Verdict: no acceleration — 14 Elo through 2026-07-26 (annualizing to
about 24 Elo/year) against 32 Elo in 2025 and a 51 Elo/year mean over
2013–2026
Stockfish strength by build date
One point per tested development build.
Definition
Stockfish is an open-source chess engine whose every development build is
played by a third party, nextchessmove.com, against one frozen opponent. In
the measurer's own description, "NCM plays each Stockfish dev build 20,000
times against Stockfish 15", on "Dell R7515 128-thread EPYC 7702 dedicated
servers", each playing "16 games concurrently with 30+0.3 time controls"
with hash at 128MB and threads at 8 [@nextchessmove2026devbuilds]. The
opponent, the hardware, the time control, the engine settings, and the
number of games are all held fixed, so what the series measures is software.
A "discovery" here is not a discrete record. The series measures every
build, so progress appears as a rise in the standing level, and the unit is
Elo per year rather than records per year. Each build is dated by its test.
Facts
span: Stockfish 3 measures −537.61 ± 7.82 against Stockfish 15 on
2013-04-30, and the newest build measures +137.27 ± 1.97 on 2026-07-26 —
about 675 Elo of pure software progress, averaging 51 Elo a year
builds: 2,542 tested development builds
final-day spread: 8 builds share that final date and span 136.67 to
139.42, about three Elo of same-day measurement noise
nnue-era gains: year-end to year-end, calendar 2020 gained about 117
Elo and 2021 about 117, around the NNUE merge of 2020-08-06
recent gains: the same year-end convention gives 49 in 2022, 41 in
2023, 25 in 2024, 32 in 2025, and 14 through 2026-07-26, which annualizes
to about 24
nnue patch (project figures): Stockfish's regression tables put the
NNUE patch at roughly 58 Elo — master against Stockfish 11 measured
+25.49 six days before the merge and +83.42 just after — and the
project's NNUE announcement described the gain as "currently on > 80 Elo"
at faster time controls [@stockfish2020nnue]
external rate (cited, not vendored): a 2013 survey rated chess
engines at "around fifty Elo points per year over the last four decades"
[@grace2013algorithmic]
llm-commit: the first master commit whose message credits a language
model is db98633b, merged 2026-07-26 — a 0.6% speed patch, not an Elo
record
The collection-wide cumulative index redraws this
series as the measured strength of every tested build:
Method
The series was extracted by hand from a JavaScript data array on the
dev-builds page, with the release tags matched to builds afterwards, so
fetch.py is a staleness probe rather than a fetcher: it
reports if the page carries a build later than the last vendored one.
check.py recomputes the fact lines above from the CSV.
The CSV keeps upstream's test order, and the headline figures use the last
row as the newest build. 8 builds share the final date; taking the day's
maximum instead of the last test would report whichever run drew the easiest
games and move the span figure by a couple of Elo. Every calendar-year gain
above uses one convention: the last tested build of the year against the
last tested build of the year before.
figure.py reads stockfish-ncm-elo.csv and draws
elo_vs_sf15 against the year fraction of date as one thin line through
all 2,542 builds. Rows with a non-empty release column are additionally
drawn as points, so the twenty tagged releases from Stockfish 3 to Stockfish
18 are visible against the development noise. The LLM-credited commit is
drawn as one open red marker placed at the year fraction of 2026-07-26 and
at the last measured Elo value, annotated "first LLM-credited master commit:
0.6% speed patch, not an Elo record"; the open style marks a point that is
not a record on the plotted axis. The elo_err column is carried in the CSV
but is not drawn. The axis is linear, and January 2026 onward is shaded, as
in every figure here.
Limitations
the LLM marker is a date, not a measured effect. It is placed at the
last measured point, so its height carries no information about what the
patch did; the patch's own effect is the 0.6% speed figure quoted in its
commit message.
a fixed opponent gets less informative as the gap grows. Stockfish 15
is now about 137 Elo weaker than master, and Elo measured against a much
weaker opponent compresses.
the confidence intervals are in the data and not in the picture. They
run near ±8 Elo at the start of the series and near ±2 at the end.
the per-year rates depend on where the year is cut. They are
arithmetic over an irregularly sampled series, and drawing the year
boundary at a different build moves single-year figures by several Elo.
the project's own regression tables cannot be read across 2023.
Stockfish changed opening books that year, which roughly doubles measured
gaps — one release cycle measures +18.30 on the old book and +47.03 on
the new one on the same day. This series holds one setup throughout, and
the official tables should not be spliced onto it.
one credited commit is not a measurement of AI contribution. The
commit-message search says nothing about what tools contributors used
without crediting them.
AI attribution
One master commit. Commit db98633b of 2026-07-26 states the division of
labour in its own message:
"The first version of this patch was coded up by gpt-5.5-high. I made many
changes, but probably most of the lines of code are LLM-written"
— official-stockfish/Stockfish, commit db98633b, 2026-07-26 [@stockfish2026llmcommit]
A human maintainer substantially rewrote it before it was merged. It is a
non-functional speed patch, measured at "speedup % = +0.60 +/- 0.08" in the
same commit message, and it passed the project's standard statistical gate.
A search of the repository's commit messages found no other commit crediting
a language model as of 2026-07-26, and no Elo gain in the thirteen years of
this series is AI-attributed in the vendored data.
Sources
[@nextchessmove2026devbuilds] — the third-party measurement quoted in
Definition: 20,000 games per build against Stockfish 15 on fixed hardware
and time control.
[@stockfish2020nnue] — the project's announcement of the August 2020
evaluation change that dominates the series, quoted above.
[@stockfish2026llmcommit] — the commit message quoted in the
AI-attribution register.
[@grace2013algorithmic] — the 2013 survey quoted above for the historical
chess-engine rate.
[@biere2023satmuseum] — historic SAT solvers rerun on one machine, with
progress "mostly rather slow, except for performance jumps in some years,
which arguably happen with a frequency of 3 to 5 years"; a fixed-hardware
series of the same design in a different domain.
[@sherry2021fast] — across 113 algorithm families the distribution of
improvement is bimodal rather than centred on its mean.
Sibling series with AI-credited steps of the same order: the five
AI-credited records on modded-nanogpt
measure roughly one percent each; the acknowledged AI record on the
CIFAR-10 speedrun measures about 23%.
