Perplexity open-sources WANDR research benchmark
Perplexity AI has open-sourced WANDR (Wide ANd Deep Research), an evaluation benchmark and dataset consisting of 500 production-grade tasks designed to test AI research agents. The benchmark measures an agent's ability to conduct complex, multi-step web research involving wide entity discovery and deep fact verification.
While LLMs have become proficient at simple information retrieval, WANDR highlights the current limitations of autonomous agents in executing long-horizon, structured research tasks without losing accuracy.
- –**Addressing Benchmark Saturation**: Standard benchmarks are being saturated rapidly by frontier models, making challenging, production-grade tasks like those in WANDR essential for identifying real-world performance gaps.
- –**Evaluating Deep Search**: Rather than evaluating static knowledge, WANDR tests dynamic web navigation, hallucination resistance, and source synthesis, which are critical for agentic workflows.
- –**Strategic Open-Sourcing**: Open-sourcing WANDR positions Perplexity's evaluation methodology as the industry standard for research agents, reinforcing their leadership in agentic search.
DISCOVERED
1h ago
2026-07-15
PUBLISHED
1h ago
2026-07-15
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