# GPT-5 Nano vs o3

> o3 is the stronger model overall, scoring 47.4 to 33.4 on the Noometry Index. GPT-5 Nano costs 25× less per token, which makes it the better buy when o3's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gpt-5-nano-vs-o3
- Last updated: 2026-10-10
- Shared benchmarks: 44

## Summary

- They share 44 benchmarks with published results for both. GPT-5 Nano scores higher in 1 category and o3 in 9 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where o3 leads 63.7 to 39.4.
- The biggest single-benchmark swing is Fiction.LiveBench: 44.4% for GPT-5 Nano and 88.9% for o3.
- GPT-5 Nano is cheaper at $0.05 / $0.40 per million input/output tokens, against $2 / $8 for o3.
- GPT-5 Nano accepts more context: 400K tokens versus 200K.

## Snapshot

| | GPT-5 Nano | o3 |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 33.4 | 47.4 |
| Rank | 234 | 53 |
| Context | 400K | 200K |
| Input $/M | $0.05 | $2 |
| Output $/M | $0.40 | $8 |
| Weights | Proprietary | Proprietary |

## Coding

- GPT-5 Nano: 33.3 (#248)
- o3: 47.3 (#57)

| Benchmark | GPT-5 Nano | o3 |
|---|---|---|
| SWE-bench Verified (bash only) | 34.8% | 58.4% |
| WeirdML | 38.1% | 52.4% |
| LMArena Coding | 1351 | 1408 |
| ALE-Bench | 718.67 | 933.55 |
| SWE-bench Verified | — | 62.3% |
| Aider Polyglot | — | 81.3% |
| GSO | — | 8.8% |
| CadEval | — | 74% |

## Agentic & Tool Use

- GPT-5 Nano: 25.6 (#99)
- o3: 34.3 (#42)

| Benchmark | GPT-5 Nano | o3 |
|---|---|---|
| Berkeley Function Calling Leaderboard | 51.5% | 63% |
| Terminal-Bench | 21.8% | — |
| GDPval | — | 30.8% |
| DeepResearch Bench | — | 45.2% |
| OSWorld | — | 23% |
| LMArena Search | — | 1144 |
| METR Time Horizons | — | 65.4% |

## Reasoning

- GPT-5 Nano: 16.4 (#291)
- o3: 32.1 (#66)

| Benchmark | GPT-5 Nano | o3 |
|---|---|---|
| ARC-AGI-2 | 2.6% | 6.5% |
| Kagi LLM Benchmark | 62.2% | 67.6% |
| ARC-AGI-1 | 20.7% | 60.8% |
| Chess Puzzles | 27% | 38% |
| LMArena Hard Prompts | 1329 | 1402 |
| Mystery Game Puzzles | 9% | 29% |
| DTBench | 62.7% | 84.8% |
| LMCA | 7.9% | 39.7% |
| Epoch Capabilities Index | 139.39 | 146.88 |
| ForecastBench | 59.1 | 62.5 |
| SimpleBench | — | 53.1% |
| CritPt | — | 1.4% |
| EnigmaEval | — | 13.1% |

## Math

- GPT-5 Nano: 29.1 (#221)
- o3: 48.9 (#49)

| Benchmark | GPT-5 Nano | o3 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 20% | 33.3% |
| OTIS Mock AIME 2024-2025 | 81.1% | 84.4% |
| Omni-MATH | 54.6% | 71.4% |
| LMArena Math | 1318 | 1426 |
| MATH Level 5 | 95.2% | 97.8% |
| FrontierMath (Feb 2025 set) | 8.3% | 18.7% |
| FrontierMath Tier 4 (v1) | 2.1% | 2.1% |
| FrontierMath Tier 4 | 2.4% | — |
| ProofBench | 12% | — |

## Knowledge

- GPT-5 Nano: 35.8 (#166)
- o3: 54.5 (#47)

| Benchmark | GPT-5 Nano | o3 |
|---|---|---|
| GPQA Diamond | 69.4% | 81.8% |
| SimpleQA Verified | 11.7% | 49.4% |
| MMLU-Pro | 77.8% | 85.9% |
| GPQA (HELM) | 67.9% | 75.3% |
| LMArena Expert | 1321 | 1403 |
| Humanity's Last Exam | — | 20.3% |
| Confabulations | — | 14.4% |
| Vectara Hallucination Rate | 10.5% | — |

## Multimodal

- GPT-5 Nano: 30.7 (#102)
- o3: 40.7 (#35)

| Benchmark | GPT-5 Nano | o3 |
|---|---|---|
| LMArena Vision | 1159 | 1214 |
| VPCT | 37.2% | 52% |
| GeoBench | — | 74% |

## Multilingual

- GPT-5 Nano: 45.5 (#167)
- o3: 51.9 (#99)

| Benchmark | GPT-5 Nano | o3 |
|---|---|---|
| LMArena Non-English | 1313 | 1402 |
| LMArena Chinese | 1355 | 1438 |
| LMArena German | 1329 | 1420 |
| LMArena Korean | 1269 | 1371 |
| LMArena Russian | 1296 | 1407 |
| LMArena Spanish | 1360 | 1395 |
| LMArena French | — | 1430 |
| LMArena Japanese | — | 1404 |

## Instruction Following

- GPT-5 Nano: 75.2 (#72)
- o3: 73.0 (#122)

| Benchmark | GPT-5 Nano | o3 |
|---|---|---|
| IFEval | 93.2% | 86.9% |
| LMArena Instruction Following | 1306 | 1368 |

## Long Context

- GPT-5 Nano: 31.3 (#275)
- o3: 53.2 (#6)

| Benchmark | GPT-5 Nano | o3 |
|---|---|---|
| Fiction.LiveBench | 44.4% | 88.9% |
| LMArena Longer Query | 1313 | 1372 |
| CL-bench | — | 17.8% |

## Writing & Preference

- GPT-5 Nano: 39.4 (#244)
- o3: 63.7 (#62)

| Benchmark | GPT-5 Nano | o3 |
|---|---|---|
| LMArena Text | 1320 | 1410 |
| LMArena Creative Writing | 1250 | 1359 |
| EQ-Bench Creative Writing | 705 | 1676 |
| WildBench | 80.6% | 86.1% |
| LMArena Multi-Turn | 1311 | 1405 |
| Short-Story Creative Writing | — | 83.9% |

## FAQ

### Is GPT-5 Nano better than o3?

o3 is the stronger model overall, scoring 47.4 to 33.4 on the Noometry Index. GPT-5 Nano costs 25× less per token, which makes it the better buy when o3's lead doesn't matter for your workload.

### Which is cheaper, GPT-5 Nano or o3?

GPT-5 Nano is cheaper. It lists at $0.05 per million input tokens and $0.40 per million output tokens; o3 lists at $2 and $8.

### Is GPT-5 Nano or o3 better for coding?

o3 scores higher on coding benchmarks: 47.3 versus 33.3 in the Noometry coding category.

### Which has the bigger context window?

GPT-5 Nano does, with 400K tokens against 200K.

### How many benchmarks do GPT-5 Nano and o3 share?

44 benchmarks have published results for both models. GPT-5 Nano has 48 scored results on Noometry and o3 has 63.