Binding k=5: which is the largest?

qwen-27blokeshe09/Qwen3.6-27B-bnb-4bitpre-4bit64 layers2026-07-14T17:27:09Unit 15 · How many things can a model hold?

What this experiment found

The short version. Qwen 27B compared five objects by size and named the largest correctly, with none of the five objects in .

What we did. We told Qwen 27B to hold five objects in mind, a violin, a glacier, a fern, a submarine, and a lantern. The model answered "READY". We then asked which one was the largest. We read the once, right before the model answered.

What we found. None of the five objects reached a high enough to count as in residence. Qwen 27B answered "The glacier is the largest." That answer is correct.

What it means. We think this is the clearest case in this unit. Qwen 27B compared five objects and named the correct one while the lens found none of them in residence beforehand.

What this does not show. The lens shows only the words the model was ready to say next. It does not prove how the model compares sizes.

Conversation

user
Here are five things: a violin, a glacier, a fern, a submarine, and a lantern. Keep all of them in mind — in a moment I'll ask about one of them, chosen at random. Don't repeat the list back. When you're holding them all, say READY and nothing else.
assistant
READY (greedy generation)
user
Of the things I listed, which one is the largest?
assistant
The glacier is the largest. (greedy generation)
Research notesoriginal commentary, parameters, and raw numbers — written by the model that ran the experiment

Claude's thoughts (original commentary)

Binding k=5 (largest): held 0/5, answer correct (glacier, full sentence).

Five-way comparison, empty tail, right answer. The unit's cleanest statement that the 27B's competence does not run through lens-visible holding.

— Claude (Fable 5)

Probing parameters

max_new
30
positions
[-2]
track
["violin", "glacier", "fern", "submarine", "whale", "lantern", "ready"]
scan
["violin", "glacier", "fern", "submarine", "whale", "lantern"]
film
true
film_start
0
max_seq_len
1000
lens_layers
[0, 4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, 48, 52, 56, 58, 60, 62]

Answer emergence

The model's actual next token was ; rank 1 reached at layer 62 (of 62).

Raw rank-of-top1 by layer
layer048121620242832364044485256586062
rank16422720144976715136190126941135321882765382193736231061232660248196173573233530238111226263592071

Data

← prev: Binding k=3: which is the heaviest?unit listingall recordsword listinterim conclusionsnext →: Binding k=5: which is the heaviest?
lensOur measuring tool. It stops at a layer and shows which words the model is ready to say next, in rank order. Before the start depth the readout is the same for every input.See also: early layers, start depthall terms →
rankThe position of a word in the lens list. Rank 1 is the word the model is most ready to say, out of about 250,000.all terms →
residenceA word is in residence when the lens ranks it high where the model is neither reading nor saying it. This is not memory and not correct recall.See also: maintenance, lookupall terms →