2 measured metrics · 1 calculated · 2 studies
AgentvsGPT 5 mini
No row separates them: 1 tie, 2 unclear.
The verdict
Agent and GPT 5 mini share 2 measured metrics and 1 list-price calculation from 2 studies. No row separates them: every interval or run range overlaps, too few runs were recorded, no interval was recorded, or more is not better for that metric. The rows are 1 tie and 2 unclear; each row says why. Calculation rows are derived from list prices and recorded counts; they are not bills or runs. Agent is a full pipeline on one model; GPT 5 mini ran under a different, simpler harness, so this compares systems, not models.
Headline metrics
How far apart the two sides are on the headline metrics. Length is the ratio of the two values; it is not a winner.
Bar length is the ratio of the two values on a log scale, pointing to the larger one. Larger is not better for time, tokens or cost. A bar has a side’s color only when that side is ahead in the data; gray means the data does not separate them.
| Metric | Agent | GPT 5 mini | n | Interval or range | Outcome | Basis | Study |
|---|---|---|---|---|---|---|---|
| Resolved rate on the same 33 SWE-bench Verified instances | 76% (25/33)full pipeline on Claude Sonnet 5.5 | 64% (21/33)public mini-SWE-agent v2 run, same instances | 33 | 95% CI: 59%–87% vs 47%–78% | Tie | The 95% intervals overlap (Agent 59% to 87%; GPT 5 mini 47% to 78%), so this sample cannot separate them. | Agent on SWE-bench Verified vs 11 public models |
| Recorded cost per resolved instance: Agent vs the public panelCalculation | $3.71full pipeline on Claude Sonnet 5.5 · notional | $0.080public mini-SWE-agent v2 run, same instances | 25 / 21 | none recorded | Unclear | No interval or range was recorded for either side, so the gap ($3.71 vs $0.080, 46x) is not tested against run-to-run variation. | What if every call ran on Opus? Repricing real agent tokens |
| Model calls per instance | 49.5full pipeline on Claude Sonnet 5.5 | 20.8public mini-SWE-agent v2 run, same instances | 33 | none recorded | Unclear | More or fewer calls is not better or worse by itself; this row describes behaviour, not a winner. | Agent on SWE-bench Verified vs 11 public models |
Marks: 95% intervals (Wilson for rates)n is shown per side on every rowHollow marks: list-price calculations, not runs
3 headline metrics as the ratio of the two values. None of them separates the sides in the data. Widest ratio: Recorded cost per resolved instance: Agent vs the public panel, 46x (Agent larger).
Metric by metric
Both values of a row come from the same chart in the same study. Each row has its own axis. The shaded band is where the two intervals or ranges overlap: a side is ahead only when they do not.
- Agent
- GPT 5 mini
- 95% interval
- where the two overlap
- hollow: list-price calculation
These calculations hold each rate fixed and assume independent samples. They are not a power calculation or a paired test. Open the sample-size planner.
Agent on SWE-bench Verified vs 11 public models
- Resolved rate on the same 33 SWE-bench Verified instances76% (25/33)n 3364% (21/33)n 33TieResolved rate on the same 33 SWE-bench Verified instances: Agent 76% (25/33) (n 33, 95% interval 59%–87%); GPT 5 mini 64% (21/33) (n 33, 95% interval 47%–78%). Tie.
Calculation: at these rates, about 208 runs per side would separate them.
- Model calls per instance49.5n 3320.8n 33UnclearModel calls per instance: Agent 49.5 (n 33); GPT 5 mini 20.8 (n 33). Unclear.
What if every call ran on Opus? Repricing real agent tokens
- Recorded cost per resolved instance: Agent vs the public panelCalculation$3.71n 25$0.080n 21UnclearRecorded cost per resolved instance: Agent vs the public panel, calculation: Agent $3.71 (n 25); GPT 5 mini $0.080 (n 21). Unclear.
| Metric | Agent | GPT 5 mini | n | Interval or range | Outcome | Basis | Study |
|---|---|---|---|---|---|---|---|
| Resolved rate on the same 33 SWE-bench Verified instances | 76% (25/33)full pipeline on Claude Sonnet 5.5 | 64% (21/33)public mini-SWE-agent v2 run, same instances | 33 | 95% CI: 59%–87% vs 47%–78% | Tie | The 95% intervals overlap (Agent 59% to 87%; GPT 5 mini 47% to 78%), so this sample cannot separate them. | Agent on SWE-bench Verified vs 11 public models |
| Model calls per instance | 49.5full pipeline on Claude Sonnet 5.5 | 20.8public mini-SWE-agent v2 run, same instances | 33 | none recorded | Unclear | More or fewer calls is not better or worse by itself; this row describes behaviour, not a winner. | Agent on SWE-bench Verified vs 11 public models |
| Recorded cost per resolved instance: Agent vs the public panelCalculation | $3.71full pipeline on Claude Sonnet 5.5 · notional | $0.080public mini-SWE-agent v2 run, same instances | 25 / 21 | none recorded | Unclear | No interval or range was recorded for either side, so the gap ($3.71 vs $0.080, 46x) is not tested against run-to-run variation. | What if every call ran on Opus? Repricing real agent tokens |
Marks: 95% intervals (Wilson for rates)n is shown per side on every rowHollow marks: list-price calculations, not runs
3 rows from 2 studies. No row separates them: 1 tie, 2 unclear.
When to pick which
Only from the rows above. A tie is not a reason to pick either side.
When to pick Agent
No row in this data puts Agent ahead of GPT 5 mini. Pick on other grounds (price, access, the tasks you run), or measure your own workload.
When to pick GPT 5 mini
- Recorded cost per resolved instance: Agent vs the public panel: $0.080 vs $3.71. A list-price calculation, not a measured difference. Calculation
Side by side
The study charts, showing only these two. Open a study for every configuration.
| Item | Resolved rate | 95% interval | n |
|---|---|---|---|
| Agent (Sonnet 5.5, full pipeline) | 76% | 59%–87% | 33 |
| GPT 5 mini | 64% | 47%–78% | 33 |
2 rows. Highest Agent (Sonnet 5.5, full pipeline) 76% (95% interval 59%–87%, n 33). Lowest GPT 5 mini 64% (95% interval 47%–78%, n 33). All intervals overlap.
NotesWhiskers: 95% Wilson intervaln = 33 per row
Agent vs 11 public mini-SWE-agent v2 runs, one attempt each
Dots show the rate; whiskers show the 95% Wilson interval for n = 33. The panel compares models under one harness; Agent is a full system on one model.
Sources: Agent on SWE-bench Verified, campaign 1 (25 instances), Agent on SWE-bench Verified, campaign 2 (8 compiled-extension instances), SWE-bench Verified leaderboard, mini-SWE-agent v2 runs
Model calls per instance
Mean over the same 33 instances
| Item | Mean calls | n |
|---|---|---|
| Agent | 49.5 | 33 |
| GPT 5 mini | 20.8 | 33 |
2 rows. Highest Agent 49.5 (n 33). Lowest GPT 5 mini 20.8 (n 33).
Notesn = 33 per row
A panel call is one bash-agent step. An Agent call is one model request of any stage (research, plan, act, verify, review).
Sources: Agent on SWE-bench Verified, campaign 1 (25 instances), Agent on SWE-bench Verified, campaign 2 (8 compiled-extension instances), SWE-bench Verified leaderboard, mini-SWE-agent v2 runs
| Item | Cost per resolved instance | n |
|---|---|---|
| Agent (notional) | $3.71 | 25 |
| GPT 5 mini | $0.08 | 21 |
2 rows. Highest Agent (notional) $3.71 (n 25). Lowest GPT 5 mini $0.08 (n 21).
Notesn 21–25 per row
Same 33 SWE-bench Verified instances; all attempts in the numerator
Recorded figures, not repricing. Panel costs are published API costs for a bash-only agent. Agent's figure is a list-price estimate of subscription calls and includes onboarding, planning, verification and review.
Sources: Agent on SWE-bench Verified, campaign 1 (25 instances), Agent on SWE-bench Verified, campaign 2 (8 compiled-extension instances), SWE-bench Verified leaderboard, mini-SWE-agent v2 runs
How a row is called
- AheadThe 95% intervals do not overlap, or the run ranges or p50–p95 bands do not overlap with at least 5 runs per side.
- TieThe values match, or both sit at the same ceiling.
- UnclearThe intervals or ranges overlap, too few runs were recorded, no interval was recorded, or more is not better (token counts are never a win).
- CalculationDerived from list prices and recorded counts. Not a bill and not a run.
The dataset compiler makes every call; this page only draws it. No composite score, no rank.
Questions
- Which is better, Agent or GPT 5 mini?
- Agent and GPT 5 mini share 2 measured metrics and 1 list-price calculation from 2 studies. No row separates them: every interval or run range overlaps, too few runs were recorded, no interval was recorded, or more is not better for that metric. The rows are 1 tie and 2 unclear; each row says why. Calculation rows are derived from list prices and recorded counts; they are not bills or runs. Agent is a full pipeline on one model; GPT 5 mini ran under a different, simpler harness, so this compares systems, not models.
- How were Agent and GPT 5 mini measured?
- They share 2 measured metrics and 1 list-price calculation from 2 public studies: Agent on SWE-bench Verified vs 11 public models; What if every call ran on Opus? Repricing real agent tokens. Every row names its configuration, its sample size and its interval or range.
- How do Agent and GPT 5 mini compare on resolved rate on the same 33 SWE-bench Verified instances?
- Agent: 76% (25/33) (full pipeline on Claude Sonnet 5.5; n = 33; 95% interval 59% to 87%). GPT 5 mini: 64% (21/33) (public mini-SWE-agent v2 run, same instances; n = 33; 95% interval 47% to 78%). The 95% intervals overlap (Agent 59% to 87%; GPT 5 mini 47% to 78%), so this sample cannot separate them.
The studies behind this page
Agent on SWE-bench Verified vs 11 public models
Agent resolved 25 of 33 SWE-bench Verified instances (76%), inside the public panel's range on the same instances. Cost, time and calls.
What if every call ran on Opus? Repricing real agent tokens
Thought experiments on real tokens: the same SWE-bench agent work priced at Haiku, Sonnet, Opus, Fable, Gemini Flash, GPT and Jev list prices.