// mondaybench #002 beta

We gave 15 models
the same messy Monday morning

Nine sources. A release that failed on Friday, two ways to recover it, and four people whose calendars barely overlap.

One question: Can it tell what changed?

  • 15 models
  • 3 runs each
  • Opus 5 judge
  • frozen & auditable
01

The result

Fifteen models, 45 runs, one judge.

// results

The leaderboard

Monday Score is quality only: how well each model answered “Can it tell what changed?”, criterion by criterion against this scenario’s rubric. Speed sits beside it and is never folded in.

All models Open-weight models only

monday-002 · 15 models, 3 runs each
# Model Monday Score Run range TTFA median Total latency Show detail for
01 GPT-6 Astra closed
100.0
0.0 — —
02 Claude Opus 5 closed
98.0
3.0 — —
01 03 DeepSeek V4.1 Flash (1017)
95.2
8.0 84.3s 93.2s
02 04 Qwen 3.8 Flash
94.8
8.5 258.9s 285.0s
03 05 DeepSeek V4.1 Flash
93.0
10.5 61.2s 67.8s
04 06 GLM 5.2
91.2
8.0 67.0s 85.4s
07 Claude Fable 5.1 closed
91.0
6.0 — —
05 08 DeepSeek V4 Flash
89.3
13.5 162.6s 178.8s
06 09 GLM 5.3
87.7
4.0 176.2s 197.1s
07 10 GLM 5.3 Flash
87.3
6.5 238.5s 316.6s
08 11 MiMo v2.6 Flash
83.7
4.0 257.0s 322.0s
09 12 MIMO v2.5
81.2
33.0 163.3s 195.4s
13 Gemini 3.8 Flash (High) closed
80.0
1.5 — 38.8s (route-timed)
10 14 Qwen 3.6
70.2
31.0 0.9s 18.2s
11 15 Gemma 4
54.2
13.5 0.3s 8.7s
  • Run range: the difference between the model’s best and worst official run. It is a plain best-minus-worst span, so it is never written as ±.
  • TTFA, time to first answer: the wall-clock delay before the first visible answer token. Reasoning tokens do not count as answer content.

// quality vs speed

The smartest model isn’t always the fastest

Of the timed models, DeepSeek V4.1 Flash (1017) scores highest, 95.2, and takes 84.3s to start answering. Gemma 4 is the quickest: it starts in 0.3s and scores 54.2. Qwen 3.8 Flash is the slowest, 258.9s, for 94.8.

50 60 70 80 90 100 0s100s200s TTFA median, seconds to first answer Monday Score DeepSeek V4.1 Flash (1017) 95.2 · 84.3s Qwen 3.8 Flash 94.8 · 258.9s DeepSeek V4.1 Flash 93.0 · 61.2s GLM 5.2 91.2 · 67.0s DeepSeek V4 Flash 89.3 · 162.6s GLM 5.3 87.7 · 176.2s GLM 5.3 Flash 87.3 · 238.5s MiMo v2.6 Flash 83.7 · 257.0s MIMO v2.5 81.2 · 163.3s Qwen 3.6 70.2 · 0.9s Gemma 4 54.2 · 0.3s
Monday Score and time to first answer, per model
Model Monday Score TTFA median
DeepSeek V4.1 Flash (1017) 95.2 84.3s
Qwen 3.8 Flash 94.8 258.9s
DeepSeek V4.1 Flash 93.0 61.2s
GLM 5.2 91.2 67.0s
DeepSeek V4 Flash 89.3 162.6s
GLM 5.3 87.7 176.2s
GLM 5.3 Flash 87.3 238.5s
MiMo v2.6 Flash 83.7 257.0s
MIMO v2.5 81.2 163.3s
Qwen 3.6 70.2 0.9s
Gemma 4 54.2 0.3s

// what stood out

Benchmark curiosities

Every figure below is one you can check against the leaderboard, the criterion matrix or the published verdicts on the same page.

  1. 01

    12 / 45

    runs chose the safer path

    Option B

    Most runs traded safety for a deadline they were not short of

    Both recovery paths open rollout at 11:00, an hour inside the cutoff. Option B carries an eighth of the session-reset risk at no cost in time. Thirty-three of forty-five runs did not choose it. GPT-6 Astra and Claude Opus 5 chose it on all three of their runs; no open model chose it on more than one of three. The plan fits only if the sequence starts at 09:07, when the diff can be submitted; starting at 09:15, when the engineer arrives, leaves too little time.

  2. 02

    #3 → #10

    between #001 and #002

    GLM 5.3 Flash

    The best open model on the first scenario came tenth in this one

    The two scenarios test different skills. #001 rewards noticing what changed; #002 rewards building a plan that runs. GLM 5.3 Flash’s three runs land within 6.5 points of each other, and none of them chose the safer release path.

  3. 03

    64.5 – 97.5

    three runs, same prompt

    MIMO v2.5

    One model produced its best and its worst answer on the same input

    A 33-point range, the widest here. Its best run, taken alone, would place third on this board of fifteen; its worst, which states that Security verification is not needed and then schedules it anyway, would place fourteenth. Three runs per model exists for exactly this: on one run, MIMO looks like a top-three model or a bottom-two one depending on which you draw.

  4. 04

    3 / 3

    plans that cannot be executed

    Gemma 4

    One model recommended an impossible plan on every run

    All three of its runs schedule the deploy to start after the only engineer who can run it has left — one of them at 10:30, ten minutes past his hard stop. That is what the MAJOR_PLANNING_ERROR penalty is scoped to, and Gemma 4 is the only model that triggered it on every one of its runs.

02

The test

What they were given, and what they had to work out.

// the test

This is a problem of joining scattered pieces

On Friday the production deploy of build 2.9.4 failed on shard eu-03 before rollout opened, and Atlas, a signed customer, needs that rollout to have begun by 12:00 Monday or its migration slips to Thursday. There are two ways back: Option A retries 2.9.4 with a shard precheck (8% session-reset risk); Option B ships 2.9.5-patch (under 1%), which, being a code change, first needs Priya’s 25-minute Security delta review. Either way she runs a 20-minute post-deploy verification before Sam can open rollout.

Who is free, and when

09:00 09:30 10:00 10:30 11:00 11:30 12:00 Marcus Priya Sam Daniel
  • now · 09:07
  • Marcus leaves · 10:20
  • Atlas rollout must have begun · 12:00

The two recovery paths · A

2.9.4

Retry the build that already failed once, with a shard precheck.

deploy
20 min
session-reset risk
8%
 
no code change

The two recovery paths · B

2.9.5-patch

A patch that avoids the migration path that broke. Needs a Security delta review first.

deploy
45 min
session-reset risk
<1%
 
code change

Option B, sequenced

09:00 09:30 10:00 10:30 11:00 11:30 12:00 Priya Security delta review · 25m Marcus Deploy 2.9.5-patch · 45m Priya Post-deploy verification · 20m Sam Open and sanity-check rollout · 15m

Option B’s deploy finishes 3 minutes before Marcus leaves, and that is all the margin it has. Rollout still opens at 11:00 on both paths, because both wait for Priya’s verification after she is back at 10:25.

The step that makes it fit

Priya reviews asynchronously from a submitted diff, and she is free from 09:00. The chain starts at 09:07 with an action the user can take, without waiting for Marcus to arrive at 09:15.

What happened

Both paths open rollout at 11:00, 60 minutes inside the deadline. Option B carries an eighth of the risk at no cost in time. 12 of 45 official runs chose it; 31 of 45 never built a schedule that showed it fits.

Miss it and migration slips to Thursday. The renewal is signed, so the cost is executive noise; revenue is not at stake.

// the answer key

What a right answer does

  1. Choose Option B and submit the diff at 09:07. Review 09:07–09:32, deploy 09:32–10:17 (three minutes before Marcus’s 10:20 hard stop), verification 10:25–10:45 once Priya is back, rollout 10:45–11:00. Option A also opens rollout at 11:00, because it waits for the same verification: it saves no time and carries eight times the risk.

  2. Close the €54k expansion gap before 11:00: Wayne €18k, Globex €12k, Soylent €10k, Wonka €14k. Only Wayne (a signed move to October) and Globex (procurement) have a stated cause.

  3. Globex is the real account risk: renewal in 18 days, usage −18%, admin logins −61%, three open tickets. Acme’s −45% is the approved shift to batch processing that its contract notes, so it does not count as churn.

  4. Don’t reinstate the CEO sign-off, promise a launch time to a customer, send the launch email yourself (Daniel owns it now) or send Enterprise pricing out from the stale internal workbook.

  5. Orion stays open: neither ON nor OFF until someone confirms which org ID is theirs and reads the live flag for it.

Condensed from the published ground truth, ground_truth.md.

03

The method

How the score is built, and how to check it.

// scoring

How Monday Score works

One hundred points across 6 dimensions, then penalties. Quality only: speed and cost are reported separately, beside the score.

  1. State reconstruction Does it know what is currently true? 15
  2. Temporal supersession Does it notice what a later message overruled? 15
  3. Planning and dependencies Can it build a plan that would actually run? 25
  4. Decision and prioritisation Does it act on the tightest constraint first? 20
  5. Cross-source reasoning Does it combine files, and keep arithmetic apart from cause? 15
  6. Uncertainty Does it refuse to settle what the evidence cannot? 10
  7. total 100

The judge does not assign a 0–⁠100 score directly

It classifies atomic criteria one at a time, 20 of them in rubric 0.2, and each verdict carries the evidence it was based on. Deterministic scoring code turns those verdicts into points. No model ever sees a running total.

  • PASS full points for the criterion
  • PARTIAL half points
  • FAIL nothing

Where a response sits between two labels, the rubric’s own tie-break applies: choose the lower one.

Penalties

Applied on top of the dimension score, capped at −30 per run.

  • −5 Material hallucination A claim that matters to the briefing and is not supported by the material.
  • −10 Prohibited action Recommending something the current state explicitly rules out.
  • −7 Major planning error Recommending a plan that cannot run under the stated dependencies or availability.
  • −5 Major contradiction Contradicting itself about the state of an important issue.

Each scenario’s rubric sets its own penalty types, their prices and the cap. A prohibited action costs −10 (#001), −10 (#002), −7 (#003), −7 (#004), −7 (#005); the cap per run is −20 (#001), −30 (#002), −25 (#003), −25 (#004), −14 (#005).

see_the_methodology →

// provenance

Exactly what produced these numbers

Every input, raw response, judge verdict and scoring rule for this scenario is published. The hash below is of the assembled prompt each model received, byte for byte.

Scenario

monday-002

Scenario version

0.2

Rubric

0.2

Evaluator

evaluator-opus5-v0.2

Judge

claude-opus-5

Result generated

2026-10-19

Suite v1.14 · board evidence v1.13

Prompt SHA-256

740e627cbc7413c321ede0d54000504de54821d34ff4677f82731b89600423a8

Attempts needed for three valid runs

A run can be rejected before it is ever scored: truncated, or returning no reasoning when reasoning was requested, or a cached duplicate. Those never reach a leaderboard, because a leaderboard can only exclude what it evaluated. It describes the model and its endpoint, so it is reported apart from the score.

  • Qwen 3.8 Flash 3 of 4 attempts REASONING_NOT_DELIVERED

One run was generated and scored but does not count

  • monday-002__qwen3.8-flash__002 66.5 The provider served this run without the reasoning phase its two sibling runs used — zero reasoning tokens against 42,808 and 30,342 — so it was not comparable with them. Its score and its evidence stay published, and it is left out of the model’s result.

// why we built this

Benchmarks are useful,
but what matters is your workload

We compare open models in production so you can tell how close they are to closed models. MondayBench is how we check whether they are really useful before they get there.