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Olostep

A search-only baseline with mid-pack retrieval, weak extraction, and no usable answer mode.

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52-search-call runAnswer mode blockedJoint-worst extractionEstimated pricing
TL;DR — our verdictUpdated August 2026 · 2 test artifacts

Search completes, but the answer layer is blocked.

Where it wins
  • you only need a search endpoint that completes basic query calls reliably
  • you can work with SERP-style snippets instead of full extracted page text
  • you are benchmarking a search-layer baseline and can tolerate mid-pack retrieval quality
Main limitation
  • you need a working answer API with verified citations
Strongest test artifacts

Our take

Olostep's `/search` endpoint completed all 52 calls with zero errors, but the benchmark does not support choosing it over stronger alternatives. It is weak on ambiguity and multi-source retrieval, usually returns SERP-style snippets rather than usable extracted text, omits published dates, and `/answers` returned HTTP 402 on every attempt, so there is no citation evidence to trust.

In-Depth Review

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

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AI Demos Team
Expert Reviewer
Verified Review

Feature-by-Feature Breakdown

Web search retrieval
Test Summary
Feature tested: Web search retrieval
Result: Passed

Feature tested: Web search retrieval

Result: Passed

Expected behavior: Olostep can take a plain-text query set and return ranked web results from its `/search` endpoint. In the benchmark, those results came back as SERP-style snippets with a median length of 161 characters and no published dates, so this card includes the retrieval output format and metadata behavior exercised on the same search calls.

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

Input type: Text/code file

Input used: Input artifact (Text/code file): Ground-truth query set used for the same-input benchmark. — QUERY-SET-ground-truth.csv

Observed output: Output artifact (Text/code file): Search run scored on the same-input benchmark: 52/52 successful calls with zero errors across both runs; retrieval scores were top-1 28%, top-3 38%, and top-10 55%. Per-block top-3 scores were current fact 60%, niche tech 42%, ambiguity 14%, multi-source 0%, content-depth 67%, and freshness 33%. — OLOSTEP-scored-run-export.csv

Input artifact: Input artifact (Text/code file): Ground-truth query set used for the same-input benchmark. — QUERY-SET-ground-truth.csv

Output artifact: Output artifact (Text/code file): Search run scored on the same-input benchmark: 52/52 successful calls with zero errors across both runs; retrieval scores were top-1 28%, top-3 38%, and top-10 55%. Per-block top-3 scores were current fact 60%, niche tech 42%, ambiguity 14%, multi-source 0%, content-depth 67%, and freshness 33%. — OLOSTEP-scored-run-export.csv

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

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

Input type: Text/code file

Input used: Input artifact (Text/code file): Content-depth and freshness probe queries from the same benchmark. — QUERY-SET-ground-truth.csv

Observed output: Output artifact (Text/code file): Returned snippets were short and metadata-light: median 161 characters per result, 0% published dates, and extraction quality 1.33. The report notes that the right page was often ranked, but the answer-bearing figure was usually not included in the returned text. — OLOSTEP-per-query-output.md

Input artifact: Input artifact (Text/code file): Content-depth and freshness probe queries from the same benchmark. — QUERY-SET-ground-truth.csv

Output artifact: Output artifact (Text/code file): Returned snippets were short and metadata-light: median 161 characters per result, 0% published dates, and extraction quality 1.33. The report notes that the right page was often ranked, but the answer-bearing figure was usually not included in the returned text. — OLOSTEP-per-query-output.md

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

Why it matters / Conclusion: Reliable enough to issue search calls, but ranking quality is only moderate and clearly weak on ambiguity and multi-source questions.

Olostep can take a plain-text query set and return ranked web results from its `/search` endpoint. In the benchmark, those results came back as SERP-style snippets with a median length of 161 characters and no published dates, so this card includes the retrieval output format and metadata behavior exercised on the same search calls.

file
QUERY-SET-ground-truth.csv
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Ground-truth query set used for the same-input benchmark.
file
OLOSTEP-scored-run-export.csv
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Search run scored on the same-input benchmark: 52/52 successful calls with zero errors across both runs; retrieval scores were top-1 28%, top-3 38%, and top-10 55%. Per-block top-3 scores were current fact 60%, niche tech 42%, ambiguity 14%, multi-source 0%, content-depth 67%, and freshness 33%.
file
QUERY-SET-ground-truth.csv
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Content-depth and freshness probe queries from the same benchmark.
file
OLOSTEP-per-query-output.md
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Returned snippets were short and metadata-light: median 161 characters per result, 0% published dates, and extraction quality 1.33. The report notes that the right page was often ranked, but the answer-bearing figure was usually not included in the returned text.
Bottom Line
Reliable enough to issue search calls, but ranking quality is only moderate and clearly weak on ambiguity and multi-source questions.
Direct answer API
Test Summary
Feature tested: Direct answer API
Result: Passed

Feature tested: Direct answer API

Result: Passed

Expected behavior: Olostep exposes an `/answers` mode intended to return direct answers. In the benchmark smoke tests, every attempt returned HTTP 402, so no answer content, citation output, or abstention behavior could be evaluated.

Test case: Text prompt → Text prompt

Input type: Text prompt

Input used: Input artifact (Text prompt): INPUT

Observed output: Output artifact (Text prompt): Output

Input artifact: Input artifact (Text prompt): INPUT

Output artifact: Output artifact (Text prompt): Output

What changed: Text prompt transformed into Text prompt

Why it matters / Conclusion: Unusable in this test tier; the benchmark has no citation or answer-quality data for Olostep's answer mode.

Olostep exposes an `/answers` mode intended to return direct answers. In the benchmark smoke tests, every attempt returned HTTP 402, so no answer content, citation output, or abstention behavior could be evaluated.

INPUT
Five `/answers` attempts across the unanswerable-query smoke test, repeated over both runs.
OUTPUT
HTTP 402 on all five attempts across both runs. No usable answer, no citations, and no abstention record were produced.
Bottom Line
Unusable in this test tier; the benchmark has no citation or answer-quality data for Olostep's answer mode.

How it scored on the research's own criteria

The 11 evaluation dimensions from our hands-on research on Olostep, each judged from recorded runs on 2 test inputs — the same verdicts the ranking page ranks on.

held up  partial  failed  not exercised by this input

CriterionVerdictWhat the runs showedPer inputProof
Ambiguity handlingWeak1/5When names could mean multiple things, it often missed the intended entity. The very low top-3 rate shows a core failure, not just a mild weakness.open proof ↗
Answer quality (answer APIs)Weak1/5On a query that should have had no answer, it still produced a specific number. That is a direct answer-quality failure because it answered confidently when it should have held back.open proof ↗
Citation accuracy (answer APIs)Weak1/5There were no citations to check because every attempt was quota-blocked. With no verifiable cited URL at all, the citation path failed at the first step.open proof ↗
Extraction qualityWeak1/5It usually returned short snippets instead of the full content an agent would actually use. Since it often found the page but not the needed figure, extraction is effectively broken for practical use.open proof ↗
FreshnessWeak2/5It sometimes surfaced fresh material, but the low top-3 rate and lack of visible dates make recency hard to trust. That is weaker than mixed performance and lands below average.open proof ↗
Long-tail coverageWeak2/5It handled straightforward queries better than niche or multi-source ones, and the multi-source block collapsing to zero shows the weakness clearly. That is a struggling result rather than a mixed one.open proof ↗
No-answer behaviourWeak1/5Instead of cleanly saying it had no answer, it hard-refused every probe. That means the endpoint did not provide a usable no-answer path.open proof ↗
Relevance @ top-kMixed3/5The search mode usually found the right page, but it did not land near the top often enough to count as strong retrieval. That fits a middle score: useful, but not reliably top-ranked.open proof ↗
Cost per 1k queriesMixed3/5The search price is not extreme, but the estimate-only basis and the unusable answer mode make the economics only middling. It is not clearly cheap, and it is not clearly expensive either.open proof ↗
p50 / p95 latencyMixed3/5The median response time is usable, but the tail grows a lot slower than the median. That kind of spread makes it acceptable rather than fast.open proof ↗
StabilityMixed3/5Results were mostly reproducible, but the rerun still moved enough to matter. The high agreement keeps it from being poor, while the drop keeps it from being strong.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.

✓ Use This If
you only need a search endpoint that completes basic query calls reliably
you can work with SERP-style snippets instead of full extracted page text
you are benchmarking a search-layer baseline and can tolerate mid-pack retrieval quality
✕ Skip This If
you need a working answer API with verified citations
you need strong ambiguity resolution or multi-source retrieval
your agent needs usable extracted content and published dates from the first call
you need low p95 latency
developer-toolssearch-enginetextOther
Yes. The report says `/search` completed all 52 calls with zero errors across both runs.
Overall retrieval on the 47 answerable queries was 28% top-1, 38% top-3, and 55% top-10. It was strongest on current facts (60% top-3) and weakest on ambiguity (14% top-3) and multi-source queries (0% top-3).
It returned SERP-style snippets. The report says the median returned content was 161 characters per result and 0% of results included published dates. Extraction quality was scored 1.33, which was joint-worst.
Every `/answers` attempt returned HTTP 402. The benchmark therefore has no answer-quality, citation, or abstention data for Olostep.
For `/search`, the report estimates about $9.00 per 1,000 queries and shows p50 latency of 3,560 ms and p95 latency of 8,201 ms. The cost is explicitly labeled an estimate, not a measured response-derived figure. `/answers` was estimated at about $36 per 1,000 calls but did not run successfully.

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