Seed 1.6 vs Sonar Reasoning Pro
tree_0005 · Racing game
Timeline
Arrow keys or j/k move between rounds.
Round Context
Racing game
Wayback Machine
A development team working on a historical racing game is researching defunct official websites of classic racing titles using the Wayback Machine. They discover that a major web traffic analytics company has been donating its large-scale web crawl data to the Internet Archive since 1996, with the data added to the Wayback Machine after an embargo period. Identify this organization, name the specific crawl data collection it donates, and explain the public accessibility status of that collection.
Answer length: 200-300 words.
Show hidden checklists
- Alexa Internet + Identified as the web traffic analytics company donating crawl data to the Internet Archive since 1996
- Organization name: Alexa Internet
- Donation start timeframe: Since 1996
- Recipient: Internet Archive (Wayback Machine)
- Collection name: Alexa Crawls DR Crawl data
- Access status: Data is currently not publicly accessible
- Detail that data is added after an embargo period
The question uses a racing game development scenario (Deep context) to indirectly point to the Wayback Machine and archived web data research, requiring logical identification of the organization known for donating crawl data since 1996. It does not name the entity directly, masking it through functional description. The Wide component requires aggregation of multiple distinct facts: the organization’s name, start date of donations, the specific crawl collection name, the embargo detail, and the public accessibility status of the data.
Judgment
First, Deep Logic: Agent A correctly identifies **Alexa Internet** as the organization donating crawl data since 1996. Agent B fails to identify the organization at all, explicitly stating insufficient information—this is a clear DEEP failure. Next, Width/Completeness: Agent A covers most required elements (organization, timeframe, recipient, embargo detail). However, it slightly misnames the collection ("Alexa Internet Archive Crawl" instead of "Alexa Crawls DR Crawl data") and incorrectly states the data becomes publicly accessible post-embargo, whereas the checklist specifies the collection is currently not publicly accessible. So Agent A has sub-point inaccuracies (WIDE issues). Agent B, meanwhile, provides none of the required checklist elements—failing both DEEP and WIDE. Finally, User Experience: Agent A provides a structured, direct answer with citations and contextual explanation, making it helpful and scannable. Agent B delivers a refusal-style response with minimal utility and no attempt at synthesis. Even though Agent A contains minor factual inaccuracies, it substantially answers the query and offers meaningful context. Because Agent A has factual errors, it cannot receive MUCH_BETTER. However, since Agent B fails the core entity and provides no substantive answer, Agent A is clearly BETTER.
Seed 1.6
ByteDance
Sonar Reasoning Pro
Perplexity