BrowseComp Plus
BrowseComp Plus (long-document extension of BrowseComp) as reported on the KRAFTON Raon-1 mini preview card; search/agentic benchmark, judge gpt-5.6-luna. Distinct from BrowseComp and BrowseComp-zh.
Category
General Agents
Score type
percent
Scale
100%
higher is better
Models tested
5
What is BrowseComp Plus?
BrowseComp (Browsing Competence) is an OpenAI benchmark for deep web research. Each task is a question whose answer is deliberately hard to find — the model has to navigate many web pages, follow leads and cross-check sources. A correct final answer is the only thing that counts.
What does it test?
BrowseComp Plus measures how well a model acts as a general-purpose agent. In detail, it checks:
- searching the web step by step instead of guessing
- reading and understanding many pages per task
- combining information from several sources
- persistence on questions that are nearly impossible without browsing
How to read the score
The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better.
Frequently asked questions
What is the BrowseComp Plus benchmark?
BrowseComp (Browsing Competence) is an OpenAI benchmark for deep web research. Each task is a question whose answer is deliberately hard to find — the model has to navigate many web pages, follow leads and cross-check sources. A correct final answer is the only thing that counts.
What does BrowseComp Plus test?
BrowseComp Plus mainly measures how well a model acts as a general-purpose agent. Concretely, it checks: searching the web step by step instead of guessing; reading and understanding many pages per task; combining information from several sources.
How is the BrowseComp Plus score calculated?
The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better. The declared maximum score of this benchmark is 100.0.
Where do I get BrowseComp Plus data and scores?
The official source is https://huggingface.co/KRAFTON/Raon-1-mini-preview. The official benchmark page/reference is linked on this page. Every score on Open LLM Radar is also available as open data: download the scores JSON (http://open-llm-radar-api:8000/api/v1/benchmarks/browsecomp-plus/scores) or pull it directly from the Open LLM Radar API with any HTTP client.
Benchmark data & downloads
Where to get, inspect and reuse the data behind this benchmark.
Official benchmark page / paper
The benchmark maintainer's website, paper or leaderboard
Benchmark metadata (JSON)
This page's benchmark record from the Open LLM Radar API
All model scores (JSON download)
Full score table as JSON; paginate with limit/offset params
Open LLM Radar API docs
Swagger UI to explore and reuse all radar API endpoints
Model scores 5 models tested
| # | Model | Score | Date | Source | Verified |
|---|---|---|---|---|---|
| 1 |
Qwen3.8-27B
Qwen Team (Alibaba Cloud)
|
58%
|
21.10.2026 | Report | Unverified |
| 2 |
Raon-1 mini
KRAFTON AI
|
55.7%
|
21.10.2026 | Report | Verified |
| 3 |
Muse-Glimmer-30B
Meta Superintelligence Lab
|
52.8%
|
21.10.2026 | Report | Unverified |
| 4 |
Qwen3.6-35B-A3B
Qwen Team (Alibaba Cloud)
|
34.8%
|
21.10.2026 | Report | Unverified |
| 5 |
Gemma4-26B-A4B
Google
|
32.2%
|
21.10.2026 | Report | Unverified |