The cost of a fix, measured.
We ran five coding agents on real issues from fifteen open-source projects, once with DevOS and once without. Across the counted runs, fix rates were effectively level: 164/206 with DevOS and 163/206 without. The best observed result was a 71% lower cost to fix with DevOS. Every run is published below.
Seventeen tasks, five models, every run published.
Real issues from fifteen open-source projects in nine languages, worked by five agents across two coding CLIs. Every task, run and exclusion is available here.
5 models across 2 coding CLIs.
- Claude Sonnet 4.6Claude Code
- Claude Sonnet 5Claude Code
- Claude Opus 5Claude Code
- GPT-5.6 SolCodex CLI
- GPT-5.6 TerraCodex CLI
412 counted. 94 set aside.
Every result uses counted runs. Set-asides remain published with their reason.
Each model, with DevOS and without.
Each card is one agent on one kind of task, with DevOS and without. Every run it made is a bar.
Search-heavy fixes
element-web · 772df302JavaScript + element-web · a692fe21JavaScript + EFCorePowerTools · 3418C# + scala-steward · 3594Scala · 3 tries each per side · 12 planned a sideMost of the cost here goes to finding the right change and proving it. Knowing the codebase pays best on these: four of the five agents landed the same fixes for less with DevOS, two of them roughly a third cheaper.
Claude Sonnet 4.6 Claude Code
Claude Sonnet 5 Claude Code
Claude Opus 5 Claude Code
GPT-5.6 Sol Codex CLI
GPT-5.6 Terra Codex CLI
Mid-size fixes
NodeBB · 18c45b44JavaScript + openlibrary · 7bf32385Python + stateless · 644C# + just · 3200Rust + task · 2716Go + PhpSpreadsheet · 4541PHP + pana · 1489Dart + pub-dev · 8884Dart + rector-symfony · 797PHP + chezmoi · 5016Go · 3 tries each per side · 30 planned a sideThese tasks take real exploration before the change. Most agents come out level on cost here, and Claude Sonnet 4.6 comes out 28% ahead.
Claude Sonnet 4.6 Claude Code
Claude Sonnet 5 Claude Code
Claude Opus 5 Claude Code
GPT-5.6 Sol Codex CLI
GPT-5.6 Terra Codex CLI
Small fixes
openlibrary · d8162c22Python + fluentd · 4655Ruby + rubocop · 13705Ruby · 3 tries each per side · 9 planned a sideA handful of turns, well under a dollar. Jobs this small fit in any agent's head, so the differences here are cents. Most agents still came in level or a little cheaper with DevOS.
Claude Sonnet 4.6 Claude Code
Claude Sonnet 5 Claude Code
Claude Opus 5 Claude Code
GPT-5.6 Sol Codex CLI
GPT-5.6 Terra Codex CLI
Every model, all tasks together.
One line per agent, averaged over every task on this page, the deep work and the trivial alike.
| Model | Fixedwith DevOS | Cost per fixwith DevOS | Fixedwithout | Cost per fixwithout | Cost per fixdifference |
|---|---|---|---|---|---|
| Claude Sonnet 4.6Claude Code | 35/47 | $1.73 | 37/47 | $2.44 | −29% |
| Claude Sonnet 5Claude Code | 36/47 | $2.09 | 37/47 | $2.07 | +1% |
| Claude Opus 5Claude Code | 36/42 | $1.24 | 35/42 | $1.38 | −10% |
| GPT-5.6 SolCodex CLI | 37/47 | $0.72 | 35/47 | $0.76 | −5% |
| GPT-5.6 TerraCodex CLI | 20/23 | $0.65 | 19/23 | $0.59 | +10% |
Fixed counts are out of each side's completed runs. Green means DevOS cost less per fix.
We measure DevOS Memory too.
DevOS Memory connects a capability name to the code, configuration and tests behind it. This benchmark isolates that navigation: the task, model and project memory stay the same; only the feature map changes.
Less spend in all seven languages
Both sides produced the same result in every language. Using DevOS Memory cut spend 34% across the set and up to 82% on Go.
Three runs per side
Each language used the same issue, model and project memory on both sides. The only difference was whether DevOS Memory supplied the feature map.
Results by language
| Language | Project | Result using DevOS Memory |
|---|---|---|
| Go | chezmoi | Same fixes · 82% less spend |
| Rust | just | Same fixes · 17% less spend |
| Scala | Scala Steward | Same fixes · 12% less spend |
| C# | EF Core Power Tools | Same fixes · 11% less spend |
| Ruby | RuboCop | Same fixes · 6% less spend |
| Dart | pub.dev | No fix either side · lower spend |
| PHP | PhpSpreadsheet | No fix either side · lower spend |
Compared with the same DevOS setup without the feature map. Three runs per side. Scala used Opus; the other languages used Sonnet.
What it takes for a run to count.
These tasks are public and their fixes are published. Five rules keep the numbers honest, and every set-aside run is listed with its reason.
No internet during runs
Runs can't reach the internet, so an agent can't look up the fix. Attempts are blocked and logged.
A run that reached the web doesn't count
Some agents can call a web tool that runs on their provider's machines, outside the seal we control. We switch those tools off, then check every run's transcript to confirm the switch held. Any run that still reached the web is set aside, together with its matching run on the other side, whatever it scored.
Answers from memory don't count
If a model reproduces a project's published fix from memory, the run doesn't count, and neither does its matching run on the other side. Claude Opus 5 did this on the element-web tasks in both setups. We checked every one of those runs by hand and set them aside.
A DevOS run has to use DevOS
Runs that skipped DevOS say nothing about it. They are set aside, together with their matching runs on the other side.
Reported straight
Results stay per task and per agent. A one-fix difference across three runs is called a tie whichever side it favours.
Cost basis. Claude Code costs are the provider's own session figures. Codex CLI costs are measured tokens at list prices.
Environments. Both sides run in identical, isolated copies of each project.
Sample size. Every figure carries its run count. A saving gets named when it held across runs, and anything inside the run-to-run spread is reported as even. From 506 runs recorded on 2026-08-06. See every one.
Run the comparison on your own stack.
The same layer that produced these numbers installs over the agents your team already runs, measured against your own baseline from day one.