Independent benchmarks, built by the community

AI benchmarks.
From real work.

nerfd compares AI coding models using results shared by the people who use them. See which models work well, where they fall short, and how they change.

Explore the community rankings
INSTALL NERFDFREE & OPEN SOURCE

Start contributing.

Connect your coding tools with one command.
nerfd records the results as you work.

curl -fsSL https://nerfd.org/install.sh | sh
Inspect script ↗

Shares session measurements. Your prompts and code stay local.

No account · Node.js 22.13+ · No lab funding

How it works

Install nerfd. Keep working.

01 / CONNECT

Install once.

nerfd connects to your coding tools.
You work as usual.

Get nerfd ↗
02 / MEASURE LOCALLY

Measure the session.

Results, corrections and cost,
measured on your machine.

HooksSession history
03 / CONTRIBUTE

Compare with others.

Share session measurements
to help compare models.

View the rankings ↗

Your prompts and code stay on your machine. Sharing is optional.

Explore the measurements

How much help did it need?

Corrections, repeated requests and pushback reveal how much direction a model needed. nerfd reduces these to counts on your machine and compares rates per user turn, so a long session is not automatically worse.

Also records frustration markers, clarifying questions and abandonment signals. These are heuristic indicators; phrase detection is English-only.

Available signals vary by tool. Shared records use weekly rotating pseudonymous IDs. Privacy · Open method ↗

Works where
you already work
Claude CodeCodexOpenCodeGemini CLIQwen CodeAll integrations ↗

01 / What you can learn

See how models perform
on everyday tasks.

Lab tests are useful, but they cannot tell you everything about using a model. nerfd adds results from real coding work, including successful sessions, errors and repeated corrections.

01.1 / COMPARE REAL TASKS

Compare models by task.

Compare ten kinds of work, from debugging to design. Each result shows how many sessions it is based on.

Compare tasks ↗
01.2 / TRACK CHANGES

Track performance over time.

See whether a model’s results improve or decline. Compare its weekly scores with its earlier results and other models.

View model histories ↗
EXAMPLE SHIFT
01.3 / CHECK THE RESULTS

See what worked.

See how people rated the work, how much of the code they kept, and how often they had to correct the model.

View session results ↗
75%
63 / 84SUCCESSFUL SESSIONS
ILLUSTRATIVE DATA

02 / The community benchmark

The community’s results.

Full rankings ↗
Weekly resultsIllustrative data

Model scores by week

Illustrative weekly model scoresExample models A, B and C change over eight weeks. Scores are illustrative, not live rankings.100755025W01W03W05W08
Model AModel BModel C

Example scores over eight weeks. Visit a model page for its recorded results.

The community scorecard

Example

CONTRIBUTED SESSIONS · LAST 4 WEEKS

01Claude Opus 4.628 sessions88
02GPT-5.424 sessions81
03Kimi K2.512 sessions74
Results vary by task.
OVERALL SCORE · LAST 4 WEEKSLoading public record…

Loading rankings…

A public rank requires at least 10 sessions. Scores combine human ratings, retained code and sessions without errors or interruptions. Tasks and users differ, so compare similar work.

03 / Your personal report

Your own results,
in one report.

You also get a report of your own sessions: which models worked best, what your subscriptions provided, and where you spent time correcting mistakes.

Import your existing session history to get started. Your report works whether or not you share results with the community.

nerfd report
nerfd / PERSONAL REPORTEXAMPLE · 4 WEEKS

Your monthly summary

84sessions
62.4hours of work
63successful
Claude Max 5× · API-equivalent value3.4×
GPT-5.4 · code survival88%
Claude Opus 4.6 · your score88 / 100

Saved as an HTML file on your machine.
API-equivalent value is an estimate, not cash saved.

04 / How it works

From your coding tools
to the public rankings.

nerfd measures sessions on your machine. If sharing is on, it sends those measurements to the public dataset. The same published scoring method applies to every model.

01 →

Install once.

The installer connects to supported tools it finds. Start with existing history using nerfd backfill --since 90d.

02 →

Work as usual.

Session hooks collect tokens, timing and errors. Conversation signals become counts locally. nerfd check measures code survival later.

03 →

Share session results.

Sharing adds your session measurements to the rankings. Prompts, code, file paths and project names stay on your machine.

04 ↗

Compare the results.

Browse community rankings and model histories. Run nerfd report to see your own results and costs.

Your work stays private.

Prompts, code and project details stay local. Shared metrics use weekly rotating pseudonymous IDs. Read the privacy details ↗

A method you can inspect.

Read the source code, check the scoring method or download the dataset. See the method ↗

Independent of model labs.

nerfd accepts no funding from model labs. Anyone can review the code and data. Explore the data ↗

05 / Help build the benchmark

Add your results
to the benchmark.

Help others compare models using results from your work. Successful sessions and failed attempts are both useful.

Free and open source. No account. Node.js 22.13 or newer.
Sharing is your choice; your personal report works either way.

Inspect the install script ↗
TERMINAL~/ your machine
curl -fsSL https://nerfd.org/install.sh | sh
$ nerfd backfill --since 90d
$ nerfd report
Sharing is on. Session measurements contribute to the rankings. Turn it off with nerfd share off.
Copy the command, then run it in your terminal.

Common questions

Before you install.

How is my work kept private?

Sharing sends session measurements, including the model, tool, plan, task category, timing and results. It does not send prompts, code, file paths or project names. Shared records use an ID that changes weekly. They are pseudonymous, not guaranteed anonymous; combinations of metadata may still identify someone. Inspect the full privacy statement.

How is this different from a lab benchmark?

Lab benchmarks test models under controlled conditions. nerfd compares results from everyday coding sessions. This shows how models perform in practice, but tasks, tools and users vary. Check the task filters and session counts when comparing models.

Does it work with local models?

Yes, through supported tools such as OpenCode and Goose. Different hosts and model variants are tracked separately, including quantised versions run locally.

How do I remove it?

Run nerfd share off to stop sharing and nerfd init --remove to remove the hooks. Your local report remains a file you can keep.

Does it include good and bad results?

Yes. With sharing on, supported completed sessions are included whether they went well or badly. Errors, corrections and interruptions are recorded too. Automated sessions are excluded from quality rankings by default.

How can I help?

Contribute session metrics, report an issue, improve an adapter or review the scoring method. Start with the contribution guide.