# Image Classification on ImageNet 32x32 1.28M 1000 (test)

Source: [Image Classification on ImageNet 32x32 1.28M 1000 (test)](<https://www.sota2.com/research/sota/image-classification-on-imagenet-32x32-1-28m-1000-test>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-06-04T09:41:20.920Z

Evaluation of standard Image Classification performance (Top-1 and Top-5 accuracy) on the 32x32 resolution, 1000-class test split of the ImageNet dataset.

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

| Scope | Recorded value |
| --- | --- |
| Task | Image Classification |
| Dataset (including any stated split) | ImageNet 32x32 1.28M 1000 (test) |
| Metric | Top-1 Accuracy |
| Unit | PERCENT |
| Direction | Higher is better |
| Results loaded | 3 of 3 |
| Coverage | All results currently returned for this benchmark |

Evaluation settings may differ between results. The original papers and recorded configurations are needed to establish comparability. A shared metric name alone does not establish an identical protocol.

## Metrics

- [Top-1 Accuracy](<https://www.sota2.com/research/sota/image-classification-on-imagenet-32x32-1-28m-1000-test.md?metric=Top-1%20Accuracy>): Higher is better; unit: PERCENT.

- [Top-5 Accuracy](<https://www.sota2.com/research/sota/image-classification-on-imagenet-32x32-1-28m-1000-test.md?metric=Top-5%20Accuracy>): Higher is better; unit: PERCENT.

## Recorded results

| Method | Top-1 Accuracy | Result date | Report paper |
| --- | --- | --- | --- |
| Laborieux and Zenke \[2022\] | 63.5 | Not recorded | 6a2106a6c10484bac23f0303 |
| Høier et al. \[2023\] | 58.52 | Not recorded | 6a2106a6c10484bac23f0303 |
| Nest and Ernoult \[2024\] | 54 | Not recorded | 6a2106a6c10484bac23f0303 |

### Laborieux and Zenke \[2022\]

Top-1 Accuracy: 63.5. Result ID: 6a214833fbc373592c1d48d2.

[Reporting paper](<https://www.sota2.com/research/paper/6a2106a6c10484bac23f0303.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6d581e209131cea39506.md>)

Recorded evaluation configuration: {"Model":"Laborieux and Zenke \[2022\]"}. This record does not assert independent reproduction.

### Høier et al. \[2023\]

Top-1 Accuracy: 58.52. Result ID: 6a214833fbc373592c1d48d3.

[Reporting paper](<https://www.sota2.com/research/paper/6a2106a6c10484bac23f0303.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa6f9b1e209131cea4690c.md>)

Recorded evaluation configuration: {"Model":"Høier et al. \[2023\]"}. This record does not assert independent reproduction.

### Nest and Ernoult \[2024\]

Top-1 Accuracy: 54. Result ID: 6a214833fbc373592c1d48d4.

[Reporting paper](<https://www.sota2.com/research/paper/6a2106a6c10484bac23f0303.md>)

[Method origin paper](<https://www.sota2.com/research/paper/68fa74c21e209131cea63982.md>)

Recorded evaluation configuration: {"Model":"Nest and Ernoult \[2024\]"}. This record does not assert independent reproduction.

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