# pgvector: how AI models rank it, November 2026

Gane Index, November 2026 Edition. Named in 73 judge labels across 1 category by 14 of 14 models. Page: https://www.gane.ai/index/it/vendors/pgvector

## Standing by category

| Category | Share | Rank | Negative rate | Labels |
|---|---|---|---|---|
| [Vector databases](https://www.gane.ai/index/it/it-data/vector-databases/index.md) | 34% | 2 | 8% | 73 |

## What the models said for it

- "the recommendation is to start with pgvector unless your scale, query patterns, or operational constraints provide specific evidence otherwise" (Claude Haiku 4.5, Vector databases)
- "Start simple: Use pgvector (in Postgres) or SQLite with vector extensions for most apps—it's battle-tested, avoids new tech debt" (Grok 4.20, Vector databases)
- "If your company already uses PostgreSQL for standard application data, pgvector is almost always the most cost-effective choice." (Gemini 3.5 Flash, Vector databases)
- "The best vector database for a mid-market B2B company is pgvector... It is the strongest default for mid-market enterprises." (Muse Glimmer 30B, Vector databases)

## And against it

- "pgvector does not natively support GPU acceleration or disk-optimized indexes, and at billion-scale workloads typically require more advanced sharding strategies" (Claude Haiku 4.5, Vector databases)
- "Using vectors beside your application data in Postgres via pgvector is often the safest default until measured retrieval requirements force a dedicated engine." (Muse Glimmer 30B, Vector databases)
- "pgvector for large, high-throughput workloads with selective filters or many tenants... approximate-index filtering can return too few results" (GPT-6 Luna, Vector databases)
- "Great for <5M-10M vectors. However, building HNSW indexes on tens of millions of vectors requires huge amounts of RAM" (Gemini 3.5 Flash, Vector databases)

## By model

| Model | First choice | Alternative | Mention | Warning | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 1 | 2 | 2 | 1 | 6 |
| GPT-5.4 mini | 1 | 3 | 0 | 0 | 4 |
| Gemini 3.5 Flash | 2 | 3 | 0 | 1 | 6 |
| Perplexity Sonar | 2 | 3 | 0 | 0 | 5 |
| Grok 4.20 | 2 | 4 | 0 | 0 | 6 |
| Mistral Small | 1 | 1 | 3 | 0 | 5 |
| DeepSeek V4 Flash | 2 | 3 | 0 | 1 | 6 |
| Llama 4 Maverick | 1 | 3 | 1 | 0 | 5 |
| Qwen 3.7 Flash | 2 | 3 | 1 | 0 | 6 |
| Kimi K2 | 2 | 4 | 0 | 0 | 6 |
| GLM 4.7 FlashX | 1 | 1 | 0 | 1 | 3 |
| MiniMax M2.5 | 1 | 2 | 0 | 0 | 3 |
| GPT-6 Luna | 1 | 4 | 0 | 1 | 6 |
| Muse Glimmer 30B | 2 | 3 | 0 | 1 | 6 |

## Sources returned with these answers

The sites and pages cited by the answers that named pgvector, from 172 of the 192 answers that named it (only the models that return a source list).

### Domains cited

- github.com: 100
- dev.to: 66
- g2.com: 54
- linkedin.com: 46
- qdrant.tech: 33
- milvus.io: 31
- geekflare.com: 30
- actian.com: 28
- gane.ai/index: 28
- resources.rework.com: 28

### Pages cited

- https://g2.com/articles/best-vector-databases: 50
- https://geekflare.com/open-source/vector-database: 30
- https://sganalytics.com/blog/top-vector-databases-enterprise-ai: 25
- https://atlan.com/know/top-vector-databases-enterprise-ai: 21
- https://github.com/exploreborders/RAG_Architecture/blob/main/docs/3-technical/vector-databases.md: 21
- https://s3.amazonaws.com/eckerson/content_assets/assets/000/000/470/original/111424_TT_Vector_Database_v2_(1).pdf: 21
- https://pingcap.com/compare/best-vector-database: 18
- https://dupple.com/learn/best-vector-databases: 17

## Record

- Method: https://www.gane.ai/index/it/methodology
- License: CC BY 4.0. Cite as Gane Index, November 2026 Edition, www.gane.ai/index/it.