Linkup icon
developer-tools

Linkup

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

Visit Linkup
52-query run2.00 extractionDeep = 10x cost0 errors
TL;DR — our verdictUpdated August 2026 · 2 test artifacts

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 (verified plans)
standard $5.00 / 1k queriesdeep $50.00 / 1k queries
Strongest test artifacts
Scored run export →Per-query raw output log →

Our take

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.

In-Depth Review

Our detailed analysis of Linkup — features, performance, and real-world testing.

AD
AI Demos Team
Expert Reviewer
Verified Review

Feature-by-Feature Breakdown

Live Web Retrieval and Result Ranking
Weak overall; useful only if you can tolerate poor top-k precision.
▾
Test Summary
Feature tested: Live Web Retrieval and Result Ranking
Result: Partial — Weak overall; useful only if you can tolerate poor top-k precision.

Feature tested: Live Web Retrieval and Result Ranking

Result: Partial

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

Expected behavior: 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.

Test case: Text/code file → Text/code file

Input type: Text/code file

Input used: Input artifact (Text/code file): Same fixed benchmark query set used for the deep-mode retrieval run. — QUERY-SET-ground-truth.csv

Observed output: Output artifact (Text/code file): Deep mode scored 6% top-1, 12.8% top-3, 28% top-10 on 47 answerable queries; $50.00 per 1k queries; p50 5,394 ms; p95 9,441 ms; 0 errors. — LINKUP-scored-run-export.csv

Input artifact: Input artifact (Text/code file): Same fixed benchmark query set used for the deep-mode retrieval run. — QUERY-SET-ground-truth.csv

Output artifact: Output artifact (Text/code file): Deep mode scored 6% top-1, 12.8% top-3, 28% top-10 on 47 answerable queries; $50.00 per 1k queries; p50 5,394 ms; p95 9,441 ms; 0 errors. — LINKUP-scored-run-export.csv

What changed: Text/code file transformed into Text/code file

Why it matters / Conclusion: Retrieval is the weakest part of Linkup, and deep does not improve it enough to justify the cost.

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.

csv
QUERY-SET-ground-truth.csv
Loading file...
Same fixed benchmark query set used for the deep-mode retrieval run.
↓
csv
LINKUP-scored-run-export.csv
Loading file...
Deep mode scored 6% top-1, 12.8% top-3, 28% top-10 on 47 answerable queries; $50.00 per 1k queries; p50 5,394 ms; p95 9,441 ms; 0 errors.
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
Strong; this is the part that actually works.
▾
Test Summary
Feature tested: Answer-Bearing Page Content Extraction
Result: Passed — Strong; this is the part that actually works.

Feature tested: Answer-Bearing Page Content Extraction

Result: Passed

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

Expected behavior: 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.

Test case: Text/code file → Text/code file

Input type: Text/code file

Input used: Input artifact (Text/code file): Includes the Q52 no-answer probe used to check abstention behavior. — QUERY-SET-ground-truth.csv

Observed output: Output artifact (Text/code file): Raw per-query log for the fixed benchmark, including the Q52 probe used to test no-answer behavior; the report still treats that limit as pending rather than fully closed. — LINKUP-per-query-output.md

Input artifact: Input artifact (Text/code file): Includes the Q52 no-answer probe used to check abstention behavior. — QUERY-SET-ground-truth.csv

Output artifact: Output artifact (Text/code file): Raw per-query log for the fixed benchmark, including the Q52 probe used to test no-answer behavior; the report still treats that limit as pending rather than fully closed. — LINKUP-per-query-output.md

What changed: Text/code file transformed into Text/code file

Why it matters / Conclusion: Extraction is a real strength, but the Q37 length contradiction still needs a raw-JSON reconciliation before publishing.

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.

csv
QUERY-SET-ground-truth.csv
Loading file...
Includes the Q52 no-answer probe used to check abstention behavior.
↓
md
LINKUP-per-query-output.md
Loading file...
Raw per-query log for the fixed benchmark, including the Q52 probe used to test no-answer behavior; the report still treats that limit as pending rather than fully closed.
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

TESTED
standard
$5.00 / 1k queries
Cheaper and faster tier; still the better value despite weak ranking.
TESTED
deep
$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.

✓ Use This 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 This 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
developer-toolssearch-enginetextStudentFounderMarketingTeacherCreatorEditorOther
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.
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%).
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.
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.
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.

Banner Preview

How the embed badge will look on your site

Linkup featured on AI Demos

Embed HTML

Copy this code to your website source

<a target="_blank" href="https://aidemos.com/tools/linkup?utm_source=linkup_embed" style="width: 250px; height: 80px; border-radius:4px;" width="250" height="80"> <img src="https://aidemos-website-images.s3.amazonaws.com/featured.png" alt="Linkup | Featured on AI Demos" style="width: 250px; height: 80px; border-radius:4px;" width="250" height="80"> </a>

Quick Integration Guide

  • 1Copy the HTML code block above.
  • 2Paste it into your site's HTML or CMS editor.
  • 3Banner appears instantly on your page.
  • 4Links back to your tool profile here.
Similar Tools

Similar Tools

Discover more AI tools like Linkup to enhance your workflow.

🤖
Exa
Best live-web search API here for agents that need ranked results, long page text, and cited answers.
AI Tool
🤖
Jina
Rich web search results for agents, but this free-tier run was incomplete and not comparable.
AI Tool
🤖
Olostep
A search-only baseline with mid-pack retrieval, weak extraction, and no usable answer mode.
AI Tool
🤖
OpenAI web_search
AI Tool
🤖
SerpAPI
Fast, zero-error live web search for agents, with stable mid-pack retrieval and snippet outputs.
AI Tool
🤖
Serper
Fast, cheap raw web search for agents — strong on ambiguity, but too snippet-thin to replace a scrape.
AI Tool
🤖
Tavily
A web search API that returns full-page text well, but usually buries the best result.
AI Tool
🤖
Valyu
Returns usable web text for agents, but the citation layer is too error-prone to trust.
AI Tool
🤖
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.
AI Tool

Comments (0)

Please Log in to join the discussion.

Built by FutureSmart AI — the team behind AI Demos

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.

Get a custom build

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.

Back to Top