ImageNet-V2 Matched Frequency.

10K new test images following ImageNet collection process. Tests model generalization beyond the original test set.

Saturated benchmark

Benchmark near ceiling or stagnant — no meaningful SOTA movement in 2+ years

Paper ↗Submit a result ↵

§ 01 · Leaderboard

Best published scores.

2 results indexed across 1 metric. Shaded row marks current SOTA; ties broken by submission date.

Primary: top-1-accuracy · higher is better

top-1-accuracy· primary

2 rows

#	Model	Org	Submitted	Paper / code	top-1-accuracy
01	Swin Transformer V2 LargeOSS	Microsoft	Dec 2025	microsoft-research	84
02	ConvNeXt V2 HugeOSS	Meta	Dec 2025	meta-research	80.50

Fig 2 · Rows sorted by score within each metric. Shaded row marks SOTA. Dates reflect model or paper release where available, otherwise the date Codesota accessed the source.

§ 03 · Progress

1 steps
of state of the art.

Each row below marks a model that broke the previous record on top-1-accuracy. Intermediate submissions are kept in the leaderboard above; only SOTA-setting entries are re-listed here.

Higher scores win. Each subsequent entry improved upon the previous best.

SOTA line · top-1-accuracy

Dec 18, 2025Swin Transformer V2 LargeMicrosoft84

Fig 3 · SOTA-setting models only. 1 entries span Dec 2025 → Dec 2025.

§ 06 · Contribute

Have a score that beats
this table?

Submit a checkpoint and a reproduction script. We will run it, publish the score, and — if it takes the top — annotate the step on the progress chart with your name.

Submit a result ↵Read submission guide

What a submission needs

01A public checkpoint or API endpoint
02A reproduction script with frozen commit + seed
03Declared evaluation environment (Python, deps)
04One row per metric declared by this dataset
05A contact so we can follow up on discrepancies

ImageNet-V2 Matched Frequency.

Best published scores.

1 stepsof state of the art.

Neighbouring benchmarks.

Have a score that beatsthis table?

1 steps
of state of the art.

Have a score that beats
this table?