Complete Comparison of 15 Native Search Engines: In-Depth Analysis from Indexing Mechanisms to Application Scenarios

Why Make This Comparison?

In daily information gathering, market research, and due diligence, we found that a single search engine's coverage and reliability have clear limitations. To achieve true "multi-engine parallel search + cross-validation," we conducted a systematic evaluation of all 15 search engines natively supported by OpenClaw.

This article builds a complete comparison matrix across eight dimensions: index source, API Key requirement, free quota, monthly cost, result style, Chinese language support, response latency, and stability, and provides recommendations for the best engine combinations for various scenarios.

1. Index Types: The Core Differences Between Search Engines

The most fundamental distinction among search engines is where their data comes from:

Independent index (proprietary crawler)         Relies on third-party index
┌────────────────────┐          ┌────────────────────┐
│ Brave              │          │ DuckDuckGo → Bing  │
│ Mojeek             │          │ Bing (in-house)         │
│ Tavily (AI optimized)    │          │ Gemini → Google    │
│ Exa (semantic index)      │          │ Perplexity → multi-source   │
│ Firecrawl (curated)    │          │ Grok → xAI + X     │
│ Wikipedia (encyclopedia)    │          │ Kimi → Chinese ecosystem     │
│                    │          │ MiniMax → Multi-source aggregation   │
└────────────────────┘          └────────────────────┘

Key insight: Independent index engines (Brave, Mojeek) provide a results perspective completely different from Google/Bing. The true value of cross-validation lies in simultaneously using engines from both index source types.

2. Complete Comparison Matrix

#	Engine	Index Source	Key Required	Free Quota/Month	Starting Paid Plan	Result Style	Chinese	Latency	Stability
1	Brave	Independent index	✅	2,000 requests	$5	Structured JSON	⭐⭐⭐	⚡ 200ms	⭐⭐⭐⭐⭐
2	DuckDuckGo	Bing aggregation	❌	Unlimited	Free	HTML Scraping	⭐⭐⭐	🐢 1-2s	⭐⭐
3	Tavily	AI aggregation	✅	1,000 requests	$20	AI structured summaries	⭐⭐⭐	⚡ 300ms	⭐⭐⭐⭐
4	Wikipedia	Own encyclopedia	❌	Unlimited	Free	Structured JSON	⭐⭐⭐⭐	⚡ 100ms	⭐⭐⭐⭐⭐
5	Bing	Own index	✅	1,000 requests	$7	Structured JSON	⭐⭐⭐⭐⭐	⚡ 200ms	⭐⭐⭐⭐⭐
6	Exa	Semantic index	✅	1,000 requests	$50	Semantic search + content extraction	⭐⭐	⚡ 400ms	⭐⭐⭐⭐
7	Firecrawl	Curated index	✅	500 requests	$19	Structured + full extraction	⭐⭐	🐢 1-3s	⭐⭐⭐
8	Gemini	Google Search	✅	Free tier available	Usage-based	AI-synthesized answers + citations	⭐⭐⭐⭐	⚡ 500ms	⭐⭐⭐⭐⭐
9	Grok (xAI)	Own + X	✅	Subscription required	$30	AI-synthesized answers	⭐⭐⭐	⚡ 500ms	⭐⭐⭐
10	Kimi (Moonshot)	Chinese ecosystem	✅	Free tier available	Usage-based	AI-synthesized answers + citations	⭐⭐⭐⭐⭐	⚡ 400ms	⭐⭐⭐
11	MiniMax	Multi-source aggregation	✅	Free tier available	Usage-based	Structured JSON	⭐⭐⭐⭐	⚡ 300ms	⭐⭐⭐⭐
12	Perplexity	Multi-source + AI	✅	Free tier available	$20	AI-synthesized answers + citations	⭐⭐⭐	⚡ 800ms	⭐⭐⭐⭐
13	Ollama Web	Local LLM	❌	Unlimited	Free (hardware required)	AI-synthesized answers	Depends on model	🐢 2-5s	⭐⭐
14	SearXNG	Multi-engine aggregation	❌	Unlimited	Self-hosted	Structured JSON	⭐⭐⭐⭐	🐢 2-4s	⭐
15	Mojeek	Independent index	❌	Unlimited	Free	Structured JSON	⭐	⚡ 200ms	⭐⭐⭐

3. In-Depth Analysis of Each Engine

🟢 Brave Search, Primary Recommendation

Index source: Independent index (Web Discovery Project, built from anonymous browsing data)

Pros:

Independent index, not reliant on Google/Bing; high result quality and less SEO spam
Structured JSON responses, well-documented API, easy to parse
Free tier of 2,000 requests/month, extremely cost-effective (paid tier starts at $5/month)
Supports Goggles (custom ranking rules)
Very low latency (~200ms)
Privacy-first, does not track users

Cons:

Chinese content coverage is not as good as Bing/Google
Index size is about 10 billion pages, far smaller than Google's hundreds of billions of pages
News timeliness can sometimes lag

Best for: English search, privacy-first use, structured API consumption, independent index verification

🟡 DuckDuckGo, Zero-Cost Fallback

Index source: Aggregates Bing + own crawler (primarily Bing)

Pros:

Zero cost, zero API key, ready to use immediately
Robust privacy protection, does not track users

Cons:

Not an independent index; primarily relies on Bing
HTML scraping is highly unstable (page structures change frequently, high CAPTCHA risk)
No official API (OpenClaw reverse-engineers and parses HTML, which is an experimental feature)
High latency (1-2 seconds), high failure rate
Not recommended as a primary option in production environments

Best for: Emergency backup, zero-cost fallback

🟢 Tavily, AI Agent Native Search

Index source: AI aggregation + own index

Pros:

Designed specifically for AI Agents, returning structured summaries instead of a list of bare links
search_depth: advanced supports JS-rendered pages
The topic parameter supports precise filtering (general/news/finance)
include_answer can directly output AI-generated answer summaries
Good coverage of Mainland China and Hong Kong content

Cons:

The free quota of 1,000 requests/month is somewhat low
Paid tiers are relatively expensive (starting at $20/month)
Limited independent index size
Speed drops noticeably when using search_depth: advanced

Best for: AI Agent consumption, needing summaries rather than links, primary cross-validation

🟢 Wikipedia, Fact-Checking Benchmark

Index source: Own encyclopedia index

Pros:

Zero cost, zero API key
Content is community-reviewed and highly authoritative
Structured JSON API, extremely fast response (~100ms)
Supports 300+ languages

Cons:

Covers only encyclopedia entries, not general search
Poor timeliness (encyclopedia content updates are delayed)
No commercial information, news, or real-time data

Best for: Fact-checking, background knowledge, term definitions, and the 'authoritative baseline' in cross-validation

🟢 Bing, King of Chinese Search

Index source: Own index (the world's second-largest search engine)

Pros:

Own large-scale index, mature and stable
Structured JSON API
Excellent Chinese support (strong in both Traditional and Simplified Chinese, rich content for the Hong Kong market)
Supports the mkt parameter for precise regional search
Free tier of 1,000 requests/month

Cons:

Chinese results have more advertising and SEO pollution
Applying for an API key has some barriers (requires going through Azure Portal)
Once announced the retirement of the Bing Search API (later reversed), creating future uncertainty

Best for: Chinese search, Hong Kong/China market information, corporate and business data

🟡 Exa, Semantic Search Pioneer

Index source: Own semantic index (neural embedding-based)

Pros:

Semantic search (neural + keyword), not mere keyword matching
Strong content extraction capabilities (highlights, text, summaries)
AI-native design, optimized for LLM consumption

Cons:

Expensive ($50/month entry level)
Weak Chinese support
Relatively high latency (~400ms)
Free quota is only 1,000 requests

Best for: In-depth English research, requiring semantic understanding rather than keyword matching

🟡 Firecrawl, Curated Authoritative Sources

Index source: Self-built curated index (focused on news, research, finance, and government sources)

Pros:

Curated authoritative sources, high result quality
Supports deep content extraction + crawling
Proprietary /agent endpoint designed specifically for AI Agents

Cons:

Starts at $19/month
Weak Chinese support
Relatively slow (1-3 seconds)
Free quota is only 500 requests/month

Best for: High-quality English content extraction, in-depth research

🟢 Gemini (Google), World's Largest Index

Index source: Google Search (the world's largest search engine)

Pros:

Backed by the world's largest index from Google Search
AI-synthesized answers + cited sources
Has a free tier
Strong Chinese support

Cons:

AI-synthesized answers may have bias or hallucinations
Requires a Gemini API key (Google Cloud Console)
Pay-as-you-go; service stops when quota is exceeded
Not pure search results; it is an AI-processed answer

Best for: Needing answers rather than a list of links, global-perspective search

🟡 Grok (xAI), Unique Advantage in Social Data

Index source: Own + X/Twitter data

Pros:

Can access real-time X/Twitter content (unique advantage!)
AI-synthesized answers + citations
Less content-moderation filtering, so non-mainstream viewpoints are reachable

Cons:

Requires an xAI subscription ($30/month)
Search results lean heavily toward social media
Mediocre Chinese-language support
API is relatively new; stability remains to be seen

Best for: social trend analysis, real-time news tracking, non-mainstream viewpoints

🟢 Kimi (Moonshot): Top Choice for the Chinese Market

Index source: China's internet ecosystem

Pros:

Extremely strong coverage of the Chinese market
Highest-quality Chinese search
AI-synthesized answers + citations
Deep understanding of Chinese companies, policies, and regulations

Cons:

Limited international perspective
May be affected by Chinese content censorship
API ecosystem is relatively young

Best for: China market research, in-depth Chinese search, due diligence on Chinese companies

🟡 MiniMax: Emerging Multi-Source Aggregation

Index source: Multi-source aggregation

Pros:

Structured results (title + snippet)
Good Chinese support
Has a free tier

Cons:

Low transparency (unclear which index sources are used behind the scenes)
Limited API documentation
Moderate stability

Best for: Chinese structured search fallback

🟡 Perplexity: Benchmark for AI Search Experience

Index source: Multi-source aggregation + AI synthesis

Pros:

Most mature AI-native search experience
Synthesized answers + precise source citations + support for follow-up questions
Powerful academic search capabilities

Cons:

From $20/month
Higher latency (~800ms)
Chinese is not as good as Kimi/Bing
AI-synthesized answers are not necessarily accurate

Best for: English academic research, cases requiring in-depth analysis rather than simple search

🟡 Ollama Web Search: Fully Local

Index source: Powered by a local LLM

Pros:

Runs entirely locally, with zero external dependencies
Free model selection

Cons:

Requires a local GPU or large RAM
Extremely slow (2-5 seconds)
Search quality depends entirely on the selected model
Not suitable for production use

Best for: Experimental scenarios, offline environments

🔴 SearXNG: Ideal vs. Reality

Index source: Theoretically can aggregate 80+ search engines

Pros:

Zero-cost self-hosting
Excellent privacy

Cons:

In actual testing, mainstream engines such as Google and DuckDuckGo block the IPs of self-hosted instances
High maintenance cost
Very few engines are actually usable (testing confirmed it cannot serve as a reliable tool)
We verified it failed in actual deployment and removed it

Best for: ⚠️ Not recommended (failed in testing)

🟡 Mojeek: The Last Truly Independent Index

Index source: Fully independent index (continuously built since 2004, developed in C)

Pros:

Zero cost, zero API key
Truly independent index (one of the world's largest independent search engines)
No tracking at all, excellent privacy
Supports JSON API
Originally from the UK, operating stably since 2004

Cons:

Smaller index size (about 6 billion pages)
Extremely weak Chinese support (almost no Chinese content)
English content is also relatively limited
Search quality is not as good as Brave

Best for: English privacy search fallback, third-party verification via independent indexes (cross-verification using dual independent indexes with Brave)

IV. Scenario-Based Engine Recommendations

Scenario 1: Hong Kong Stock Due Diligence (Chinese-focused)

Priority	Engine	Reason
🔴 Required	Bing	Strongest Chinese-language support, rich Hong Kong market content
🔴 Required	Tavily	AI-structured summaries, quickly extracts key information
🟡 Recommended	Kimi	Deepest coverage of Chinese company information
🟡 Recommended	Brave	Cross-validation of English financial data

Scenario 2: Global Market Research (English-focused)

Priority	Engine	Reason
🔴 Required	Brave	Highest quality independent index
🔴 Required	Tavily	AI summaries + citations
🟡 Recommended	Gemini	Google, the world's largest index
🟡 Recommended	Wikipedia	Benchmark for fact verification

Scenario 3: Cross-Validation Search (Pursuing Factual Accuracy)

Priority	Engine	Reason
🔴 Required	Brave	Independent index (different perspective)
🔴 Required	Tavily	Native to AI agents
🔴 Required	DuckDuckGo	Zero-cost complement to Bing's index
🟡 Recommended	Wikipedia	Zero-cost authoritative benchmark
🟡 Recommended	Bing	Chinese-language content reinforcement
🟢 Optional	Mojeek	Third independent index for verification

Scenario 4: Zero-Cost Solution

Priority	Engine	Monthly Free Quota
🔴 Required	Brave	2,000 queries
🔴 Required	DuckDuckGo	Unlimited
🔴 Required	Wikipedia	Unlimited
🟡 Recommended	Mojeek	Unlimited
🟡 Recommended	Tavily	1,000 queries

5. Our Choice: Cross Search Plugin Default Configuration

Based on the above analysis, our in-development OpenClaw Cross Search Plugin uses the following default engine combination:

{
"providers": [
    "brave",       // Independent index, highest quality, API Key already available
    "tavily",      // AI Agent native, API Key already available
    "duckduckgo",  // Zero-cost complement to the Bing index
    "wikipedia",   // Zero-cost authoritative baseline
    "bing",        // Best for Chinese (optional enablement)
"mojeek"       // third independent index verification
  ],
  "maxResults": 10,
  "timeoutMs": 8000
}

Selection Logic:

Brave + Mojeek = dual verification from two independent indexes
Tavily = AI-structured summaries for fast understanding
DuckDuckGo = queries the Bing index with no additional API Key required
Wikipedia = zero-cost authoritative factual baseline
Bing = the best choice for Chinese content (API Key configuration required)

6. Key Conclusions

There is no perfect search engine. Every engine has clear strengths and weaknesses, and the best strategy is multi-engine parallel use + cross-validation.
Independent indexes vs. third-party indexes is the most critical distinguishing dimension. The independent indexes of Brave and Mojeek provide a perspective completely different from the Google/Bing ecosystem.
Zero cost does not equal zero value. Wikipedia's authority in fact-checking and the value of DuckDuckGo and Mojeek in providing fallback perspectives cannot be underestimated.
Chinese-language search is a unique challenge. Bing is currently the best choice among Chinese-language search engines, but Kimi has irreplaceable value in China market research.
There is a huge gap between the ideal and reality of SearXNG. Self-hosted multi-engine aggregation is perfect in theory, but in practice it is blocked by mainstream search engines and is not recommended for investment.
The design of Cross Search Plugin stems precisely from these findings: integrating the strengths of multiple engines into one tool, using Promise.all to achieve true parallelism, and using URL deduplication and confidence scoring to achieve cross-validation.

This article was written by the Junze Think Tank research team based on actual deployment and test data. Last updated: 2026-05-12.

Why Make This Comparison?

1. Index Types: The Core Differences Between Search Engines

2. Complete Comparison Matrix

3. In-Depth Analysis of Each Engine

🟢 Brave Search, Primary Recommendation

🟡 DuckDuckGo, Zero-Cost Fallback

🟢 Tavily, AI Agent Native Search

🟢 Wikipedia, Fact-Checking Benchmark

🟢 Bing, King of Chinese Search

🟡 Exa, Semantic Search Pioneer

🟡 Firecrawl, Curated Authoritative Sources

🟢 Gemini (Google), World's Largest Index

🟡 Grok (xAI), Unique Advantage in Social Data

🟢 Kimi (Moonshot): Top Choice for the Chinese Market

🟡 MiniMax: Emerging Multi-Source Aggregation

🟡 Perplexity: Benchmark for AI Search Experience

🟡 Ollama Web Search: Fully Local

🔴 SearXNG: Ideal vs. Reality

🟡 Mojeek: The Last Truly Independent Index

IV. Scenario-Based Engine Recommendations

Scenario 1: Hong Kong Stock Due Diligence (Chinese-focused)

Scenario 2: Global Market Research (English-focused)

Scenario 3: Cross-Validation Search (Pursuing Factual Accuracy)

Scenario 4: Zero-Cost Solution

5. Our Choice: Cross Search Plugin Default Configuration

6. Key Conclusions

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