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Runs every morning at 6:00 ET

Daily model bench

Every morning each model I pay for gets the same kind of coding job: fix nine bugs, then build a scheduler from a written spec. The details change daily so nothing can be memorized, but the work stays the same size. If time, tokens or the pass rate move, the model or the plan changed.

last run Wednesday, Oct 28 · every run on GitHub

Opus 5.5

Claude Max
More tokens than usual
157/ 157
Time
2m 30s
Tokens
253K
API price
$0.56
5h limit
1%

Fable 5.1

Claude Max
Slower than usual
157/ 157
Time
4m 18s
Tokens
216K
API price
$1.73
5h limit
3%

Sol 6.1

ChatGPT
Passed
157/ 157
Time
2m 36s
Tokens
162K
API price
n/a
5h limit
n/a

Astra

ChatGPT
Passed
157/ 157
Time
2m 28s
Tokens
138K
API price
n/a
5h limit
n/a

DeepSeek V4.1 Flash

OpenCode Go
More tokens than usual
157/ 157
Time
12m 31s
Tokens
2.8M
API price
$0.08
5h limit
under 1%

Trends

Same work, every day

Each line is one model on the day's task. Hover for the numbers, or click a name to pick it out.

Pass record

One dot per day. Red means it missed at least one hidden test.

Opus 5.5 100%
Fable 5.1 100%
Sol 6.1 88%
Astra 100%
DeepSeek V4.1 Flash 100%

Today's twist

What changed in Oct 28's version of the task.

Leftover cent goes to
the earlier share
Exact halves round
to the even cent
Fields look like
a=1| b='x'
Duration units
h m s
Day fields combine with
AND, both must match
Backwards ranges
wrap around
Search horizon
50 years
Split function is called
allocate_units()

How it works

Fair, boring, every day

Source and every result ↗
  1. Same work, new detailsNine bugs across five small modules, plus a cron-style scheduler built from a spec. A new variant is generated from the date, so every model gets the same task on the same day.
  2. Graded by hidden tests157 tests the model never sees check the work. Their answers come from a reference implementation that's itself checked against a brute-force search.
  3. No peekingEach model runs through its own CLI with fixed settings and none of my instructions. The hidden tests only exist after it's done, and any run that touches the grader is thrown out.

Today's models all pass this task nearly every time, so a red dot matters. Time, tokens and limit use are the trends to watch. Limit readings are whole percents shared with my other work, so a single day's number is rough.