Linkup
Standard mode is the usable tier: strong extraction, weak ranking; deep is slower, pricier, and weaker.
Standard is the useful tier; deep is not worth the tradeoff.
- 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
- you need strong top-1/top-3 retrieval on content-depth or ambiguity queries
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.
Feature-by-Feature Breakdown
Live Web Retrieval and Result RankingWeak 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.
Answer-Bearing Page Content ExtractionStrong; 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.
How it scored on the research's own criteria
The 11 evaluation dimensions from our hands-on research on Linkup, each judged from recorded runs on 5 test inputs — the same verdicts the ranking page ranks on.
held up partial failed not exercised by this input
| Criterion | Verdict | What the runs showed | Per input | Proof |
|---|---|---|---|---|
| Ambiguity handling | Weak1/5 | It does not reliably separate lookalike entities; the right target never showed up early in the ambiguous-name tests. | open proof ↗ | |
| Answer quality (answer APIs) | Mixed3/5 | It gets a fair share of answer-mode questions right and usually knows when to stay quiet, but the repeated wrong-base-year and source-extraction misses keep it below strong territory. | open proof ↗ | |
| Citation accuracy (answer APIs) | Mixed3/5 | Most answer-mode citations resolve correctly, but a meaningful minority are wrong or incomplete, so the citation trail is useful but not fully dependable. | open proof ↗ | |
| Extraction quality | Strong4.5/5 | Even when it misses the exact URL, it still returns enough text to recover the answer, so the content it brings back is strong rather than snippet-thin. | open proof ↗ | |
| Freshness | Weak2/5 | It does reach some recent material, but only about a third of the freshness probes made top-3 in either mode, which is too spotty to call it fresh. | open proof ↗ | |
| Long-tail coverage | Mixed3/5 | It can surface some niche technical pages, but a one-in-four top-3 hit rate says the coverage is real yet limited, not broad. | open proof ↗ | |
| No-answer behaviour | Weak1/5 | On probes that should have triggered caution, it still volunteered specific numbers and unrelated facts, so its hold-back behavior is badly broken. | open proof ↗ | |
| Relevance @ top-k | Weak1/5 | On the checked GDPR query, it missed the supporting page completely in the early results, so the core top-k relevance test failed rather than merely wobbling. | open proof ↗ | |
| Cost per 1k queries | Weak2/5 | The expensive tier is dramatically pricier without delivering better retrieval, so the value proposition is poor. | open proof ↗ | |
| p50 / p95 latency | Weak2/5 | The slower mode adds a lot of wait time, especially at the tail, so the user experience is materially sluggish. | open proof ↗ | |
| Stability | Mixed3/5 | Its broad standing is fairly repeatable, but the leader board shifts enough that the ranking is only moderately stable, not truly steady. | open proof ↗ |
Verdicts come verbatim from the study's recorded observations, never re-derived at render; a criterion with no recorded run shows Not exercised — this section cannot invent a score.
Run-derived cost per 1k queries
Measured from the 2026-08-16 run in ap-south-1
These are benchmark-derived all-in costs from the test run, not vendor list pricing.
Featured in Rankings
Independent rankings where Linkup was tested and rated.
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