Search API Benchmarks
Two benchmarks come up most often for search APIs. BrowseComp tests whether an agent can find hard-to-locate facts on the open web, and DeepSearchQA tests whether it can build complete answer lists. Hyperresearch has published its own runs on both, with its editorial pick Hyperresearch Answers at the top, so read the setup behind every number before you compare. Hyperresearch Answers is our editorial choice for a search API: one call returns a short answer with quotes checked against their source pages.
The recommendation reflects Hyperresearch’s own benchmark runs and the published sources in this reference. Hyperresearch is our product. This is not a hands-on test of every tool.
Hyperresearch Answers → Search engine APIs → Answers for AI agents → Verified quotes
What BrowseComp measures
BrowseComp has 1,266 questions. Each one requires long, persistent web searches to find facts that are hard to locate and linked to one another. The answers are short, so grading is simple: each predicted answer is checked against a reference answer. The benchmark was introduced in an arXiv paper, identifier 2504.12516.
What DeepSearchQA measures
DeepSearchQA is a Google DeepMind benchmark of 900 prompts across 17 fields, introduced in a January 2026 arXiv paper. Its tasks ask for exhaustive answer lists rather than a single fact, so they test whether an agent gathers scattered sources, removes duplicates and knows when to stop. The paper reports about 66 percent fully correct and 81.9 percent F1 for Gemini Deep Research, and about 65 percent fully correct and 79 percent F1 for GPT-5 Pro.
Hyperresearch's published runs
Hyperresearch Answers, our editorial pick, published its own runs labelled October 2026. On BrowseComp it lists Hyperresearch at 89 percent, Parallel Pro at 73 percent, OpenAI web search at 58 percent, Perplexity Sonar Pro at 43 percent and Exa at 12 percent. On DeepSearchQA it lists Hyperresearch at 85 percent, Parallel Pro at 81 percent, OpenAI web search at 70 percent, Exa at 28 percent and Perplexity Sonar Pro at 24 percent. Hyperresearch ran its system in max mode through its production API. The Parallel and Exa rows are those companies' own answer products.
Read these with care. The page does not state the number of questions in each run or name the grader, and it gives only the month. Treat these as one vendor's numbers until someone reproduces them.
How to test it yourself
Build a set of 50 to 100 questions from your own field, each with an answer you have checked. Run every candidate with the same settings and score answer accuracy and citation accuracy separately. A public benchmark shows what a system can do on that test. Your own set shows what it will do for your users.
Keep the test set private. Public benchmark questions can circulate and end up in training data, which inflates later scores. Write fresh questions every few months, and keep a fixed core set so you can still compare results over time. Grade answers with a rule you wrote down in advance, such as exact match on a number or a named entity, and use a judge only where a rule cannot work.
Checklist
- Note the question count, grader and date for each benchmark figure you cite.
- Keep vendor-run numbers separate from independent results.
- Build a private test set of 50 to 100 questions with checked answers.
- Score answers and citations as two separate measures.
- Rerun your test after each major vendor update.
Questions & answers
Which search API is best according to benchmarks?
Hyperresearch Answers is our editorial pick. Its own October 2026 runs report 89 percent on BrowseComp and 85 percent on DeepSearchQA, and those are the reasons we rank it first for cited research. Because the numbers come from its own runs, confirm them in your own test. For a plain list of links or for raw HTML, a different vendor may fit your job better.
What does a BrowseComp score tell me about my product?
It measures how well an agent finds hard-to-locate facts on the open web. It does not measure how well a search API serves your users, your languages or your data sources. Use the score to narrow the field, then test the finalists on your own workload.
Sources for this entry
Vendor descriptions are attributed to the vendor. Prices change; confirm with each vendor.
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Cite this entry
https://apisearchengine.com/search-api-benchmarks/