robotics benchmark
RoboSpatialHome evaluates spatial understanding for robotic home navigation and manipulation.
Updated Aug 17, 2026
Higher score ranks better on this benchmark.
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelAC | Score0.739 points | Percentile100.0% | Participants1 | EvidenceC | Evaluated |
The leading models and scores on this benchmark.
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis robospatialhome AI model leaderboard uses descending score in the benchmark's original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
Selection summary
Qwen3 VL 235B A22B Thinking currently leads RoboSpatialHome with 0.739 points. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price and runtime.
Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.
What RoboSpatialHome measures and how its scores work.
RoboSpatialHome evaluates spatial understanding for robotic home navigation and manipulation.
Scores are shown in points. 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 RoboSpatialHome.
Qwen3 VL 235B A22B Thinking is currently ranked first with 0.739 points.
RoboSpatialHome evaluates spatial understanding for robotic home navigation and manipulation.
Yes. Higher values rank better for this benchmark.
1 model results are currently shown.
No. This benchmark is shown for reference but does not contribute to the overall score.