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Fine-grained 4D Spatial Reasoning on DSR-Bench (test)

87Absolute Distance Accuracy (A.Dis)DSR Suite-Model
11.631.17550.7570.325May 7, 2026

Evaluation results

MethodLinks
DSR Suite-ModelCategory=Spatial Understanding Models2026.058773.884.173.87235.575.876.177.760.637.135.146.458.9—
4DThinker (+DIFT+4DRL)Backbone=InternVL3.5-38B, Training Protocol=+DIFT+4DRL2026.0585.573.483.580.260.437.467.974.770.564.944.937.349.859.4—
4DThinker (+DIFT+4DRL)Backbone=Qwen3-VL-32B, Training Protocol=+DIFT+4DRL2026.0584.379.782.3846747.86782.879.562.944.24148.562—
4DThinker (+DIFT+4DRL)Backbone=Qwen3-VL-8B, Training Protocol=+DIFT+4DRL2026.0578.365.682.359.358.246.159.463.261.558.839.136.647.254.6—
4DThinker (+DIFT+4DRL)Backbone=Qwen2.5-VL-7B, Training Protocol=+DIFT+4DRL2026.0571.162.560.870.449.539.160.447.143.638.132.632.342.547.1—
4DThinker (+DIFT+4DRL)Backbone=InternVL3.5-8B, Training Protocol=+DIFT+4DRL2026.0569.964.165.853.151.639.152.855.252.647.439.136.649.850—
4DThinker (+DIFT)Backbone=InternVL3.5-38B, Training Protocol=+DIFT2026.055953.149.440.741.832.251.941.438.544.339.929.844.242.5—
VG-LLMCategory=Spatial Understanding Models2026.0555.232.358.557.151.632.25636.33230.332.129.127.938.4—
4DThinker (+DIFT)Backbone=Qwen3-VL-32B, Training Protocol=+DIFT2026.055365.640.545.75641.750.948.346.243.337.734.844.245.2—
4DThinker (+DIFT)Backbone=Qwen3-VL-8B, Training Protocol=+DIFT2026.0551.845.355.744.437.442.65047.144.942.335.532.940.842.6—
4DThinker (+DIFT+4DRL)Backbone=Qwen2.5-VL-3B, Training Protocol=+DIFT+4DRL2026.0550.634.429.156.834.134.849.133.330.827.826.828.627.534.2—
4DThinker (+DIFT)Backbone=Qwen2.5-VL-3B, Training Protocol=+DIFT2026.0548.228.125.346.928.628.735.829.937.224.725.331.126.631.1—
4DThinker (+DIFT)Backbone=Qwen2.5-VL-7B, Training Protocol=+DIFT2026.0545.835.934.250.637.429.640.637.935.930.919.627.338.634.8—
4DThinker (+DIFT)Backbone=InternVL3.5-8B, Training Protocol=+DIFT2026.0543.442.236.7373330.441.539.137.235.130.42841.236.2—
VLM-3RCategory=Spatial Understanding Models2026.0528.227.631.742.838.73334.423.830.822.226.429.13531.4—
InternVL3.5-38BBackbone=InternVL3.5-38B2026.0525.827.829.234.224.728.526.716.323.429.232.115.431.326.7—
Qwen3-VL-8BBackbone=Qwen3-VL-8B2026.0523.524.642.629.727.933.818.128.434.524.222.127.933.528.7—
InternVL3.5-8BBackbone=InternVL3.5-8B2026.0523.527.62834.524.727.922.41719.728.23014.230.125.4—
GPT-5Category=Proprietary Models2026.0521.141.548.734.533.334.717.244.341.921.22530.926.730.8—
Qwen2.5-VL-3BBackbone=Qwen2.5-VL-3B2026.0520.520.320.33717.622.625.520.725.623.72924.22724.6—
Gemini-2.5-ProCategory=Proprietary Models2026.052044.653.627.338.730.523.232.943.217.128.527.934.331.7—
Qwen2.5-VL-7BBackbone=Qwen2.5-VL-7B2026.0518.815.314.642.82919.431.819.311.122.219.220.230.123.5—
Qwen3-VL-32BBackbone=Qwen3-VL-32B2026.0514.537.524.143.227.538.313.232.238.517.520.32831.828—
InternVL2.5Scale=2B2026.05——————————————32.5
InternVL2.5 + DRScaffoldScale=2B2026.05——————————————66.6
Phi4-multimodalScale=5.6B2026.05——————————————45.8
Phi4-multimodal + DRScaffoldScale=5.6B2026.05——————————————50.7
Qwen2.5-VLScale=3B2026.05——————————————35
Qwen2.5-VLScale=32B2026.05——————————————44.7
Qwen2.5-VL + DRScaffoldScale=3B2026.05——————————————62.6