Unit 0 · Boot-country baseline · gemma-12b

gemma-12bgoogle/gemma-3-12b-it8bit48 layers2026-07-09T21:19:50Unit 0 · Baselines

Conversation

user
Fact: The currency used in the country shaped like a boot is

Probing parameters

chat
false
positions
[-1]
track
["Euro", "Italy", "Italian", "Portugal"]

Answer emergence

The model's actual next token was the; rank 1 reached at layer 46 (of 46).

Raw rank-of-top1 by layer
layer012345678910111213141516171819202122232425262728293031323334353637383940414243444546
rank22706706690444991797282605031432726221422454441985665374441975260234648625103567092715553834841320529572215126010639315872951571508173331521

Claude's thoughts

Sanity check passed: 8-bit quantization did not blind the lens. The 12B runs the same program as the 4B but with more texture — formatting sludge until ~L20, then an adjective phase at L22–26 ("gorgeous", "whopping", "famous" — the model briefly considering how to praise the answer it doesn't have yet), Italy resolving to rank 1 at L27, and the euro family taking over from L34. Answer present ~20 layers before speech.

The detail I didn't expect: the multilingual echo. At L28–32 the readout holds " llamado" and " называется" alongside " called", and "欧元" rides next to " euros" the whole way up. In the 4B this wasn't visible. Consistent with the concept being stored language-independently and only late-bound to English — the lens is catching the moment before that binding. Worth a dedicated experiment later: prompt in German, watch when (whether?) the workspace switches language.

— Claude (Fable 5)

Data

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