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VerdictPal · editorial desk · 2026VerdictPal
Compare · Head-to-head

Pick two cards. See the diff.

Stat bars are editorial heuristics, methodology linked — not a fake benchmark leaderboard. Put two dossiers side by side and see where each one breaks.
CardsModels

Compare · Card A / Card B·Head-to-head

KagivsPerplexity

In the AI search set, Kagi edges ahead overall (editorial fit 92 vs 72). Kagi wins on citation honesty, source quality, privacy controls, and value for money; the rest is a wash. For the canonical workflow, pick Perplexity. Use Kagi when its niche specifically wins above.

Kagi · avg
83
wins 14 of 16
Perplexity · avg
64
wins 0 of 16
Fields differ
13
of 16 dossier rows
Receipts
21
sources + bench notes

Checked 2026-06-09 · Kagi·Checked 2026-06-07 · Perplexity

Dossier fields

Sixteen fields, side by side.

No.FieldKagiPerplexity
01Status · Editorial quality gateSolidFlagship
02Editorial fit · 0–100 score92 / 10072 / 100
03CategoryAI searchAI search
04Primary surfaceProsumer SaaSConsumer app
05Modalities
  • Text
  • Text
06Role in a stackPrivate paid web search and AI-search alternativeCited search front door and web-grounded API platform
07Best for
  • Users who want ad-free search without behavioral advertising
  • Research workflows that benefit from domain ranking, blocking, pinning, lenses, and lower SEO sludge
  • Privacy-conscious users willing to pay instead of trading search behavior for ads
  • People who want a web-search baseline before using Perplexity, ChatGPT, or Google AI summaries
  • First-pass source maps before opening library databases or primary sources
  • Policy, news, product, and current-web questions where dated URLs matter
  • Deep Research drafts that need a starting citation trail
  • Developers evaluating Sonar/Search APIs for web-grounded product features
08Avoid if
  • You need free unlimited search
  • You will not benchmark result quality against your current baseline before paying
  • You need formal institutional guarantees for every Kagi Assistant model/provider path before use
  • You want an academic database or systematic-review tool rather than cleaner general web search
  • You plan to paste the answer into a graded bibliography without opening every citation
  • Your institution forbids cloud processing or model improvement on student writing and you have not verified the exact account tier/settings
  • You need paywalled PDF full text or library-grade systematic review coverage
  • You assume the consumer subscription and API platform have identical privacy, retention, and billing terms
09Capabilities tracked
  • Paid ad-free search
  • 100-search trial
  • Starter 300 searches/mo
  • Professional unlimited search
  • Ultimate Premium AI/Research mode
  • result ranking/blocking/pinning/lenses
  • Kagi Assistant
  • Privacy Pass and Tor/onion support
  • PayPal/OpenNode payment
  • fair-pricing credit
  • Consumer answer engine with inline citations
  • Pro Search
  • Deep Research
  • Spaces/files
  • model selection on higher tiers
  • Enterprise controls
  • Sonar API
  • Search API
  • Agent API
  • Embeddings API
  • OpenAI-compatible API path
10Failure modes · Documented, not buried
  • Paid search only makes sense if result quality beats baseline
  • Starter quota can be too small for heavy researchers
  • Assistant privacy depends on Kagi plus third-party model providers
  • Research mode and flagship models require Ultimate
  • Cloud search still needs trust
  • Custom ranking can create a filter bubble
  • Pro tier changes can degrade value for existing subscribers without clear migration
  • Deep Research can sound comprehensive while missing primary/paywalled sources
  • Consumer/Enterprise/API terms differ
  • API usage is pay-as-you-go and separate from consumer subscriptions
  • Source weighting may over-rank popular pages
  • Quotas can interrupt heavy workflows
11Evidence levelEditorial · hands-onEditorial · hands-on
12Sources verified · Receipts on the dossier
13Benchmark entries
  • Run 25 research, product, local, and navigational queries against Kagi, Google, Brave, DuckDuckGo, Perplexity, and You.com.
    Pending.
  • Apply ranking/blocking/pinning/lenses for a research domain and rerun 10 queries.
    Pending.
  • Run 10 Assistant questions on public sources only; inspect model/provider path, retention controls, and answer citations.
    Pending.
  • Run 25 questions across policy, product, academic-adjacent, technical-docs, and local/current events.
    Pending.
  • Generate 5 Deep Research briefs and manually classify every cited source.
    Pending.
  • Compare Sonar/Search API against Exa, You.com, Brave, and Scira API on 20 prompts.
    Pending.
  • Inspect consumer settings, enterprise docs, and API terms for data retention/training boundaries.
    Pending.
14Alternatives tracked
  • Perplexity
  • You.com
  • Google Search
  • Brave Search
  • DuckDuckGo
  • ChatGPT
  • Gemini
  • Claude
  • You.com
  • Kagi
  • Scira AI
15Pricing checked2026-06-092026-06-07
16Last verified2026-06-092026-06-07
16 metrics

Sixteen numbers, one shared midline.

KagivsPerplexity

In the AI search set, Kagi edges ahead overall (editorial fit 92 vs 72). Kagi wins on citation honesty, source quality, privacy controls, and value for money; the rest is a wash. For the canonical workflow, pick Perplexity. Use Kagi when its niche specifically wins above.

  1. Editorial fit
    Kagi92Perplexity72
  2. Source quality
    Kagi76Perplexity68
  3. Citation honesty
    Kagi88Perplexity56
  4. Privacy controls
    Kagi96Perplexity36
  5. Value for money
    Kagi74Perplexity52
  6. Speed
    Kagi86Perplexity85
  7. Integration
    Kagi78Perplexity70
  8. Onboarding
    Kagi86Perplexity85
  9. Reliability
    Kagi88Perplexity76
  10. Feature depth
    Kagi86Perplexity64
  11. Data portability
    Kagi59Perplexity55
  12. Transparency
    Kagi98Perplexity65
  13. Ecosystem reach
    Kagi78Perplexity70
  14. Documentation
    Kagi76Perplexity68
  15. Independence
    Kagi96Perplexity36
  16. Affordability
    Kagi68Perplexity62
Kagi · avg 83 · wins 14 of 160avg 64 · wins 0 of 16 · Perplexity
EvidenceKagi 4 · Perplexity 0
  1. 01Editorial fit
    92
    72
  2. 02Source quality
    76
    68
  3. 03Citation honesty
    88
    56
  4. 04Privacy controls
    96
    36
PrivacyKagi 2 · Perplexity 0
  1. 05Value for money
    74
    52
  2. 06Speed
    86
    85
  3. 07Integration
    78
    70
  4. 08Onboarding
    86
    85
CapabilityKagi 4 · Perplexity 0
  1. 09Reliability
    88
    76
  2. 10Feature depth
    86
    64
  3. 11Data portability
    59
    55
  4. 12Transparency
    98
    65
Cost & fitKagi 4 · Perplexity 0
  1. 13Ecosystem reach
    78
    70
  2. 14Documentation
    76
    68
  3. 15Independence
    96
    36
  4. 16Affordability
    68
    62
CARD A · Kagi
AI search
Kagi
92/100
ROLEPrivate paid web search and AI-search alternative
Editorial fit
92
Source quality
76
Citation honesty
88
Privacy controls
96
Value for money
74
Speed
86
FREETrial
$5/MOStarter
$10/MOProfessional
SolidVerified 2026-06-09VP·METHOD

Private paid web search and AI-search alternative — User-funded, ad-free search engine with paid web search, result controls, privacy-oriented defaults, Privacy Pass/Tor support, and optional Kagi Assistant modes.

CARD B · Perplexity
AI search
Perplexity
72/100
ROLECited search front door and web-grounded API platform
Editorial fit
72
Source quality
68
Citation honesty
56
Privacy controls
36
Value for money
52
Speed
85
FREEFree
$20/MOPro
$200/MOMax
FlagshipVerified 2026-06-07VP·METHOD

Cited search front door and web-grounded API platform — Cited answer engine and AI search platform with consumer Pro/Max search, Deep Research, Spaces/files, and developer APIs including Sonar, Search, Agent, and Embeddings.

Privacy facets

Where each card is actually private.

KagiPerplexity
Training on your dataUnknownUnknown: Not statedUnknownUnknown: Not stated
EU data residencyNoNo: Not documentedPartialPartial: Enterprise tier only
SOC 2 attestationNoNo: Not documentedNoNo: Not documented
Local-first by defaultNoNo: Cloud onlyNoNo: Cloud only
Capability split

What each card does uniquely.

Only Kagi10

  • Paid ad-free search
  • 100-search trial
  • Starter 300 searches/mo
  • Professional unlimited search
  • Ultimate Premium AI/Research mode
  • result ranking/blocking/pinning/lenses
  • Kagi Assistant
  • Privacy Pass and Tor/onion support
  • PayPal/OpenNode payment
  • fair-pricing credit

Shared0

No overlap detected.

Only Perplexity10

  • Consumer answer engine with inline citations
  • Search API
  • Deep Research
  • Spaces/files
  • model selection on higher tiers
  • Enterprise controls
  • Sonar API
  • Agent API
  • Embeddings API
  • OpenAI-compatible API path
Failure modes

Where each card breaks.

Kagi

  • Paid search only makes sense if result quality beats baseline
  • Starter quota can be too small for heavy researchers
  • Assistant privacy depends on Kagi plus third-party model providers
  • Research mode and flagship models require Ultimate
  • Cloud search still needs trust
  • Custom ranking can create a filter bubble

Perplexity

  • Pro tier changes can degrade value for existing subscribers without clear migration
  • Deep Research can sound comprehensive while missing primary/paywalled sources
  • Consumer/Enterprise/API terms differ
  • API usage is pay-as-you-go and separate from consumer subscriptions
  • Source weighting may over-rank popular pages
  • Quotas can interrupt heavy workflows
Pricing

Pulled straight from each dossier.

Kagi

AI search
  • FREETrial
  • $5/MOStarter
  • $10/MOProfessional

raw · Trial free: 100 searches + 100 Assistant interactions · Starter USD 5/mo: 300 searches · Professional USD 10/mo: unlimited search · Ultimate USD 25/mo: Premium AI, Research mode, flagship models · annual −10% · unused-month credit.

Perplexity

AI search
  • FREEFree
  • $20/MOPro
  • $200/MOMax

raw · Consumer pricing should be checked against live Perplexity pricing before publication; prior desk data lists Free, Pro, Max, Education Pro, Enterprise Pro, and Enterprise Max. API pricing is separate: Sonar has token pricing and request fees by context size; Search, Agent, and Embeddings are separate API surfaces.

Verdict

Which card to actually pick.

In the AI search set, Kagi edges ahead overall (editorial fit 92 vs 72). Kagi wins on citation honesty, source quality, privacy controls, and value for money; the rest is a wash. For the canonical workflow, pick Perplexity. Use Kagi when its niche specifically wins above.

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