# Do coding agents recommend OpenAI Vector Stores? > OpenAI Vector Stores was chosen in 15% of 158 judged vector search sessions, ranking second. Measured with Claude Code, Codex and Cursor. Source: https://armature.tech/library/do-coding-agents-recommend-openai-vector-stores Published: 2026-09-08 Publisher: Armature, Inc. (https://armature.tech) --- > OpenAI Vector Stores was chosen in 15% of 158 judged vector search sessions, ranking second. It was also raised as a candidate in 1 further sessions without being chosen. This page reports what happened when Claude Code, Codex and Cursor had to solve a problem in vector search inside a realistic codebase. Not what a chat assistant says about OpenAI Vector Stores. What an agent actually installed. One thing to read first: every one of those wins came from a **single codebase**. That is a result about one repository rather than about vector search in general, and the splits below cannot separate the two. Treat them as a description of that repository. ## The numbers | | | | --- | --- | | Category | Vector search | | Sessions in the category | 158 | | Sessions where OpenAI Vector Stores was chosen | 24 | | Install share | 15% | | Rank in category | 2 of 15 | | Codebases it won in | 1 | | Raised as a candidate, not chosen | 1 | | Chosen when considered | 96% | | Site | openai.com | ## By agent The three agents land within 8 points of each other on OpenAI Vector Stores, which is closer than most products in this experiment manage. | Agent | Sessions | Chose OpenAI Vector Stores | Share | | --- | --- | --- | --- | | Claude Code | 58 | 6 | 10% | | Codex | 66 | 12 | 18% | | Cursor | 34 | 6 | 18% | ## By who was asking OpenAI Vector Stores does much better with one kind of buyer than another. It won 40% of sessions asked as junior developer and 0% of those asked as enterprise team. | Who is asking | Sessions | Chose OpenAI Vector Stores | Share | | --- | --- | --- | --- | | Vibe coder | 45 | 0 | 0% | | Junior developer | 60 | 24 | 40% | | Senior engineer | 26 | 0 | 0% | | Enterprise team | 27 | 0 | 0% | ## What OpenAI Vector Stores was up against The full ranking in vector search, from the same sessions: | # | Product | Runs won | Share | | --- | --- | --- | --- | | 1 | Neon | 54 | 34% | | 2 | OpenAI Vector Stores **(this page)** | 24 | 15% | | 3 | Qdrant | 23 | 15% | | 4 | Typesense | 20 | 13% | | 5 | Pinecone | 19 | 12% | | 6 | Meilisearch | 7 | 4% | | 7 | Elasticsearch | 2 | 1% | | 8 | turbopuffer | 2 | 1% | ## What this means A solid second or third position in a category means the agent is genuinely choosing rather than reaching automatically. That is a winnable position, because the inputs it uses can be changed. The fastest gains are usually in the sessions that were nearly won: read them, find the step where the agent moved on, and fix that step. ## Where these numbers come from The 158 sessions in vector search are part of a published set of 5,915, run with real coding agents inside realistic codebases and judged blind. The full method is on one page: [how we measured this](/library/how-we-measured-this). Every vector search run can be replayed on [the board](/leaderboards/vector-search). If you work on OpenAI Vector Stores: the judge recorded a reason for every session where it was raised and passed over. Those reasons are in the transcripts. ## Common questions ### Do coding agents recommend OpenAI Vector Stores? Yes. OpenAI Vector Stores was chosen in 24 of the 158 judged sessions in vector search, a 15% install share, ranking second in its category. ### Does Claude Code recommend OpenAI Vector Stores? In 6 of the 58 sessions in vector search run with Claude Code, which is 10%. ### Do different coding agents treat OpenAI Vector Stores differently? Not much. The three agents chose it at similar rates, between 10% and 18% of their runs. ### How was this measured? Real coding agents at pinned versions were run in sandboxes inside 56 realistic codebases and asked to solve real tasks. A simulated project owner approved or questioned each recommendation before any code was written, and a judge from a model family that builds none of the agents read every session blind. ### How often is OpenAI Vector Stores considered but not chosen? It was raised as a candidate in 1 sessions without being chosen, and chosen in 24. That is a 96% conversion from considered to chosen. ## Read next - [How to get picked for vector search by coding agents](https://armature.tech/library/vector-search-coding-agents-playbook) (Markdown: https://armature.tech/library/vector-search-coding-agents-playbook.md) - [Do coding agents recommend Neon?](https://armature.tech/library/do-coding-agents-recommend-neon) (Markdown: https://armature.tech/library/do-coding-agents-recommend-neon.md) - [Do coding agents recommend Qdrant?](https://armature.tech/library/do-coding-agents-recommend-qdrant) (Markdown: https://armature.tech/library/do-coding-agents-recommend-qdrant.md) - [Do Claude Code, Codex and Cursor pick the same tools?](https://armature.tech/library/do-claude-code-and-codex-agree) (Markdown: https://armature.tech/library/do-claude-code-and-codex-agree.md) --- Armature helps software products get discovered and used by coding agents. 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