MagicLabChina2026
Magic-Mix
Key figures as stated by the developer
1 of 7 key figures stated-
Model type A
world action model
Not stated: Controls · Inputs · Access · Parameters · Base model · Licence
Full specifications
2 of 14 fields stated| Field | Value | Source and caveats |
|---|---|---|
| Release | ||
| Released | 28 April 2026 | [A] "On April 28 (PST), the inaugural Global Embodied Intelligence Summit (GEIS), initiated by Magiclab Robotics (MagicLab), successfully concluded in Silicon Valley" A |
| Input and output | ||
| Model type | world action model | MagicLab calls Magic-Mix a world model with two engines: "The Magic-Mix World Model comprises two core engines". The first engine, Magic-Mix WAM, is described as "Responsible for physical environment understanding, spatial reasoning, and action decision-making". A |
| Inputs | not stated | |
| Controls | not stated | |
| Degrees of freedom controlled | not stated | |
| Size and speed | ||
| Parameters | not stated | |
| Control rate | not stated | Note MagicLab gives no figure: "granting robots millisecond-level responsiveness for complex tasks". A |
| Where it runs and what it is built on | ||
| On robot or cloud | not stated | |
| Base model | not stated | |
| Openness | ||
| Access | not stated | |
| Licence terms | not stated | |
| Licence | not stated | |
| The developer’s own claims | ||
| Learns new tasks | not stated | |
| Works across robots | not stated | Yes only if the developer itself says the model runs on different robot models, for example robots from two manufacturers or two of one manufacturer’s models. Several units of the same robot do not count. |
How to read the figures
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Notes
- MagicLab launched Magic-Mix at its Global Embodied Intelligence Summit in Silicon Valley in April 2026.
- MagicLab trains Magic-Mix in a video-action dual-expert mode.
Versions and notes in the key figures (1)
Model type
MagicLab calls Magic-Mix a world model with two engines: "The Magic-Mix World Model comprises two core engines". The first engine, Magic-Mix WAM, is described as "Responsible for physical environment understanding, spatial reasoning, and action decision-making".
Sources
-
A
Primary source. www.
magiclabglobal. · Retrievedcom/ blog/ the-magiclab-global-embodied-ai-innovation-conference-concludes-in-silicon-valley-spearheading-the-next-decade-of-embodied-ai. html
One line per source, not per figure: a source has one retrieval date. The letter beside a figure points to the line it came from.