Buyer prompt · published evidence
How should an engineering team evaluate vector search benchmark claims for recall, tail latency, throughput, scale, and total cost?
An exact prompt-level view of which reviewed brands surfaced and which public URLs the configured AI models cited. No answer text or tenant data is published.
- Intent
- commercial
- Model providers
- 3
- Categories
- 1
- Last observed
- Aug 4, 2026, 12:00 AM UTC
Competitive outcome
Brands surfaced
Ordered by provider breadth, then total mentions and owned-domain citations. A mention is not an endorsement or a position claim.
| # | Brand | Category | Providers | Mentions | Owned citations | Provider evidence |
|---|---|---|---|---|---|---|
| 01 | Qdrantqdrant.tech ↗ | Vector DBs | 1 | 0 | 1 | Openai |
Model comparison
Answer matrix
One row per configured provider and category snapshot. Hashes prove answer identity without publishing stored answer text.
| Provider | Model version | Category | Brands surfaced | Citations | Unique domains | Answer hash |
|---|---|---|---|---|---|---|
| Openai | openai/gpt-4o-mini | Vector DBs | Qdrant | 6 | 6 | 94e99e07…1f4eb |
| Anthropic | anthropic/claude-haiku-4-5 | Vector DBs | None observed | 0 | 0 | 40afc1af…9f745 |
| Gemini | google/gemini-2.5-flash | Vector DBs | None observed | 6 | 6 | 18d8fe68…c3c37 |
URL-derived citations
Sources cited
Hostnames are derived from the returned public URLs. Best position is the smallest citation position observed.