# GPT-5 NanoLow

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OpenAI

Canonical URL: https://benchize.com/models/gpt-5-nano-low
Last updated: Thu, 22 Oct 2026 07:32:33 GMT

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OpenAI

## Benchmarks

| Benchmark | Score | ± | Rank | Cost | Source |  |
| --- | --- | --- | --- | --- | --- | --- |
| [ARC-AGI-2](https://benchize.com/benchmarks/arc-prize%3Av2_Semi_Private.md) | 0% | — | 231 / 243 | 0.0033usd per task | [arc prize · v2](https://arcprize.org/media/data/leaderboard/v2.json) |  |
| ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `score` \| 0 \| score_fraction \| v2_Semi_Private \| Higher is better \| \| `cost_per_task` \| 0.0033 \| usd_per_task \| v2_Semi_Private \| Lower is better \| ### Configuration evaluationSplit v2_Semi_Private harness Not reported modelGroup gpt-5-nano-reasoning modelType CoT Reasoning effort low sourceModelVersion gpt-5-nano-2025-08-07-low thinkingEnabled true ### Source [Original source](https://arcprize.org/media/data/leaderboard/v2.json) Source arc prize Original model label GPT-5 Nano (Low) Source version v2 Observed 2026-10-22T05:20:04.306Z Evidence SHA-256 `4351eb696e78113b0459e9bb5f0258318b905efef34f473dcea51ce641b0d94d` Source locator `/evaluations/71` |  |  |  |  |  |  |
| [AIME 2025](https://benchize.com/benchmarks/aime-2025.md) | 47.22% | 95% CI 38.17–56.27% | 32 / 36 | 0.001usd per problem | [matharena · aime--aime_2025](https://matharena.ai/competition_tables/aime--aime_2025) |  |
| ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `accuracy` \| 47.22 \| percent \| competition \| Higher is better \| \| `cost_per_problem` \| 0.001 \| usd_per_problem \| competition \| Lower is better \| ### Configuration competition aime--aime_2025 predicted false Reasoning effort low sourceModelName GPT-5-nano (low) sourceModelVersion openai/gpt-5-nano-low thinkingEnabled true ### Reported statistics Uncertainty 95% confidence interval: 38.17–56.27% confidenceInterval95 9.05 problems 30 ### Source [Original source](https://matharena.ai/competition_tables/aime--aime_2025) Source matharena Original model label GPT-5-nano (low) Source version aime--aime_2025 Observed 2026-10-22T05:30:11.892Z Evidence SHA-256 `fab0abcecc4032852ef2cbd2a84d34ffc42202be358b2994bfaba44ae7a0cd9a` Source locator `/table/rows/53` |  |  |  |  |  |  |
| [ARC-AGI-1](https://benchize.com/benchmarks/arc-prize%3Av1_Semi_Private.md) | 4.04% | — | 240 / 245 | 0.0033usd per task | [arc prize · v1](https://arcprize.org/media/data/leaderboard/v1.json) |  |
| ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `score` \| 0.0404 \| score_fraction \| v1_Semi_Private \| Higher is better \| \| `cost_per_task` \| 0.0033 \| usd_per_task \| v1_Semi_Private \| Lower is better \| ### Configuration evaluationSplit v1_Semi_Private harness Not reported modelGroup gpt-5-nano-reasoning modelType CoT Reasoning effort low sourceModelVersion gpt-5-nano-2025-08-07-low thinkingEnabled true ### Source [Original source](https://arcprize.org/media/data/leaderboard/v1.json) Source arc prize Original model label GPT-5 Nano (Low) Source version v1 Observed 2026-10-22T05:20:04.066Z Evidence SHA-256 `2bf68d22dafba37047d07ad833ebc0e8199c9aa2f9eeaed50c75c1b704462836` Source locator `/evaluations/69` |  |  |  |  |  |  |

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Cite as: GPT-5 NanoLow — Benchize, https://benchize.com/models/gpt-5-nano-low (retrieved 2026-10-22)