BrowseComp Long Context 128k
Models answer BrowseComp questions from a 128k-token context of the needed web pages mixed with related distractor pages. Scored by accuracy.
The 128k setting of BrowseComp Long Context, which scales beyond 1M tokens.
- Level
- Expert Specialists with years of training, often over hours of work
- Scored
- Checked automatically A program checks the result against an answer key, unit tests or the expected final state.
- Answers
- Short answer A number, word or short string matched to a key.
GPT-5.1 leads with 90% among models released by Nov 2025
Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.
The newest model with a score here came out in Nov 2025, and nobody has reported a newer one. Among the 20 highest-ranked models on the capability index, these have no score yet:
- GPT-6 Astra
- Claude Opus 5.5
- GPT-6.1 Terra
- GPT-6.1 Sol
- and 16 more
- 1 GPT-5.1 90%
- 2 GPT-5 mini 89.4%
- 3 GPT-5 nano 80.4%
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | GPT-5.1 | 90% | Nov 2025 | Model card | |
| 2 | GPT-5 mini | 89.4% | Aug 2025 | Model card | |
| 3 | GPT-5 nano | 80.4% | Aug 2025 | Model card |
2 models have held number one since its release in Aug 2025
Lab claims count from the day the card came out, independent runs from the model’s release.
The best score passed 85% in Aug 2025
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Labs dropped it from launch posts once the best score passed 85%
Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.
| Date | Launch post | Score | As the post writes it |
|---|---|---|---|
| 13 Nov 2025 | GPT-5.1 | 90 | BrowseComp Long Context 128k |
| 7 Aug 2025 | GPT-5 nano | 80.4 | BrowseComp Long Context 128k 80.4 (256k 68.4) |
| 7 Aug 2025 | GPT-5 mini | 89.4 | BrowseComp Long Context 128k 89.4 (256k 86.0) |
More in Long context
- MRCR v2 In use Multi-round coreference: retrieve the n-th of several similar requests hidden in a long synthetic conversation, up to 1M tokens.
Muse Spark 1.3 98.5% - LongBench v2 In use 503 multiple-choice questions over 8K-2M-word contexts (QA, dialogue, code repos, structured data). Accuracy. Beam 1.0 66.9%
- GraphWalks In use A graph is given as an edge list in long context. The model answers BFS or parent queries, scored by F1. Claude Fable 5 100%
- OpenAI MRCR v2 In use Models read a long synthetic chat that hides 2, 4 or 8 identical writing requests and must reproduce the response to the i-th one. Scored by mean string match ratio per context bin.
K-EXAONE 2.0 94.4% - CL-bench In use Model must learn new knowledge from a supplied long context (rules, procedures, data) and solve tasks. Strict LLM-verified rubrics. GPT-5.4 27.9%
- AA-LCR 1.1 In use Models answer 100 questions that need reasoning across sets of real documents of about 100K tokens. An LLM equality checker with a fixed system prompt compares each answer with the key.
Step 5 Preview 88.3%