Post
1750
SpaceThinker-Qwen2.5VL-3B shows a 3B VLM can compete with closed, frontier APIs in quantitative spatial reasoning, a key capability for embodied AI applications like drones and robotics.
Check out how it stacks up against Gemini and OpenAI on Q-Spatial-Bench in the ModelCard. Includes .gguf, colab quickstart, docker images.
SpaceThinker adopts the Qwen2.5VL-3B architecture, fine-tuned on the SpaceThinker dataset of synthetic spatial reasoning traces, created with VQASynth
This model builds upon the SpaceLLaVA series of VLMs finetuned for enhanced spatial reasoning using synthetic data by adding test-time compute for multimodal thinking.
Model: remyxai/SpaceThinker-Qwen2.5VL-3B
Dataset: remyxai/SpaceThinker
Space: remyxai/SpaceThinker-Qwen2.5VL-3B
Code: https://github.com/remyxai/VQASynth
Discussion: open-r1/README#10
Check out how it stacks up against Gemini and OpenAI on Q-Spatial-Bench in the ModelCard. Includes .gguf, colab quickstart, docker images.
SpaceThinker adopts the Qwen2.5VL-3B architecture, fine-tuned on the SpaceThinker dataset of synthetic spatial reasoning traces, created with VQASynth
This model builds upon the SpaceLLaVA series of VLMs finetuned for enhanced spatial reasoning using synthetic data by adding test-time compute for multimodal thinking.
Model: remyxai/SpaceThinker-Qwen2.5VL-3B
Dataset: remyxai/SpaceThinker
Space: remyxai/SpaceThinker-Qwen2.5VL-3B
Code: https://github.com/remyxai/VQASynth
Discussion: open-r1/README#10