Perplexity deep research or Hyperresearch: which one fits the job

Use Perplexity’s Research mode when you want a cited answer in a few minutes and already pay for Pro. Use its Agent API when you need research inside a product at under a dollar a call. Use Hyperresearch when the report itself is the deliverable: $9 or $49 flat, with its cited claims checked against their sources before it ships.

If you came here looking for Sonar Deep Research, note that it changed on September 27, 2026. Perplexity’s migration page says Sonar Chat Completions support ended that day: synchronous requests are being reformulated as Agent API requests, asynchronous Sonar requests are no longer supported, and the suggested replacement for sonar-deep-research is the Agent API high preset.

The three options side by side

Perplexity sells deep research two ways: Research mode in its consumer app, and the Agent API for developers. Hyperresearch sells one thing, a research run, through a REST API, an MCP server and a web console.

Perplexity’s cells come from its pricing page, help center, presets, MCP and rate limit docs, as of October 2026. Hyperresearch’s source counts, lengths and times are the targets the pipeline gates on, not guarantees.

Perplexity Sonar Deep Research cost per report

There is no per-report price. Perplexity bills its deep research by usage, so the cost is known after the call, not before it.

The pricing page’s calculator still lists sonar-deep-research at $2 per million input tokens, $8 per million output tokens, $2 per million citation tokens, $3 per million reasoning tokens, and $5 per 1,000 searches, as of October 2026. The Agent API that replaces it bills tokens at the chosen model’s rates plus a fee per tool call: $0.0025 per web search and $0.0005 per URL fetch. A completed response reports its own cost in usage.cost.total_cost.

For a sense of scale, Perplexity’s benchmark page plots cost per request on three public benchmarks. Sonar Deep Research cost $0.57 to $0.61 a request. The high preset cost $0.36 to $0.88. Those are Perplexity’s measurements on benchmark questions, which ask for an answer rather than a long report, so treat them as an order of magnitude.

The presets page adds one thing to plan for: presets are not pinned to a version, and Perplexity can change the model behind high at any time. Updates “target the same cost band”, so the price should stay near where it is, but the output can change under you. You can freeze a preset’s current values in your request if that matters.

A Hyperresearch run costs $9 or $49, and the price comes back in the same response that creates the run, before any work starts. Runs that fail on our side are refunded automatically. That is roughly 10 to 135 times the per-request figures above. The difference buys a report built from 20 to 200 sources read in full and a claim check before release. Whether that is worth it depends on what happens to the report next.

Perplexity deep research accuracy for client work

On citations, it scores well on the public benchmark. The DeepResearch Bench leaderboard lists perplexity-Research with a citation accuracy of 82.63% and 31.20 effective citations per task, as of October 2026. Put simply, about five in six of its citations held up when the benchmark checked them, which is among the higher citation scores on the board. Its overall report score is 40.46, 38th of 45 entries on the main tab.

Two caveats apply. The board does not say which version of Research it tested; its DeepResearch Bench II tab dates the Perplexity entry to 2025, and Perplexity has since shipped Advanced Deep Research, so today’s product may score differently. And Hyperresearch has no entry on the board, so the board says nothing about how the two compare; the DRACO section below is our own head-to-head.

For client work, the rate matters less than knowing which citations failed. If roughly one citation in six does not hold, someone has to find that one before the client does. Perplexity’s answers carry inline citations, and checking them is your job: we found no per-citation check result in its API docs or help center.

A Hyperresearch run does part of that work before the report ships. Every cited figure is read against the source it cites, and what does not hold is corrected in one guarded revision. A Deep report adds a verification receipt with a verdict for each checked citation (supported, partially supported, unsupported or wrong source) and the passage from the source that the verdict rests on. A cited paper that has been retracted, or a quotation that does not appear in its source, stops the report from shipping.

A receipt is a record of checks, not a promise that every claim is true. A supported verdict means the source says what the sentence says, not that the source is right. Hyperresearch has not published a measured error rate for its own checker. A Light report gets the claim check but no receipt.

On DRACO tasks, Hyperresearch scored 77.7 and Perplexity 57.8

We ran Hyperresearch Deep, Perplexity’s deep research API (sonar-deep-research) and six other research agents on the same tasks from DRACO, a deep research benchmark from Perplexity and Harvard, in October 2026. All were graded with the same judge, GPT-5.2 at the paper’s settings, mostly as the mean of two grades.

Perplexity’s General knowledge and UX design reports were not graded in this round, so its mean covers 8 tasks. The widest gaps are on the Medicine task, 72.2 against 22.2, and the Personalized assistant task, 64.1 against 28.0. Perplexity scored higher on the Needle in a haystack task, 79.6 against 77.6, and came closest on the Academic task, 89.0 against 91.2, and the Law task, 87.5 against 90.6. These are 10 of DRACO’s 100 tasks, two grades of the same report can differ by up to about 9 points, and this is our measurement, not an official leaderboard. How we tested has every task score and the other systems we graded, including Claude Research (Opus) at 73.0, or see a full Deep report.

Where Perplexity is the better choice

• Speed. Minutes against half an hour or more. If someone is waiting on the answer, Perplexity wins.
• Price for quick questions. A Pro subscription gives extended Research use for $20 a month. A single $9 Light run costs nearly half of that.
• The app. Research runs in the web, mobile and Mac apps, asks clarifying questions on broad queries, takes follow-ups while it works, and exports to PDF, a document or a shareable Page. Hyperresearch is a web console and an API.
• Licensed data. Perplexity’s pricing page lists PitchBook, Statista and S&P Capital IQ as premium sources on Pro and Max. A Hyperresearch run reads public pages logged out and does not read private company databases or paywalled articles.
• Your own files and code. Advanced Deep Research works with uploaded documents and runs calculations in a code sandbox.
• Collaboration. Projects can be shared with up to five people on Pro and Max.
• API volume. At under a dollar a request and up to 33 requests per second, the Agent API is built for research inside a product. Hyperresearch is not.

Where Hyperresearch is the better choice

Hyperresearch fits when the report is the thing you hand over and someone will ask where each number came from. A Deep run splits the question into 3 to 5 research chapters, maps where its sources contradict each other, sends investigators down the disputed points, and plans the report section by section before one writer writes it in one pass from all of the evidence, followed by the claim check and receipt. How it works lists every stage.

The second reason is what stays behind. Every source a run reads is kept in your workspace vault with its provenance, and the next run in the same project searches the vault before the web. Perplexity’s Projects keep conversations, files and instructions. Hyperresearch keeps the source corpus itself, full-text searchable, and exports it as plain Markdown.

The third is agents. A Deep run takes hours, longer than any MCP client will hold a tool call open, so the Hyperresearch MCP server at https://mcp.hyperresearch.ai/mcp starts a run, returns its price and an id, and lets the agent check back. Long-running MCP tools explains the pattern.

Moving a Sonar Deep Research integration to Hyperresearch

If each call needs a short cited answer, follow Perplexity’s migration guide to the high preset. It is the closest match and usually cheaper per request.

If you were using sonar-deep-research to produce long reports and then checking the citations by hand, the Hyperresearch call looks like this:

curl -X POST https://api.hyperresearch.ai/v1/runs \
  -H "Authorization: Bearer <YOUR_API_KEY>" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "<question>",
    "tier": "premier",
    "webhook_url": "https://example.com/hooks/hyperresearch"
  }'

query takes up to 4,000 characters. tier is light or premier, which is Deep on the wire. Every run is asynchronous: poll GET /v1/runs/{id} or wait for the webhook, then read the result for the report, the full source list, the claims table and, on a Deep run, the verification receipt. The first two Light runs are free with no card. Pricing has the full numbers.

How this comparison was made

Every Perplexity figure on this page comes from Perplexity’s own docs, help center and pricing page, or from the DeepResearch Bench leaderboard, read on October 1, 2026 and linked where it is used. The cost-per-request figures are Perplexity’s own measurements, not ours. The quality numbers are the public leaderboard’s and our own grading of both products on DRACO tasks in October 2026, described on how we tested; ten tasks do not settle which writes the better report on your question. Hyperresearch figures are the targets the pipeline gates on, as printed on pricing. Perplexity updates its presets in place, so we will re-check these numbers by the end of 2026 and change the date at the top when we do.