The 500 OSS Performance Indexv0.1
AI is reshaping engineering every day. We track the change across the repos that power the industry, giving you the baseline that moves with the market.
How we measure each PR, and why the leaders are pulling away.
Show methodologyHide methodologyEngineering is in the middle of its sharpest productivity shift since the move to the cloud. AI-assisted authoring, autonomous agents, and code-generation tooling are compounding inside review and merge, and the teams that picked them up first are not waiting for the rest. Output per engineer at the top is pulling away from the median fast enough that the gap reshuffles week to week.
Engineering Throughput Value scores every merged commit by the depth of work it represents (Growth, Maintenance, Fixes), then averages it per active contributor and normalizes to a 30-day calendar month using a 90-day moving window.
The fraction of merged code attributable to AI-augmented authoring, aggregated quarterly from public commit metadata.
A damped extrapolation of the rolling 90-day per-month trend forward one year, with a confidence cone that widens further from today.
Engineering isn't just speed. It's building the right thing. But the minimum speed required to build the right thing keeps rising, because the teams that iterate fastest learn fastest. You're much more likely to ship something users actually want when you can take twenty shots at it instead of two.
The 500 OSS Performance Index
+124.8%
from 0.86 to 1.94 ETV / dev / mo across the 90d rolling series
Growth share change
+4.4 pp
from 32.5% to 36.9% across the 90d rolling series
Maintenance share change
−7.1 pp
from 53.5% to 46.3% across the 90d rolling series
Fixes share change
+2.8 pp
from 14.0% to 16.7% across the 90d rolling series
Engineering performance is shifting faster than annual planning can track. Knowing where your team stands, in real numbers, is the only way to move it. You can only bend a curve you can see.
Rolling 90-day Performance per org, normalized to a 30-day month. Δ compares the first 90-day window after launch to the latest.
Performance Index
Avg performance
1.94 ETV
per developer per month
Total ETV / month (90-day MA)
+124.8%
Work mix
Growth
38%
Maintenance
47%
Fixes
16%
Jun 29, 2025 – May 27, 2026
Pooled across all orgsAvg performance
2.74 ETV
per developer per month
Total ETV / month (90-day MA)
+139.8%
Work mix
Growth
44%
Maintenance
38%
Fixes
17%
Jun 29, 2025 – May 28, 2026
Company breakdownAvg performance
1.19 ETV
per developer per month
Total ETV / month (90-day MA)
+43.3%
Work mix
Growth
33%
Maintenance
53%
Fixes
13%
Jun 29, 2025 – May 28, 2026
Company breakdownAvg performance
6.13 ETV
per developer per month
Total ETV / month (90-day MA)
>+999%*
Work mix
Growth
41%
Maintenance
47%
Fixes
12%
Jun 29, 2025 – May 28, 2026
Company breakdownAvg performance
3.08 ETV
per developer per month
Total ETV / month (90-day MA)
+183.7%
Work mix
Growth
32%
Maintenance
48%
Fixes
21%
Jun 29, 2025 – May 27, 2026
Company breakdownAvg performance
1.41 ETV
per developer per month
Total ETV / month (90-day MA)
+65.8%
Work mix
Growth
34%
Maintenance
53%
Fixes
13%
Jun 29, 2025 – May 28, 2026
Company breakdownAvg performance
1.01 ETV
per developer per month
Total ETV / month (90-day MA)
+153.5%
Work mix
Growth
36%
Maintenance
47%
Fixes
17%
Jun 29, 2025 – May 28, 2026
Company breakdownSee how your engineering team scores against the orgs that built the industry. Public on the leaderboard, or private in your own workspace.
Pick an organization and a monthly AI budget. The spend splits into Growth, Maintenance, and Fixesby that org's real work mix, then lands as a cost per ETV delivered, per developer, and per repository, so you can see where a dollar of AI spend goes furthest.
How much do these companies spend on AI each month? Take a guess and read the return. Your budget splits into Growth, Maintenance, and Fixes by the chosen org's actual work mix, then normalizes against the ETV it delivers, its developers, and its repositories. Cost per ETV delivered is the bottom line: the lower it is, the better the AI ROI.
Guess what this company spends on AI each month, then see the ROI below.
Spend per ETV delivered
$231
What every 1 ETV of engineering value this org delivers costs in AI budget. Lower means better AI ROI.
Spend per developer
$633
Budget spread across 158 active contributors.
Spend per repository
$8,333
Budget spread across 12 active repositories.
$44.1K / mo
Net-new capability. Features and functionality that did not exist before.
$38.5K / mo
Sustaining what already exists. Refactors, dependency upkeep, and docs.
$17.4K / mo
Rework. Fixing bugs and replacing code that did not hold up.
| Repository | Spend / mo | Split (Growth / Maintenance / Fixes) |
|---|---|---|
vscode 942 ETV · 72% of org | $72,500 | $34.9K$24.6K$13K |
playwright 122 ETV · 9% of org | $9,384 | $3.1K$4.8K$1.5K |
FluidFramework 69 ETV · 5% of org | $5,308 | $1.9K$3K$484.2 |
fluentui 62 ETV · 5% of org | $4,781 | $1.8K$2.4K$615.9 |
PowerToys 54 ETV · 4% of org | $4,139 | $1.7K$1.3K$1.1K |
Agents-for-net 23 ETV · 2% of org | $1,798 | $397.8$1.2K$163.1 |
semantic-kernel 16 ETV · 1% of org | $1,228 | $234$835.3$158.6 |
terminal 6 ETV · 0% of org | $443 | $131.6$80.1$231.7 |
DeepSpeed 4 ETV · 0% of org | $306 | $22.4$186$97.2 |
TypeScript 1 ETV · 0% of org | $67 | $3.8$44.7$18.5 |
autogen 1 ETV · 0% of org | $43 | $0$18.5$24.6 |
markitdown 0 ETV · 0% of org | $4 | $1$2.9$0 |
Illustrative model. The per-unit figures move only with each org's delivered ETV, team size, repository count, and work mix. Token counts assume the blended price above across all models.
Curious how much money this work actually brings in? Connect this data to Jira or Linear to tie engineering output to business impact and revenue. Available with the Navigara on-prem deploy.
See business impactTop repositories ranked by Engineering Throughput Value (ETV) per developer. The 7-day board shows where momentum is this week; the 90-day board shows where it's been over the quarter.
Highest per-developer Engineering Throughput Value (ETV) shipped in the last 7 days — 7-day snapshot, not normalized to a month. Hover any value for the full formula.
turborepo
Vercel · 1 dev
2.0
ETV / dev · 7d
agents
Cloudflare · 3 devs
1.9
ETV / dev · 7d
fbthrift
Meta · 11 devs
1.8
ETV / dev · 7d
semantic-kernel
Microsoft · 1 dev
1.5
ETV / dev · 7d
sandbox-sdk
Cloudflare · 2 devs
1.5
ETV / dev · 7d
Highest per-developer Engineering Throughput Value (ETV) over the trailing 90 days, normalized to a 30-day calendar month. Hover any value for the full formula.
openai-agents-js
OpenAI · 1 dev
13.6
ETV / dev / mo
agents
Cloudflare · 6 devs
6.6
ETV / dev / mo
codex
OpenAI · 31 devs
6.5
ETV / dev / mo
turborepo
Vercel · 7 devs
5.6
ETV / dev / mo
openai-agents-python
OpenAI · 2 devs
5.3
ETV / dev / mo
Beyond the headline number, the same data through a different lens. How each org's monthly Performance breaks down between Growth, Maintenance, and Fixes, and how concentrated the workload is across the engineers who ship it.
Where the team's monthly Performance went, averaged over the last 90 days. A larger Growth slice means more time on net-new features; a larger Fixes slice means more time reworking past code.
Total Performance per connected organization, in ETV, stacked by work type. Bar lengths compare engineering output across orgs; colors show what kind of work fills it.
How many engineers fall in each avg-ETV-per-month bucket over the last 90 days. Reveals whether a few top contributors carry most of the work, or whether output is evenly spread.
The repositories and engineers with the most cumulative Engineering Throughput Value (ETV) since the benchmark began. A long-window view, complementing the rolling 7-day and 90-day leaderboards above.
Highest total Engineering Throughput Value (ETV) across the benchmarked repositories. Measured since Q2/2025.
Individual contributors ranked by Engineering Throughput Value (ETV) over the last 90 days. The Per-month column normalizes the 90-day window to a 30-day calendar month.
These charts show what we can measure across teams already using Navigara. We can do the same for your organization and help you bend the trend in the right direction.
Benchmark your org
