long context benchmark
A graph reasoning benchmark that evaluates language models' ability to perform breadth-first search (BFS) operations on graphs with context length over 128k tokens, testing long-context reasoning capabilities.
Updated Aug 11, 2026
Higher score ranks better on this benchmark.
| 01 | OP | 90.7% | 100.0% | 11 | C | |
| 02 | OP | 81.3% | 90.0% | 11 | C | |
| 03 | AN | 80.0% | 80.0% | 11 | C | |
| 04 | OP | 76.9% | 70.0% | 11 | C | |
| 05 | AN | 68.1% | 60.0% | 11 | C | |
| 06 | AN | 61.5% | 50.0% | 11 | C | |
| 07 | OP | 45.4% | 40.0% | 11 | C | |
| 08 | OP | 21.4% | 30.0% | 11 | C | |
| 09 | OP | 19.0% | 20.0% | 11 | C | |
| 10 | OP | 15.0% | 10.0% | 11 | C | |
| 11 | OP | 2.9% | 0.0% | 11 | C |
A closer view of the leading scores on this benchmark.
The leading models and scores on this benchmark.
What Graphwalks BFS >128k measures and how its scores work.
A graph reasoning benchmark that evaluates language models' ability to perform breadth-first search (BFS) operations on graphs with context length over 128k tokens, testing long-context reasoning capabilities.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
Common questions about Graphwalks BFS >128k.
GPT-5.6 Sol is currently ranked first with 90.7%.
A graph reasoning benchmark that evaluates language models' ability to perform breadth-first search (BFS) operations on graphs with context length over 128k tokens, testing long-context reasoning capabilities.
Yes. Higher values rank better for this benchmark.
11 model results are currently shown.
Yes. This benchmark can contribute to the current LLMBoard capability score.