GPT-5.4 Nano
GPT-5.4 Nano (OpenAI) was released on Mar 17, 2026. In the Epoch AI capability ranking (ECI), it ranks #82 out of 267 models, with 146.12. On Arena, which measures human preference in blind comparisons, it has 1,404 ELO points (#169). On LiveBench, the overall average is 69.6, #49 out of 58 scored models. Against models of the same generation, its best result is on Chess puzzles: 45.0%, #11 of 37, tied with 1 others.
Where GPT-5.4 Nano stands out and where it falls behind, by the numbers
GPT-5.4 Nano has published results on 18 tests compiled by Epoch AI. The yardstick here is its generation: its position among the models released between Jun 20, 2025 and Jun 15, 2026 that took the same test. Against the whole archive, which includes 2023 models, a recent release lands near the top of almost everything, and that says nothing.
Where it stands out
Tests where it sits in the top third of its own generation.
Where it falls behind
Tests where it sits in the bottom half of its own generation.
See all 18 tests, one by one
| Test | Score | In its generation | Overall | Test record |
|---|---|---|---|---|
| GPQA Diamond | 78.5% | #50 / 64 | #87 / 173 | 96.4% Gemini 4 Argon |
| AIME 2024 and 2025 (OTIS) | 87.8% | #32 / 64 | #65 / 168 | 100.0% GPT-5.5 |
| Dtbench | 80.3% | #37 / 59 (tied with 1) | #70 / 148 | 98.9% Claude Opus 5.5 |
| Lmca | 36.86 | #29 / 56 | #61 / 121 | 68.23 Claude Opus 5.5 |
| CritPt | 9.3% | #16 / 49 | #52 / 112 | 32.3% GPT-5.6 Sol |
| WeirdML | 49.2% | #28 / 53 | #48 / 112 | 93.6% GPT-6 Astra |
| SciCode | 47.2% | #18 / 45 | #55 / 104 | 66.9% Claude Opus 5.5 |
| Frontiermath Tiers 1 3 V2 | 44.9% | #22 / 39 (tied with 1) | #55 / 86 | 93.7% GPT-6 Astra |
| ARC-AGI 2 | 5.7% | #25 / 35 | #55 / 83 | 95.0% GPT-6 Astra |
| ALE-Bench | 1,005 | #19 / 48 | #40 / 82 | 2,951 GPT-6 Astra |
| ARC-AGI | 51.5% | #28 / 35 | #57 / 81 | 98.5% Claude Fable 5 |
| SimpleQA Verified | 11.7% | #36 / 38 (tied with 1) | #77 / 81 | 76.0% Gemini 4 Argon |
| Chess puzzles | 45.0% | #11 / 37 (tied with 1) | #26 / 80 | 76.0% GPT-6 Astra |
| Game puzzles | 9.0% | #31 / 37 (tied with 2) | #64 / 77 | 84.0% GPT-6 Astra |
| ProofBench | 5.0% | #30 / 33 | #69 / 74 | 100.0% Claude Fable 5.1 |
| Frontiermath Tier 4 V2 | 12.2% | #20 / 29 (tied with 2) | #53 / 67 | 100.0% GPT-6.1 Sol |
| FrontierMath | 25.9% | #23 / 40 | #23 / 65 | 51.7% GPT-5.5 |
| FrontierMath tier 4 | 6.3% | #19 / 39 (tied with 1) | #19 / 48 | 39.6% GPT-5.5 Pro |
For each test, the model's best effort level counts, as in the ranking. Source of the scores: Epoch AI, under CC BY 4.0.
What to compare GPT-5.4 Nano with
The models from other labs closest in capability and released in the same period, at most two per lab. Click any of them to see its page.
| Model | Lab | ECI | ELO | LiveBench | Release |
|---|---|---|---|---|---|
| Qwen 3.5 Plus (hosted 397B-A17B) | Alibaba | 146.32 | n/a | n/a | Feb 16, 2026 |
| Qwen3.5-122B-A10B | Alibaba | 146.26 | 1,466 | n/a | Feb 24, 2026 |
| GPT-5.4 Nano | OpenAI | 146.12 | 1,404 | 69.6 | Mar 17, 2026 |
| DeepSeek-V3.2 | DeepSeek | 146.11 | 1,455 | n/a | Dec 1, 2025 |
| DeepSeek-V4-Flash | DeepSeek | 146.05 | 1,468 | 65.5 | Apr 24, 2026 |
| Kimi K2 Thinking | Moonshot | 145.96 | n/a | n/a | Nov 6, 2025 |
| MiniMax-M2.7 | MiniMax | 145.88 | 1,454 | n/a | Mar 18, 2026 |
GPT-5.4 Nano or DeepSeek-V3.2?
DeepSeek-V3.2 is the model from another lab closest to GPT-5.4 Nano in capability. Across the 9 tests both took, this is the score:
| Test | GPT-5.4 Nano | DeepSeek-V3.2 |
|---|---|---|
| FrontierMath tier 4 | 6.3% | 2.1% |
| ProofBench | 5.0% | 8.0% |
| ARC-AGI 2 | 5.7% | 4.0% |
| Lmca | 36.86 | 28.82 |
| FrontierMath | 25.9% | 22.1% |
| ARC-AGI | 51.5% | 57.0% |
| Dtbench | 80.3% | 85.6% |
| GPQA Diamond | 78.5% | 83.4% |
| AIME 2024 and 2025 (OTIS) | 87.8% | 87.8% |
Unweighted score: each test counts one point, whether math or coding. The dot marks who did better on each row.
What GPT-5.4 Nano costs to deliver each task
Price per token is what is on the price sheet; cost per task is what lands on the invoice, because it depends on how many tokens the model spends. Each point is an effort level, published by whoever ran the test and compiled by Epoch AI. The further up and to the left, the more score per dollar.
ARC-AGI 2
The score scale does not start at zero.
ARC-AGI
The score scale does not start at zero.
Other models from OpenAI
The models from the same lab closest in time, newest first.
| Model | Release | ECI | ELO | LiveBench | Access |
|---|---|---|---|---|---|
| GPT-5.5 Instant | May 5, 2026 | 142.45 | 1,456 | n/a | API access |
| GPT-5.5 Pro | Apr 23, 2026 | 161.97 | n/a | n/a | API access |
| GPT-5.5 | Apr 23, 2026 | 158.95 | 1,533 | 80.2 | API access |
| GPT-5.4 Mini | Mar 17, 2026 | 148.77 | 1,446 | 66.4 | API access |
| GPT-5.4 Nano | Mar 17, 2026 | 146.12 | 1,404 | 69.6 | API access |
| GPT-5.4 Pro | Mar 5, 2026 | 159.00 | n/a | n/a | API access |
| GPT-5.4 | Mar 5, 2026 | 156.72 | 1,519 | 78.0 | API access |
| GPT-5.3 Codex | Feb 5, 2026 | 156.76 | n/a | n/a | API access |
| GPT-5.2 Pro | Dec 11, 2025 | 156.03 | n/a | n/a | API access |
Have you used GPT-5.4 Nano? Rate it
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What people ask about GPT-5.4 Nano
Where does GPT-5.4 Nano rank among AI models?
In the ROO3 AI Benchmark, ordered by the Epoch AI ECI, GPT-5.4 Nano ranks #82 out of 267 models, with an ECI of 146.12. The ECI is a composite index that combines several hard benchmarks into a single scale. The position changes when a new model comes out, and the page is refreshed six times a day.
Is GPT-5.4 Nano better than DeepSeek-V3.2?
Across the 9 tests both models took and Epoch AI compiled, GPT-5.4 Nano comes out ahead on 4, behind on 5 and tied on 0. It is a test-by-test count with no weighting: a win in math counts the same as a win in coding. To choose between the two, look at the tests that resemble your own use.
What is GPT-5.4 Nano best at?
Against models of the same generation (released up to 9 months before and up to 3 months after it), the best relative results of GPT-5.4 Nano are: Chess puzzles (#11 of 37); CritPt (#16 of 49). The yardstick is its position among the models of that period that took the same test.
Where do the numbers on this page come from?
From the same three sources as the ranking, all openly licensed: Epoch AI (ECI and individual tests, CC BY 4.0), Arena (human-preference ELO, CC BY 4.0) and LiveBench (overall average, CC BY-SA 4.0). ROO3 does not measure any model. When the page shows a figure published by the maker itself, it appears in the written analysis, labeled as the maker's, and never enters the ranking.
Where each number comes from
Epoch AI, "AI Benchmarking Hub". Published at epoch.ai. Data under the CC BY 4.0 licence, reordered by roo3.co.
The Arena (LMArena) leaderboard, from the public lmarena-ai/leaderboard-dataset on Hugging Face, under the CC BY 4.0 licence. We are not affiliated with the Arena.
LiveBench, by the LiveBench team, published at livebench.ai under the CC BY-SA 4.0 license. The overall average is recomputed by roo3.co with the same formula as the website (average of the categories), and those numbers stay under CC BY-SA 4.0. We are not affiliated with LiveBench.
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