · <1%
- What is the current SOTA reranker for RAG pipelines? (opens in a new tab) · <1%
- Open-source embedding models: which one's the best? (opens in a new tab) · <1%
- Be mindful of some embedding APIs - they own rights ... - Reddit (opens in a new tab) · <1%
- Rerankers in RAG: when you need them + the main approaches (no fluff) (opens in a new tab) · <1%
- 5%
- [2409.10173] jina-embeddings-v3: Multilingual Embeddings With Task LoRA (opens in a new tab) · 2%
- [2509.25085] jina-reranker-v3: Last but Not Late Interaction for Listwise Document Reranking (opens in a new tab) · 1%
- jina-reranker-v3.5: An Efficient Listwise Reranker with Hybrid Attention and Self-Distillation (opens in a new tab) · 1%
- MMTEB: Massive Multilingual Text Embedding Benchmark (opens in a new tab) · <1%
- rerankers: A Lightweight Python Library to Unify Ranking Methods (opens in a new tab) · <1%
- LoRACode: LoRA Adapters for Code Embeddings (opens in a new tab) · <1%
- A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions (opens in a new tab) · <1%
- jina-reranker-v3: Last but Not Late Interaction for Document Reranking (opens in a new tab) · <1%
- 4%
- jina-rerankers on Elastic Inference Service - Elasticsearch Labs (opens in a new tab) · 1%
- jina-embeddings-v3 is now available on Elastic Inference Service - Elasticsearch (opens in a new tab) · 1%
- Jina Embeddings v3 on Gemini Enterprise Agent Platform Model Garden (opens in a new tab) · 1%
- On-premises AI: Jina embedding models, no internet needed (opens in a new tab) · 1%
- Semantic reranking | Elastic Docs (opens in a new tab) · <1%
- Improve search relevance and RAG implementation | Elastic (opens in a new tab) · <1%
- jina-embeddings-v5-text: Compact multilingual embedding models - Elasticsearch (opens in a new tab) · <1%
- jina-rerankers on Elastic Inference Service - Elasticsearch Labs (opens in a new tab) · <1%
- 4%
- Rerankers in the RAG Pipeline 🔮. A purely overview-style article | by Annakokovina | Medium (opens in a new tab) · 1%
- Rerankers in RAG. Retrieval Augmented Generation (RAG)… | by Anbu Valluvan (opens in a new tab) · <1%
- Medium (opens in a new tab) · <1%
- Top 8 Rerankers: Quality vs Cost. A practical benchmark of modern… | by Bhagya Rana | Medium (opens in a new tab) · <1%
- Top 5 Re-Ranking Models Under 150 ms | by Hash Block - Medium (opens in a new tab) · <1%
- The Indispensable Reranker: A Deep Dive into Optimizing Retrieval in Retrieval-Augmented Generation… (opens in a new tab) · <1%
- Web Scraping using AI: Jina AI, Vector Databases, and the Future of RAG Applications (opens in a new tab) · <1%
- Medium (opens in a new tab) · <1%
- How to Choose the Best Vector Database and Embedding Model for Your LLM Application | by Yajurved Jayavarapu | Medium (opens in a new tab) · <1%
- Reranking- Advance RAG’s Technique | by Ayushi Gupta | Medium (opens in a new tab) · <1%
- 4%
- The Only Embedding Model You Need for RAG (opens in a new tab) · 1%
- RAG Reranking Explained: How To Improve RAG Results (opens in a new tab) · 1%
- LangChain (OpenAI) Vector Embeddings For Beginners (opens in a new tab) · 1%
- From Text to Meaning: Semantic Search with Sentence ... (opens in a new tab) · <1%
- RAG Model Study Guide Top 5 Embedding Models (opens in a new tab) · <1%
- The Only Embedding Model You Need for RAG (opens in a new tab) · <1%
- OpenAI vs. Open-source Embedding Model Showdown (opens in a new tab) · <1%
- RAG Tutorial 2026 #17: RAG Reranking and Next Steps! (opens in a new tab) · <1%
