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SWE-bench Verified · five harnesses · any model

Any harness. Any model.
Measured the same way.

An open evaluation rig that runs coding agents on SWE-bench Verified at scale, enforces hard cost limits per problem from outside the agent, grades with the official harness, checks every number for contamination, and publishes each result with the provenance to reproduce it.

What the runs showed

Six findings. Each card links to the page with the run ids, intervals and provenance behind it.

All results →
379 = 379of 500, ours vs official

The reference run reproduces the official leaderboard

mini-swe-agent × MiniMax M2.5 resolves 379 of 500 here and 379 of 500 on swebench.com's Bash Only entry, with 88.4% per-instance agreement and cost within 10.7%. Same grading, same images, independently run.

Versus the official leaderboard →
1.5×the bill between the leanest and heaviest scaffold, for one outcome

The harness decides what gets burnt, not what gets solved

Five harnesses on one model and the same 500 problems land between 75.8% and 77.0% with overlapping intervals. The bill differs 1.5×, and the judge's redundant-call flags run from 52 to 258 of 500 attempts depending on the scaffold.

By harness →
4.5×per resolved instance, for the model that is 5–10× cheaper per token

Cheaper per token is not cheaper per task

Laguna xs 2.1 and MiniMax M2.5 on the same harness, prompt, tools and limits resolve the same share of 78 problems; Laguna carries 7.5× the prompt tokens and costs 4.5× as much per resolved instance. Only the per-call ledger shows why.

Model vs model →
−35.6%cost on Laguna, −27.3% on MiniMax M2.5, same resolve rate

Efficiency can be engineered, and it has to be enforced

Five working rules in the system prompt cut the bill by a quarter to a third on the same 78 problems with no measurable change in outcome. The rule both models ignored, stop once tests are green, is the one the harness now has to enforce; the judge measures the waste that remains.

What a prompt can buy →
384 vs 385two-tool loop vs the best full CLI, of 500

A two-tool loop keeps up with the commercial scaffolds

The framework's own control agent, one loop and two tools, resolves 384 of 500 at $34: inside the noise of the four CLIs. What a scaffold adds shows up in the bill and in the judge's efficiency findings, not in the resolve rate.

The custom minimal agent →
12 in 2,509contamination flags, every one with a cited turn

The judge found the rig's bug first, and twelve memorisation flags in 2,509 attempts

Rubric v3 read every attempt of the five runs. Its first pass flagged 221 of 500 OpenCode attempts for a search tool broken in the isolated image, a framework defect fixed and re-run. Across all five it raised 12 contamination flags, none citing anything reachable inside the container, and one class of test gaming no static check sees.

LLM judge →

How a run works

From a launch request to a graded, judged, published result — every step enforced by a component that does not trust the agent.

Architecture →

Launch

Pick the harness, the model, the instances and the limits. A per-run provider key carries the budget as a hard cap.

Isolated agents

One container per instance, no internet, repository history pruned at the base commit. A local proxy shim meters every call.

Paced inference

One gateway for every call. A token-bucket pacer and an autoscaler keep hundreds of agents inside the provider's real limits.

Official grading

The official SWE-bench harness in the official per-instance images, pulled by digest, each one gold-patch validated first.

Judge and publish

An evidence-required LLM judge reads the trajectories; every number ships with its run id, model, commit and limits.

What it measures, and what it refuses to hide

Resolve rate is one number. The rig records the cost, the behaviour and the integrity checks behind it.

The headline number

Five harnesses on the same model and the same 500 problems. The scaffold barely moves the resolve rate; it moves the bill.

All results →

Cost per resolved instance

USD of inference per resolved SWE-bench Verified instance · minimax/minimax-m2.5 · lower is better

Inference spend only, from the gateway's own metering (compute cost is reported separately on the Cost page). Sorted cheapest first. A missing bar is an unmeasured run, not a free one.

How to read it

  • Resolve rates run from 75.8% to 77.0% and every 95% interval overlaps every other — at n = 500, the harness does not change the outcome by more than the noise.
  • Cost does separate them: the cheapest harness spent about two thirds of what the most expensive one did for the same outcome.
  • The OpenCode row is a re-run on a fixed image; the first run, whose search tools were broken, is kept as a documented defect on the Integrity page.
Provenance — what this run actually measured
run
01789087148400722169-0c9303b3 · 2026-09-11
model
openrouter/minimax/minimax-m2.5 (alias minimax-m2.5-opencode)
harness
OpenCode · CLI 1.18.18 (pinned in the harness image build at this framework commit)
framework
631be843b55ccabe33347f0a7de2f7ee0676ce1a
harness image
sha256:c8c56129b240e898fb5de452b50e36ad1aedf04fada946592ee98ca757753564
benchmark
SWE-bench/SWE-bench_Verified @ 78f471bf655a · swebench 5.0.2 · images SWE-bench_Verified-78f471bf655a.json
network
isolated
explore
this run in the Explorer: every instance, its trajectory and patch, every inference call, the judge’s verdicts
download
this run's artifacts (patches, trajectories, call ledgers, eval reports, judge passes) · preds.jsonl · all runs

Built to be argued with

Every claim on this site traces to a run id, a commit and a committed export. Anything not measured says so — it is never rendered as zero.

Reproduce it
  • Both denominators and a Wilson 95% interval on every rate
  • Provenance block on every page that shows a number
  • Official grading, official images, dataset revision pinned — reproduces the official leaderboard's mini-swe-agent × MiniMax M2.5 entry to the decimal
  • Per-call ledgers and trajectories published per run
  • One person, four weeks, and the receipts for what it cost