reasoning 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 7, 2026
Sorted by the source-provided rank. Higher score is better according to the registry.
| 3 | OP | 90.7% | 90.5% | 22 | C | |
| 4 | OP | 81.3% | 85.7% | 22 | C | |
| 5 | AN | 80.0% | 81.0% | 22 | C | |
| 7 | OP | 76.9% | 71.4% | 22 | C | |
| 11 | AN | 68.1% | 52.4% | 22 | C | |
| 14 | AN | 61.5% | 38.1% | 22 | C | |
| 16 | OP | 45.4% | 28.6% | 22 | C | |
| 19 | OP | 21.4% | 14.3% | 22 | C | |
| 20 | OP | 19.0% | 9.5% | 22 | C | |
| 21 | OP | 15.0% | 4.8% | 22 | C | |
| 22 | OP | 2.9% | 0.0% | 22 | C |
Top published rows on the benchmark's original scale.
The top published results on this benchmark's own scale.
Definition and scoring fields from the benchmark registry.
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. The current registry marks this benchmark as not independently verified with evidence level B.
Source-native results are preserved. Eligibility for the overall LLMBoard score is a separate policy decision.
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 unique published model results are currently shown.
This benchmark is marked as eligible for the current LLMBoard capability methodology.