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acceptance row3 1790523938508
MBPP · 3 tasks · 1 harness · 1 model
MBPP with claude-haiku-4-5-20251001 delivered measurable efficiency on the tasks evaluated.
Ranked shootout, no baseline arm: cells ranked by the composite score — the benchmark's own graders, then efficiency — claude-code / claude-haiku-4-5-20251001 leads.
Abstract
This single-arm shootout evaluated MBPP across 3 tasks on one harness/model cell. The treatment achieved a median cost of $0.03 (mean $0.03), median tokens of 35.1k (mean 36.2k), and median duration of 28.6s (mean 33.3s). No baseline arm was run by design, so this benchmark measures the treatment's absolute performance rather than a comparative gain. The leader across all cells is claude-code / claude-haiku-4-5-20251001.
The result
claude-code
- 1claude-code / claude-haiku-4-5-20251001100.0best
Overall score per cell, 0–100 points (not a pass rate): 75% benchmark pass rate (the benchmark's own graders carry the outcome share — no judge grades or evals on this board) + 25% efficiency (cost · tokens · duration, vs the board's best arm). Absent components renormalize. Best at the top — the board's best setup is tagged.
Leaderboard
Cells ranked by the composite score — outcome (the lenses that graded) × efficiency — absolute values, no baseline arm. Tokens, cost and duration are per-cell medians, the efficiency the score folds.
| # | Harness | Model | Score | Pass rate | Quality | Evals | Goal | Tokens | Cost | Duration | Runs |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | claude-code | claude-haiku-4-5-20251001 | 100.0 | 100% | − | − | 100% | 35.1k | $0.03 | 28.6s | 3/3 |
Quality × efficiency clusters — normalized across the study
Every graded run, standardized across the study — each task ran once, so there is no field per task to compare against: → right = fewer tokens than the study's average run, ↑ up = higher quality index (85% the benchmark's own pass/fail + 15% outcome) than average. Every run scored alike on quality here, so the vertical axis separates nothing — read the map left to right. The field pools every harness and model, so a setup's left–right position largely reflects its own token habits. Dots are runs; each harness logo is a harness × model × arm centroid — hover it for the model and averages. Up-right wins.
claude-code
Every metric, per harness × model
Benchmark pass rate
- claude-code / claude-haiku-4-5-20251001100%
Task completion
- claude-code / claude-haiku-4-5-20251001100%
Cost per run
- claude-code / claude-haiku-4-5-20251001$0.03
Tokens per run
- claude-code / claude-haiku-4-5-2025100135.1k
Duration per run
- claude-code / claude-haiku-4-5-2025100128.6s
Distributions
Every completed run is one dot — the spread the averages hide. Click a dot to replay that run's journey.
Cost per run
Token composition — average per run
Statistics
| Metric | Arm | n | Mean | Median (pooled) | Min | Max | Std dev |
|---|---|---|---|---|---|---|---|
| Cost | treat | 3/3 | $0.03 | $0.03 | $0.01 | $0.05 | $0.02 |
| Duration | treat | 3/3 | 33.3s | 28.6s | 24.6s | 46.9s | 11.9s |
| Total tokens | treat | 3/3 | 36.2k | 35.1k | 35k | 38.3k | 1.8k |
| Output tokens | treat | 3/3 | 1.9k | 977 | 747 | 4k | 1.8k |
| Cache-read tokens | treat | 3/3 | 20.8k | 31.3k | 0 | 31.3k | 18k |
| Cache-write tokens | treat | 3/3 | 13.4k | 3.1k | 2.9k | 34.3k | 18.1k |
| Turns | treat | 3/3 | 2 | 2 | 2 | 2 | 0 |
n = runs carrying the fact / completed runs in the arm; every statistic runs over present facts only — a missing fact is never counted as 0. Std dev is the sample form (n−1), withheld below n = 2. Every figure here POOLS all runs. The typical-run figures in the abstract, the head-to-head decision and the per-setup panels take each task's median first and then the median across tasks, so a task that ran more often never outweighs one that ran once; the two medians can differ. A promise study's headline (“cut average tokens”) compares per-arm means.
What each setup did
Derived from each run's recorded tool calls — not from a model's description of the run — and aggregated per setup, so a behavior seen across several runs is stated once with its rate. Open a finding to see the runs behind it, each linked to its journey at the step where it happened.
claude-code · anthropic · claude-haiku-4-5-20251001 · Your setup1 finding
- 3 of 3 runs · 3 completed
Task text withheld
Task text withheld — this benchmark is guarded and its tasks are not republished here.
Tasks
Task text withheld — this benchmark is guarded and its tasks are not republished here.
Task text withheld — this benchmark is guarded and its tasks are not republished here.
Task text withheld — this benchmark is guarded and its tasks are not republished here.
Runs
Every run is inspectable — open one to replay the agent's journey step by step, with the analyst's read underneath.
Every run, filterable… of 3Show runsHide runs
| Harness | Model | Task | Completed | Pass | Tokens | Cost | Duration |
|---|
Loading runs…
Methodology
What each metric means
- Completed
- The run finished and the harness returned a response. It does NOT mean the answer was correct — a completed run can score zero on quality.
- Denominator: Terminal runs, excluding those killed by our own infrastructure.
- Quality index
- A composite used only in the quality x efficiency plot, built from whichever grader scored this study's runs — the judge's rubric, the pre-registered checks or the benchmark's own verdict — plus whether the run's own outcome was success. The map's caption names the grader and its weights.
- Denominator: Graded runs — runs the study's grader scored.
- Infra-excluded
- A run killed by our own infrastructure. It is a missing measurement, never a loss for the arm, and is excluded from every rate denominator.
- Denominator: Reported as a count beside every affected panel.
- Single arm
- Every task runs once per harness × model cell — a shootout with no baseline arm. The readout is absolute (quality, success, tokens, cost) and the cells are ranked into a leaderboard.
- One run per task
- Every task ran once per cell, in one phrasing. Run-to-run variation is therefore not measured: a single task's difference can be one lucky or unlucky attempt. Every row of the reference table treats the TASKS as the unit: its intervals resample the tasks and its p-values come from a paired test over them, so they describe how much the result depends on which tasks were drawn — not how it would change if the same tasks were run again. With few tasks no difference can reach significance (five tasks cannot go below p = 1/16).
- Sample size
- 1 cell × 3 tasks × 1 arm = 3 runs.