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Buying question

Which buying criteria matter most for production vector retrieval, including recall, latency, filtering, durability, and operations?

Which brands each model API named when asked this question, and which pages it cited. Answer text is not published.
Snapshot Sep 12, 2026. Each category is re-run in rotation, every few weeks.

Commercial

Kind of question

3

Model APIs

2

Brands named

11

Pages cited

Brands

Brands the answers named

Rank#BrandModel APIsMentionsOwn-site citationsNamed by
1Zilliz Cloud / Milvuszilliz.com202OpenAI · Google
2Redisredis.io101OpenAI

Model APIs

What each model API returned

Model APIModelBrands namedCitationsDomainsAnswer hash
OpenAIopenai/gpt-4o-miniZilliz Cloud / Milvus · Redis55d911b3cf…dfda4
Anthropicanthropic/claude-haiku-4-5None named00aca9c10c…2f214
Googlegoogle/gemini-2.5-flashZilliz Cloud / Milvus658a897be1…83de3

Sources

Pages the answers cited

Snapshots
794067bc-f4fa-456f-8063-1db7efff0c35
Question set
vector-database-platforms-2026-07-27
Benchmark version
4-vector-database-platforms-2026-07-27-models-64232fd32583
What is kept
Measured in Vector DBs. Full answers are not stored or published, and no customer data is included.

Enter your website. In about two minutes, Rank.ai asks ChatGPT, Claude and Gemini 12 questions your customers ask and grades how often they name you.

  • Your grade out of 100How often AI names you, cites your site, and how high it ranks you.
  • Who gets namedEvery competitor in the answers, most named first.
  • The pages AI readsThe sources behind each answer.
  • Three fixesWhat to fix first, with a brief for the first article.