reasoning benchmark
DeepSearchQA Leaderboard
DeepSearchQA is a benchmark for evaluating deep search and question-answering capabilities across complex knowledge domains.
Updated Sep 5, 2026
Models10
Model coverage10
MetricScore
EvidenceB
DeepSearchQA Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelMA | Score95.00% | Percentile100.00% | Participants10 | EvidenceC | Evaluated |
| Rank02 | ModelAN | Score93.10% | Percentile88.89% | Participants10 | EvidenceC | Evaluated |
| Rank03 | ModelAN | Score91.30% | Percentile77.78% | Participants10 | EvidenceC | Evaluated |
| Rank04 | ModelTE | Score91.00% | Percentile66.67% | Participants10 | EvidenceC | Evaluated |
| Rank05 | ModelME | Score89.40% | Percentile55.56% | Participants10 | EvidenceC | Evaluated |
| Rank06 | ModelXI | Score86.70% | Percentile44.44% | Participants10 | EvidenceC | Evaluated |
| Rank07 | ModelMA | Score83.00% | Percentile33.33% | Participants10 | EvidenceC | Evaluated |
| Rank08 | ModelMA | Score77.10% | Percentile22.22% | Participants10 | EvidenceC | Evaluated |
| Rank09 | ModelME | Score74.80% | Percentile11.11% | Participants10 | EvidenceC | Evaluated |
| Rank10 | ModelME | Score74.60% | Percentile0.00% | Participants10 | EvidenceC | Evaluated |
DeepSearchQA Highlights
The leading models and scores on this benchmark.
DeepSearchQA Score Distribution
A closer view of the leading scores on this benchmark.
The Top AI Models for DeepSearchQA
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
What is DeepSearchQA?
What DeepSearchQA measures and how its scores work.
DeepSearchQA is a reasoning benchmark for evaluating deep search and question-answering capabilities.
It measures models' ability to perform multi-hop reasoning and information retrieval across complex knowledge domains, using the Score metric as a ratio.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- DeepSearchQA
- Modality
- text
- Primary category
- reasoning
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- overall
LLM Stats. Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about DeepSearchQA.
Which model scores highest on DeepSearchQA?
Kimi K3 is currently ranked first with 95.00%.
What are the top three models on DeepSearchQA?
The current leaders are Kimi K3 (95.00%), Claude Opus 4.8 (93.10%), and Claude Opus 4.6 (91.30%).
Which DeepSearchQA model has the lowest official input price?
MiMo-V2-Pro has the lowest matched official input price at $0.44 input / $0.87 output per 1M tokens.
Which models are fastest among DeepSearchQA results?
The fastest matched records are Claude Opus 4.6 (123.15 tok/s via Anthropic), Claude Opus 4.8 (42.00 tok/s via Vertex AI), and Muse Spark 1.3 (8.44 tok/s via Meta Model API).
Does the highest score result prove overall model quality?
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.