Measured · Study1views
acceptance row1 1790522824583
GSM8K · 3 tasks · 1 harness · 1 model
GSM8K augmentation delivered the strongest efficiency gains with openai-compatible / gpt-oss-120b.
Ranked shootout, no baseline arm: cells ranked by the composite score — the benchmark's own graders, then efficiency — openai-compatible / gpt-oss-120b leads.
Abstract
This single-arm shootout evaluated GSM8K augmentation across 3 tasks and 2 harness/model cells, with openai-compatible / gpt-oss-120b as the leader. Efficiency was the deciding factor: the treatment achieved a median cost of $0.0001 (mean $0.0001), median tokens of 277 (mean 330), and median duration of 719ms (mean 994ms).
The result
openai-compatible
Best setup: openai-compatible / gpt-oss-120b · effort high (99.7 of 100)
- 1openai-compatible / gpt-oss-120b · effort high99.7best
- 2openai-compatible / gpt-oss-120b · effort low72.6
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 | openai-compatible | gpt-oss-120b · effort high | 99.7 | 100% | − | − | 100% | 254 | $0.0001 | 743ms | 3/3 |
| 2 | openai-compatible | gpt-oss-120b · effort low | 72.6 | 67% | − | − | 100% | 299 | $0.0001 | 834ms | 3/3 |
Pass rate
83.3% (95% CI 50–100)over 6 graded runs| Cell | Pass rate | Tasks | Runs | Ran as | Matcher |
|---|---|---|---|---|---|
| openai-compatible/accounts/fireworks/models/gpt-oss-120b · effort high | 100% | 3 | 3 | as published | numeric |
| openai-compatible/accounts/fireworks/models/gpt-oss-120b · effort low | 66.7% (95% CI 0–100) | 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 per task
Every graded run, standardized WITHIN its task so difficulty cancels out: → right = fewer tokens than the field on the same task, ↑ up = higher quality index (85% the benchmark's own pass/fail + 15% outcome) than the field. 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.
openai-compatible
Every metric, per harness × model
Benchmark pass rate
- openai-compatible/accounts/fireworks/models/gpt-oss-120b · effort high100%
- openai-compatible/accounts/fireworks/models/gpt-oss-120b · effort low67%
Task completion
- openai-compatible/accounts/fireworks/models/gpt-oss-120b · effort high100%
- openai-compatible/accounts/fireworks/models/gpt-oss-120b · effort low100%
Cost per run
- openai-compatible/accounts/fireworks/models/gpt-oss-120b · effort high$0.0001
- openai-compatible/accounts/fireworks/models/gpt-oss-120b · effort low$0.0001
Tokens per run
- openai-compatible/accounts/fireworks/models/gpt-oss-120b · effort high254
- openai-compatible/accounts/fireworks/models/gpt-oss-120b · effort low299
Duration per run
- openai-compatible/accounts/fireworks/models/gpt-oss-120b · effort high743ms
- openai-compatible/accounts/fireworks/models/gpt-oss-120b · effort low834ms
By harness, by model
By harness
By model
Benchmark pass rate
By harness
- openai-compatible83%
By model
- gpt-oss-120b83%
Task completion
By harness
- openai-compatible100%
By model
- gpt-oss-120b100%
Cost per run
By harness
- openai-compatible$0.0001
By model
- gpt-oss-120b$0.0001
Tokens per run
By harness
- openai-compatible277
By model
- gpt-oss-120b277
Duration per run
By harness
- openai-compatible719ms
By model
- gpt-oss-120b719ms
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 | 6/6 | $0.0001 | $0.0001 | $0.0001 | $0.0003 | $0.0001 |
| Duration | treat | 6/6 | 994ms | 789ms | 563ms | 1.7s | 493ms |
| Total tokens | treat | 6/6 | 330 | 277 | 207 | 525 | 140 |
| Output tokens | treat | 6/6 | 194 | 124 | 91 | 386 | 135 |
| Turns | treat | 6/6 | 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.
openai-compatible · fireworks · gpt-oss-120b · Your setup1 finding
- 6 of 6 runs · 6 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 6Show 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
- 2 cells × 3 tasks × 1 arm = 6 runs.