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e2e reference lens 1790522803022
GSM8K · 3 tasks · 1 harness · 1 model
GSM8K augmentation delivered the most efficient performance in this configuration.
Ranked shootout, no baseline arm: cells ranked by the composite score — the benchmark's own graders, then efficiency — claude-consumer / claude-sonnet-5 leads.
Abstract
This single-arm shootout evaluated three tasks with GSM8K augmentation across one harness/model cell. The treatment achieved a median cost of $0.0008 (mean $0.0009), consumed 159 median tokens (mean 138), and completed in a median 1.5s (mean 1.4s). Claude-consumer / claude-sonnet-5 ranked as the leader across cells. The benchmark was decided on efficiency grounds.
The result
claude-consumer
- 1claude-consumer / claude-sonnet-5100.0best
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-consumer | claude-sonnet-5 | 100.0 | 100% | − | − | 100% | 159 | $0.0008 | 1.5s | 3/3 |
Pass rate
100%over 3 graded runs| Cell | Pass rate | Tasks | Runs | Ran as | Matcher |
|---|---|---|---|---|---|
| claude-consumer/claude-sonnet-5 | 100% | 3 | 3 | as published | numeric |
Each run's answer was extracted from its response and matched against the benchmark's own key — no model in the loop. Two-stage: the mean over repeats per task, then the mean over tasks, with the interval taken over tasks.
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-consumer
Every metric, per harness × model
Benchmark pass rate
- claude-consumer / claude-sonnet-5100%
Task completion
- claude-consumer / claude-sonnet-5100%
Cost per run
- claude-consumer / claude-sonnet-5$0.0008
Tokens per run
- claude-consumer / claude-sonnet-5159
Duration per run
- claude-consumer / claude-sonnet-51.5s
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 | $0.0009 | $0.0008 | $0.0006 | $0.0012 | $0.0003 |
| Duration | treat | 3/3 | 1.4s | 1.5s | 1.3s | 1.6s | 113ms |
| Total tokens | treat | 3/3 | 138 | 159 | 96 | 159 | 36 |
| Output tokens | treat | 3/3 | 40 | 31 | 25 | 63 | 20 |
| Turns | treat | 3/3 | 1 | 1 | 1 | 1 | 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-consumer · claude-sonnet-5 · 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.