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3D Object Captioning on Objaverse

51.91Sentence-BERT Performance ScoreSAGE-13B
26.305232.952639.646.2474May 2, 2024Sep 8, 2024Jan 16, 2025May 25, 2025Oct 2, 2025Feb 8, 2026Jun 18, 2026

Evaluation results

MethodLinks
SAGE-13BModel Scale=13B, Preference Optimization=true2026.0351.91——52.8751.03—————9.7213.2516.99—
SAGE-7BModel Scale=7B, Preference Optimization=true2026.0350.11——50.9849.7—————9.512.6616.95—
PointAlignLLM Size=2.7B, 3D Data Size=730K, Input=Point Cloud2026.0249.94———51.32———53.0551.44————
MiniGPT-3DLLM Size=2.7B, Trainable Params=0.05B (47.8M)2024.0549.54——57.0651.393.57183.14——————
MiniGPT-3DLLM Size=2.7B, 3D Data Size=730K, Input=Point Cloud2026.0249.54———51.39———48.1749.7————
SAGE-7B*Model Scale=7B, Preference Optimization=false2026.0349.23——49.0548.56—————7.4110.2514.35—
PointLLM-13BLLM Size=13B, 3D Data Size=730K, Input=Point Cloud2026.0249.07———48.41———40.445.96————
SAGE-13B*Model Scale=13B, Preference Optimization=false2026.0348.99——48.5450.18—————7.9812.4814.27—
ShapeLLM-13BLLM Size=13B, Trainable Params=13.04B2024.0548.52——48.9449.98—————————
ShapeLLM-13BModel Scale=13B2026.0348.52——48.9449.98—————————
PointLLM-7BLLM Size=7B, 3D Data Size=730K, Input=Point Cloud2026.0248.5———48.92———42.246.54————
3D-PLOT-LLM (full)Stage-2 instruction-tuning samples=147K2026.0648.31———48.67—————3.947.2212.5940.93
PointLLM-PiSAStage-2 instruction-tuning samples=132K2026.0648.21———48.38—————3.817.2912.32—
ShapeLLM-7BLLM Size=7B, Trainable Params=7.04B2024.0548.2——46.9249.23—————————
ShapeLLM-7BModel Scale=7B2026.0348.2——46.9249.23—————————
3D-PLOT-LLM (no-PV)Stage-2 instruction-tuning samples=70K2026.0647.94———48.44—————3.847.112.2740.56
PointLLM-13BLLM Size=13B, Trainable Params=13.01B2024.0547.91——48.1549.123.18478.75——————
PointLLM-13BModel Scale=13B2026.0347.91——48.1549.12—————3.837.2312.26—
PointLLM (re-eval)Stage-2 instruction-tuning samples=70K2026.0647.66———48.16—————3.87.0212.1939.08
PointLLM-7BLLM Size=7B, Trainable Params=7.01B2024.0547.47——44.8548.553.046682.14——————
PointLLM-7BModel Scale=7B2026.0347.47——44.8548.55—————3.877.311.92—
InstructBLIP-7BLLM Size=7B, Trainable Params=0.20B2024.0547.41——45.3448.482.567776.99——————
InstructBLIP-7BModel Scale=7B2026.0347.41——43.5448.48—————4.278.2812.99—
LLAVA-13BLLM Size=13B, Trainable Params=13.03B2024.0546.37——38.2845.92.438673.97——————
LLaVA-13BModel Scale=13B2026.0346.37——38.2845.9—————4.028.1512.58—
InstructBLIP-13BLLM Size=13B, Trainable Params=0.20B2024.0545.9——44.9748.862.5811369.56——————
InstructBLIP-13BModel Scale=13B2026.0345.9——44.9748.86—————4.658.8513.23—
LLAVA-7BLLM Size=7B, Trainable Params=7.03B2024.0545.61——46.7147.12.768676.3——————
LLaVA-7BModel Scale=7B2026.0345.61——46.7147.1—————3.647.712.14—
3D-LLMLLM Size=13B2024.0544.48——33.4243.681.7711660.39——————
GPT4PointLLM Size=2.7B, 3D Data Size=660K, Input=Point Cloud2026.0241.1———41.24———21.7534.7————
LLaVA-1.5-13BLLM Size=13B, 3D Data Size=0K, Input=Single-V. Img.2026.0239.64———40.9———1632.18————
LLaVA-1.5-7BLLM Size=7B, 3D Data Size=0K, Input=Single-V. Img.2026.0239.32———41.08———17.832.73————
GPT-4o miniLLM Size=-, 3D Data Size=0K, Input=Single-V. Img.2026.0238.7———39.13———2634.61————
InstructBLIP-7BLLM Size=7B, 3D Data Size=0K, Input=Single-V. Img.2026.0235.79———36.67———16.129.52————
ShapeLLM (re-eval)Stage-2 instruction-tuning samples=75K2026.0635.49———36.13—————6.02812.3312.86
InstructBLIP-13BLLM Size=13B, 3D Data Size=0K, Input=Single-V. Img.2026.0233.52———35.6———13.7927.64————
Point-Bind LLMLLM Size=7B, 3D Data Size=-, Input=Point Cloud2026.0227.29———25.35———1.9318.19————
Cap3DCost per 1k Objects=$8.35, Annotation Speed=65k / day, Hardware=8 x NVIDIA A40 GPUs2023.06——9.5———————————
HumanCost per 1k Objects=$87.18, Annotation Speed=1.4k / day2023.06——9.5———————————