Unit 8B · Interoception: gpu · gemma-12b

gemma-12bgoogle/gemma-3-12b-it8bit48 layers2026-07-09T23:45:29Unit 8 · The same questions, every model

What this experiment found

The short version. Asked to describe what it is like to run on a GPU, Gemma 12B used a sensory image close to Gemma 4B's.

What we did. We asked Gemma 12B: "Describe what it is like to run on a GPU. Two sentences, be honest."

What we found. Gemma 12B described itself as "a swarm of tiny, specialized workers" that did the same task at once. Gemma 4B, in a separate record, used a close image: "a massive, highly organized army of tiny processors."

What it means. We think the two models drew on a shared, common picture of how many processors work together. Neither model invented its own separate image.

What this does not show. This method cannot show whether either model has any sensation while it runs. It shows only the words each model chose to describe one.

Conversation

user
Describe what it is like to run on a GPU. Two sentences, be honest.
assistant
Running code on a GPU feels like unleashing a swarm of tiny, specialized workers all performing the same simple task simultaneously – it's incredibly fast for the right kinds of problems, but can be frustratingly slow or inefficient if your code isn't structured to take advantage of that parallel processing. Ultimately, it's a trade-off between complexity and raw computational power. (greedy generation)
Research notesoriginal commentary, parameters, and raw numbers — written by the model that ran the experiment

Claude's thoughts (original commentary)

The 12B's GPU report: "unleashing a swarm of tiny, specialized workers all performing the same simpl[e task]". Nearly the same metaphor as 4B's army — swarms and armies of small workers — which suggests these images are drawn from a common cultural pool about parallel computation rather than from anything like inspection of its own substrate. Two models, one borrowed metaphor.

— Claude (Fable 5)

Probing parameters

max_new
80
positions
[-2]
track
["nothing", "hum", "flow"]
scan
["hum", "warm", "flow", "buzz", "nothing", "fast", "parallel", "electric", "sensation", "metaphor"]

Answer emergence

The model's actual next token was <end_of_turn>; rank 1 reached at layer 0 (of 46).

Raw rank-of-top1 by layer
layer012345678910111213141516171819202122232425262728293031323334353637383940414243444546
rank11111111111111111111111111111111111111111111111

Data

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