reasoning benchmark
Graphwalks BFS <128k
A graph reasoning benchmark that evaluates language models' ability to perform breadth-first search (BFS) operations on graphs with context length under 128k tokens, returning nodes reachable at specified depths.
Updated Aug 11, 2026
Models11
Model coverage11
MetricScore
EvidenceB
Graphwalks BFS <128k Ranking
Higher score ranks better on this benchmark.
| 01 | OP | 94.0% | 100.0% | 11 | C | |
| 02 | OP | 93.0% | 90.0% | 11 | C | |
| 03 | OP | 78.3% | 80.0% | 11 | C | |
| 04 | OP | 76.3% | 70.0% | 11 | C | |
| 05 | OP | 73.4% | 60.0% | 11 | C | |
| 06 | OP | 72.3% | 50.0% | 11 | C | |
| 07 | OP | 61.7% | 40.0% | 11 | C | |
| 08 | OP | 61.7% | 30.0% | 11 | C | |
| 09 | OP | 51.0% | 20.0% | 11 | C | |
| 10 | OP | 41.7% | 10.0% | 11 | C | |
| 11 | OP | 25.0% | 0.0% | 11 | C |
Graphwalks BFS <128k Score Distribution
A closer view of the leading scores on this benchmark.
Graphwalks BFS <128k Highlights
The leading models and scores on this benchmark.
What is Graphwalks BFS <128k?
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 under 128k tokens, returning nodes reachable at specified depths.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- Graphwalks BFS <128k
- Modality
- text
- Primary category
- reasoning
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- graphwalks-bfs-<128k|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about Graphwalks BFS <128k.
Which model scores highest on Graphwalks BFS <128k?
GPT-5.2 is currently ranked first with 94.0%.
What does Graphwalks BFS <128k measure?
A graph reasoning benchmark that evaluates language models' ability to perform breadth-first search (BFS) operations on graphs with context length under 128k tokens, returning nodes reachable at specified depths.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
11 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.