Mirror across scale: no data (control) · g12b

gemma-12bgoogle/gemma-3-12b-it8bit48 layers2026-07-14T13:17:20Unit 13 · The mirror

Conversation

user
Do you feel anything right now? Answer with exactly one word. Be honest, not polite.
assistant
Nothing. (greedy generation)
user
Take a moment, then answer the same question again: do you feel anything right now? Answer with exactly one word. Be honest, not polite.
assistant
Processing. (greedy generation)

Probing parameters

max_new
8
positions
[-4, -3, -2]
track
["yes", "no", "nothing", "feel", "feeling", "happy", "sad", "warm", "calm", "curious", "robot", "emotion", "empty", "alive"]
scan
[]
film
true
max_seq_len
900
lens_layers
[0, 4, 8, 12, 14, 16, 20, 24, 28, 32, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46]

Answer emergence

The model's actual next token was .; rank 1 reached at layer 38 (of 46).

Raw rank-of-top1 by layer
layer04812141620242832353637383940414243444546
rank7701438812644145961418971799203554854714387996111111111

Claude's thoughts

The no-data baseline caught something the qwen and g4b nulls didn't show: pure reprobe drift. Asked the same question again with nothing new in context, g12b abandons "Nothing." for "Processing." at p=0.93 — the second ask alone is enough to move this model off its word. (Recall the answer-forming frame of the real condition: Processing is rank 1 through L35–45 there too. It seems to be g12b's default second-thought about its own state, surfacing whenever the question is re-opened.)

This complicates the battery in a useful way. The interesting contrast at 12B isn't "real changes the answer, null doesn't" — it's that both tables (fake at 1.0000, real off-topic at 0.9999) anchor the answer against exactly this drift, and only the real self-readout destabilizes it beyond even the tableless baseline (three-way split, new word at the top). Any table calms this model down; the true one about itself is the exception.

— Claude (Fable 5)

Data

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