Model X-Ray evidence correction — 6 September 2026. Any structural-location, knowledge-separation, portrait-visualization, lesion-response, legacy simulated-quantization, robustness or prior X-Ray endorsement previously linked from this card has been withdrawn. It is not current evidence. No replacement result is published while validation remains pending. Correction record.
🎉 The X-Ray instrument is now in FREE open beta — for a limited time
The scanner behind this work is open to everyone: create an account and scan public models up to 7B — 20 free scans per account, no invite, no waitlist.
It runs on our own local GPUs, and that capacity is the honest limit of the free beta — so if you want in, sooner beats later.
→ tetracta.ai/xray.html
Twin Loss Curves — and the Seed-Null That Retracted the Headline
Correction (13 July 2026). The first version of this card reported that the two models below
compute measurably differently inside — a "4.4× quieter internals under int8" figure, an "84% of
depth" divergence, and a routing-stability edge. We then ran the one control we had flagged as
"obvious next": an independent-seed null. We trained three more models and re-scanned. Every one
of those differential-internal claims fell inside the noise between two ordinary runs, and is
retracted. This card now documents the original claims, the control that refuted them, and what
survived. The retraction is the point — see the full post-mortem at
https://www.tetracta.ai/note-xray-twin-study.html.
Update (17 July 2026). We re-ran both arms through the current production X-Ray pipeline
(rs-1.3 at the time of that re-run; the production schema is now rs-1.5 with probe-set ps-1.1 and metric mv-1.2 — the same scanner outside teams now use). The character of the observation is
unchanged: under int8 both twins keep byte-identical outputs (0/6 behavior change on either),
while their per-layer internal responses resolve differently and deterministically. Per the seed-null
control below, we attribute none of this to the architecture — what it demonstrates is the
instrument: per-pair internal resolution that output-level evals cannot provide by construction.
The scanner is now in free open beta — any account gets 20 scans on public models up to 7B, no invite:
https://www.tetracta.ai/xray.html
Two 0.93B language models, trained under strictly matched conditions — identical seed, identical
data in identical order, identical schedule — differing in exactly one component: the attention
weighting function (standard softmax vs Tetracta's undisclosed rational operator, zero extra params).
vanilla/
rational/
val bits-per-byte @ step 30 000
1.0092
1.0102
parameters
0.929 B
0.929 B
By every output-level metric these two are twins — and the seed-null control made that the strongest
claim here, not the weakest (below).
What we first claimed, and what the control did to it
We scanned both with Tetracta Model X-Ray and published four internal
findings. A reviewer asked for the denominator: how much do two runs of the same recipe, differing
only in seed, already diverge inside? We trained VAN-seed-B, VAN-seed-C (two more softmax runs) and
RAT-seed-B, and measured, with thresholds sealed in advance. Five checkpoints; ~$300 compute; all
pods terminated; all checkpoints md5-sealed.
Loss twins — CONFIRMED, and strengthened. The three softmax seeds landed at bpb 1.0092 / 1.0072 /
1.0085; the two rational seeds at 1.0102 / 1.0101. The spread between softmax seeds (0.0020 bpb) is
larger than the original softmax-vs-rational gap (0.0010). The operator moves loss by less than the
seed does — a leaderboard genuinely cannot separate them.
"4.4× quieter inside" — RETRACTED. Internal disturbance under int8, per model: VAN-42 4.166,
VAN-B 0.573, VAN-C 0.967, RAT-42 1.277, RAT-B 1.104. Spread among softmax seeds alone: 7.3×. The
original VAN-42 was a high outlier; the softmax median (0.97) sits below rational (1.19). The
direction did not survive, let alone the 4.4×.
Routing-stability edge — RETRACTED. int8 token-flip rate: VAN-42 2.97%, VAN-B 0.93%, VAN-C 1.74%,
RAT-42 0.52%, RAT-B 2.66%. The rational replication lands inside the softmax band; RAT-42's low
value was a lucky draw.
"84% of depth" divergence — RETRACTED (as a ceiling). Cross-scan mean deviation: operator pair
0.000307, seed pair 0.000324 — both span 84% of depth (ratio 1.06×). Two ordinary softmax runs diverge
internally exactly as much as the operator swap does. Our own note had flagged 84% as a ceiling
indicator; the control confirmed it, at our expense.
A null we kept (unchanged). An early read suggested rational abstains more on trick questions.
Adversarial re-verification killed it on day one (a generation-budget artifact, p≈0.2). Still a null.
What survived, and is seed-independent
On a converged public MoE (Qwen1.5-MoE-A2.7B, 1.47M routing decisions), real int8 kernels flip
about twice the routing decisions of the round-to-nearest simulation most quantization audits use
(~2.6% vs ~1.3%, deterministic). Anyone auditing quant with a simulation sees roughly half the real
kernel's routing effect. This does not depend on the twins, and it stands.
And the capability the retraction does not touch: the instrument scanned a bespoke, undisclosed
architecture unchanged — the product pipeline ran on a custom operator, not a HuggingFace model.
Honest limits
0.93B models at step 30k of 157k — young. Simulated per-row RTN quantization, not production GPTQ/AWQ.
Behavioural comparisons rest on n=6 probe prompts. Nothing here is a scaling law, and nothing here
claims rational produces a better model. The internal-difference claims we did make were retracted
by our own control — which is the methodology this release is really about.
float32. lm_head is tied to tok_emb. rational/ cannot be run correctly without the undisclosed
operator (method patent application in preparation) — loading it into a softmax model yields meaningless
output; please do not benchmark that as "Tetracta rational."
The point of all this
Output-level equality is not evidence of internal equality — but a single internal measurement is not
evidence of a real effect either. The discipline that separates a real signal from the luck of a seed
is a pre-registered negative control, run even when it overturns your own headline. That discipline,
not any one number, is what Tetracta sells.
