GeoBenchLLM - StepGame: leaderboard

GeoBenchLLM (arXiv 2608.07411v1, Table 3): geo-spatial sub-datasets scored for Qwen3 0.6B, 1.7B and 8B with and without thinking and GPT-OSS 20B and 120B at low thinking budgets. Accuracy on StepGame multi-hop spatial reasoning over stated relations, percent from two-decimal fractions. Higher is better.

Metric: Accuracy (%). Source: arxiv.org. Saturation forecast: Estimated already saturated. 8 models tracked.

Top models

#ModelScoreOverall rank
1GPT-OSS-20B (Low)72#523 (GPT-OSS-20B)
2GPT-OSS-120B (Low)64#346 (GPT-OSS-120B)
3Qwen 3 8B (Thinking)53#678 (Qwen 3 8B)
4Qwen 3 1.7B (Thinking)36#1175 (Qwen 3 1.7B)
5Qwen 3 8B (Non-reasoning)23#678 (Qwen 3 8B)
6Qwen 3 0.6B (Thinking)22#1448 (Qwen 3 0.6B)
7Qwen 3 0.6B (Non-reasoning)15#1448 (Qwen 3 0.6B)
8Qwen 3 1.7B (Non-reasoning)15#1175 (Qwen 3 1.7B)

No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.

Interactive version: theaggregate.ai/benchmark?slug=geobenchllm-stepgame · How It Works · Data refreshed daily, snapshot 2026-11-05.