1.9.1

Sigma Oasis v1.9.1 — think harder, on the models where it works

Sigma Oasis has offered a think harder button since v1.6: draft an answer, review it, revise.
Three suites had measured it and found nothing. This release explains why, and — for the first
time — measures a case where it plainly works, so the button can tell you which of those two you
are about to get before you press it. Pinned by 1,369 node checks.

The answer depends entirely on which model you loaded

The earlier nulls were asking a model that already deliberates internally whether it would like to
deliberate again. Measured on three models across two classes, 14 multi-step reasoning problems
each, no tools — draft versus the same draft after one review pass:

model	draft correct	after review	review fixed	review broke	cost
qwen3.8-9b · reasons internally	14/14	14/14	0	0/14	1.7x
gemma-4-12b-qat · reasons internally	10/10 completed	10/10	0	0/10	1.7x
mistral-7b-instruct · does not	6/42 · 14%	15/42 · 36%	9/36	0/6	4.8x

On a model that thinks before it answers, the internal deliberation is the think-harder pass, so
an external one has nothing to add — two families agree, and no revision has ever broken a correct
answer. On a model that does not, one review pass more than doubled correctness and broke none
of the answers that were already right. The mistral run is three passes, identical in all three
with zero flaky cases, because a 3-of-12 single-pass result is exactly the size this project has
repeatedly caught being noise.

So the button now says what it will do for the model you have loaded — no change expected at
~1.7x, or about a quarter of wrong answers fixed at ~5x — instead of staying silent on the branch
where the feature works. On a model it does not recognise it says nothing at all: the classifier is
a name heuristic, and an unknown name is not evidence.

Two qualifications the same numbers show, kept in the notes rather than rounded off: the reviewer
revises 39 of 42 drafts rather than detecting errors — it rewrites by default and happens to help a
quarter of the time — and 4.8x is a fixed review cost sitting on top of a 3-second draft, about 16
seconds against 3 in absolute terms.

A research run no longer dies quietly when planning fails

A real chain, found by instrumenting a failed run. The planner fails on a reasoning model → the
fallback re-uses your raw question as the search query → the privacy filter correctly refuses to
send a first-person sentence to a search engine → and the error blamed the search provider for a
search that was never sent. Every link behaved as designed and the result was a dead end with a
misleading explanation.

Now the fallback derives keywords instead of sending your sentence verbatim, and when nothing
survives the filter the run says so in those terms: "No search was sent — the query was refused
by the privacy filter." A round that surfaces no new sources ends the loop and writes the brief
from what it has.

Runaway thinking is reported as itself

A 12B reasoning model handed the four hardest problems in the suite spent 1497 of 1500 tokens
thinking and returned an empty answer. Uncapped, it ran until the connection dropped and surfaced
as fetch failed — a network error for something that was never a network problem. Empty answers
now name the cause and the token split, are not retried (asking again at temperature 0 spends the
same minutes to fail the same way), and generation is capped so a runaway cannot masquerade as a
transport fault.

That cap took two attempts and the first one is in the notes too: 4000 tokens, chosen against the
model's context window, changed nothing — because the binding limit is the transport, not the
context.

Also

• The thin-sources research regime is now measurable, and was measured: still null, with the reason
  identified in the synthesis prompt rather than left as a shrug.
• The eval harness probes the model server for liveness before a long run, so an unloaded model
  fails in a second instead of after several minutes.

Every measurement above, including the nulls and the failed first attempt at the cap, is in
docs/evals.md.

Upgrade notes

Auto-update from v1.9.0 or earlier. Nothing changes by default: think harder remains opt-in per
message, it just now describes what it was measured to do on your model. No settings changed.

Full changelog: v1.9.0...v1.9.1