SURDS

Progress Over Time

Interactive timeline showing model performance evolution on SURDS

State-of-the-art frontier
Open
Proprietary

SURDS Leaderboard

1 models
ContextCostLicense
1
Alibaba Cloud / Qwen Team
Alibaba Cloud / Qwen Team
1.0M$0.32 / $1.28
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About this benchmark

What is SURDS?

SURDS is a benchmark for spatial understanding and reasoning in autonomous-driving scenes.

SURDS is a multimodal benchmark evaluating models on multimodal, reasoning, and vision tasks. LLM Stats tracks 1 models on this benchmark, scored on a 0–1 scale. The current average is 0.8, with the leader at 0.8.

Compare leaders on the best AI for multimodal, best AI for reasoning and best AI for vision leaderboards.

Current leaders

Qwen3.7-Plus from Alibaba Cloud / Qwen Team currently leads the SURDS leaderboard with a score of 0.772 across 1 evaluated AI models.

1Qwen3.7-PlusAlibaba Cloud / Qwen Team77.2%

FAQ

Common questions about the SURDS benchmark and leaderboard.

What is the SURDS benchmark?

SURDS is a benchmark for spatial understanding and reasoning in autonomous-driving scenes.

What is the SURDS leaderboard?

The SURDS leaderboard ranks 1 AI models based on their performance on this benchmark. Currently, Qwen3.7-Plus by Alibaba Cloud / Qwen Team leads with a score of 0.772. The average score across all models is 0.772.

What is the highest SURDS score?

The highest SURDS score is 0.772, achieved by Qwen3.7-Plus from Alibaba Cloud / Qwen Team.

How many models are evaluated on SURDS?

1 models have been evaluated on the SURDS benchmark, with 0 verified results and 1 self-reported results.

What categories does SURDS cover?

SURDS is categorized under multimodal, reasoning, and vision. The benchmark evaluates multimodal models.

Which model offers the best value on SURDS?

Among models scoring within 10% of the leader, Qwen3.7-Plus from Alibaba Cloud / Qwen Team is the cheapest, at $0.32 per million input tokens with a score of 0.772.

How recent are the SURDS leaderboard results?

The SURDS leaderboard was last updated in July 2026 and currently includes 1 evaluated models.