Model comparison
squishy_pick_act vs Gemini 2.5 Pro
Capability radar, value bars, and side-by-side posture.
squishy_pick_act
Not scored
value score
Gemini 2.5 Pro
93
value score
squishy_pick_act ctx
—
Gemini 2.5 Pro ctx
1.0M
Capability radar
Value · context · multimodal · openness · speed posture
Value head-to-head
- Gemini 2.5 Pro93
Attribute tape
| Field | squishy_pick_act | Gemini 2.5 Pro |
|---|---|---|
| Developer | JamieOgundiran | Google DeepMind |
| Context | — | 1.0M |
| Modalities | Text, Code, Image, Audio, Video | |
| Openness | — | Proprietary Model |
| Speed | — | — |
| Price | — | $1.25/1M in · $10/1M out |
| Value score | — | 93 |
| Summary | A Hugging Face-hosted robot manipulation policy checkpoint trained with ACT (Action Chunking with Transformers), an imitation-learning approach that predicts short sequences of actions for a robot arm to pick and place objects. The model is trained from demonstration data and targets fine-grained, low-cost robotic manipulation tasks. | Google frontier multimodal model. |