---
title: "Linkup"
type: "AI Tool"
url: "https://aidemos.com/tools/linkup"
description: "We tested Linkup’s standard vs deep modes: standard extracted cleanly with zero errors, but ranking stayed weak and deep was 10x costlier, slower, and weaker."
category: "developer-tools"
website: "https://www.linkup.so/"
published: "2026-08-20T10:53:16.054919+00:00"
updated: "2026-08-24T11:25:55.288697+00:00"
---

# Linkup

Standard mode is the usable tier: strong extraction, weak ranking; deep is slower, pricier, and weaker.

## TL;DR Verdict

**Standard is the useful tier; deep is not worth the tradeoff.**

**Where it wins:**
- you care most about getting usable page text back from the web
- you can tolerate weaker top-k ranking if the extracted content is still useful
- you want a zero-error, stable API and are comfortable comparing standard versus deep by real run metrics

**Main limitation:** you need strong top-1/top-3 retrieval on content-depth or ambiguity queries

**Pricing:** standard $5.00 / 1k queries · deep $50.00 / 1k queries

`52-query run` · `2.00 extraction` · `Deep = 10x cost` · `0 errors`

**Website:** [Visit Linkup](https://www.linkup.so/)

> **Standard is the useful tier; deep is not worth the tradeoff.**
>
> Linkup splits cleanly by mode. Standard is a legitimate web-content API because extraction is strong and the run had zero errors, but its ranking is weak. Deep does not rescue that weakness: it is 10x the benchmark cost, slower at p95, and still scores lower than standard. The Q37 length discrepancy and the missing response-native metadata mean the evidence is not fully closed, so this is a mixed verdict rather than a clean win.

## Feature-by-Feature Breakdown

### Live Web Retrieval and Result Ranking

**Verdict:** Weak overall; useful only if you can tolerate poor top-k precision.

Linkup can take a live-web query set in standard or deep mode and return ranked results for agent consumption. The evidence here covers both modes being error-free across 52 calls each, with retrieval quality measured on answerable queries and deep mode not improving enough to offset cost.

**Input:** Ground-truth query set

> **Csv** — Ground-truth query set

**Output:** Scored run export

> **Csv** — Scored run export

**Bottom line:** Retrieval is the weakest part of Linkup, and deep does not improve it enough to justify the cost.

### Answer-Bearing Page Content Extraction

**Verdict:** Strong; this is the part that actually works.

Linkup can return substantial clean text from a found page instead of only a thin snippet. The evidence includes the extraction quality score and the Q37 probe returning 22,708 characters containing all five GDPR Article 17(3) exceptions.

**Input:** Ground-truth query set

> **Csv** — Ground-truth query set

**Output:** Per-query raw output log

> **Md** — Per-query raw output log

**Bottom line:** Extraction is a real strength, but the Q37 length contradiction still needs a raw-JSON reconciliation before publishing.

## Run-derived cost per 1k queries

Measured from the 2026-08-16 run in ap-south-1

| Plan | Price | Notes |
| --- | --- | --- |
| standard ★ (tested) | $5.00 / 1k queries | Cheaper and faster tier; still the better value despite weak ranking. |
| deep (tested) | $50.00 / 1k queries | 10x the standard cost, slower at p95, and lower-scoring on retrieval. |

*These are benchmark-derived all-in costs from the test run, not vendor list pricing.*

## Is It Right For You?

**Use it if**
- you care most about getting usable page text back from the web
- you can tolerate weaker top-k ranking if the extracted content is still useful
- you want a zero-error, stable API and are comfortable comparing standard versus deep by real run metrics

**Skip it if**
- you need strong top-1/top-3 retrieval on content-depth or ambiguity queries
- you need response-native published dates, content length, or cost fields
- you want a deep tier that justifies a 10x price increase
- you need confirmed free-tier allowance before committing

## Classification

- **Category:** developer-tools
- **Subcategory:** search-engine
- **Type:** text
- **Built for:** Student, Founder, Marketing, Teacher, Creator, Editor, Other

## Frequently Asked Questions

**Q: Does Linkup return full page text or just snippets?**

The report says Linkup returns usable extracted content, not only short snippets. Standard median output length was about 3,552 characters and deep was about 3,720 characters, extraction quality scored 2.00, and the Q37 probe returned 22,708 characters containing all five GDPR Article 17(3) exceptions. The content-length story is not fully reconciled yet because Q37 is far above the published median framing.

**Q: Is deep better than standard?**

No. Deep was worse on retrieval and much more expensive. In the benchmark it cost $50.00 per 1k queries versus $5.00 for standard, ran slower at p95 (9,441 ms versus 4,478 ms), and scored lower on top-3 retrieval (12.8% versus 14.9%).

**Q: Does Linkup return published dates in its response?**

No. The report says 0% published dates, and it also notes that response-native content length, published date, and cost fields were missing, so those had to be computed client-side.

**Q: What is Linkup’s biggest weakness in this benchmark?**

Ranking. The report calls Linkup the lowest-retrieval-accuracy priced mode in the benchmark, with 0% top-3 on content-depth queries and 0% ambiguity handling. The surprise is that extraction is strong even when ranking is weak.

**Q: What raw artifacts back this page?**

Three attached artifacts back the run: QUERY-SET-ground-truth.csv for the fixed benchmark inputs, LINKUP-scored-run-export.csv for the aggregate metrics, and LINKUP-per-query-output.md for the raw per-query outputs, including the Q37 and Q52 probes.

## Similar Tools

AI tools similar to Linkup:

- [Jina](https://aidemos.com/tools/jina) — Rich web search results for agents, but this free-tier run was incomplete and not comparable.
- [OpenAI web_search](https://aidemos.com/tools/openai-web-search) — A citation-honest control arm for live-web answering, but not a reliable retrieval layer for fresh content.
- [SerpAPI](https://aidemos.com/tools/serpapi) — Fast, zero-error live web search for agents, with stable mid-pack retrieval and snippet outputs.
- [Serper](https://aidemos.com/tools/serper) — Fast, cheap raw web search for agents — strong on ambiguity, but too snippet-thin to replace a scrape.
- [Valyu](https://aidemos.com/tools/valyu) — Returns usable web text for agents, but the citation layer is too error-prone to trust.
- [You.com](https://aidemos.com/tools/you-com) — Best-in-benchmark top-1 web retrieval for agent queries, with full-page text and published dates — but at a measured high all-in cost.

## Need a custom AI solution for this use case?

If you are looking to build a custom web search, information extraction, or retrieval assistant for your business or internal workflow, email us at [contact@futuresmart.ai](mailto:contact@futuresmart.ai).

### Found something inaccurate or missing?

We try to keep our AI research accurate and useful. If you found outdated information, an issue, or have a suggestion, email us at [collaborate@aidemos.com](mailto:collaborate@aidemos.com).