# GPT-5 Nano vs phi-3-medium 14B

> GPT-5 Nano is the stronger model overall, scoring 33.4 to 29.1 on the Noometry Index.

- Canonical page: https://noometry.com/compare/gpt-5-nano-vs-phi-3-medium-14b
- Last updated: 2026-10-10
- Shared benchmarks: 3

## Summary

- They share 3 benchmarks with published results for both. GPT-5 Nano scores higher in 2 categories and phi-3-medium 14B in 1 category; 3 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GPT-5 Nano leads 35.8 to 9.1.
- The biggest single-benchmark swing is MATH Level 5: 95.2% for GPT-5 Nano and 17.6% for phi-3-medium 14B.
- phi-3-medium 14B has downloadable open weights; the other is API-only.

## Snapshot

| | GPT-5 Nano | phi-3-medium 14B |
|---|---|---|
| Provider | OpenAI | Microsoft |
| Noometry Index | 33.4 | 29.1 |
| Rank | 234 | 306 |
| Context | 400K | — |
| Input $/M | $0.05 | — |
| Output $/M | $0.40 | — |
| Weights | Proprietary | Open |

## Coding

- GPT-5 Nano: 33.3 (#248)
- phi-3-medium 14B: 36.3 (#198)

| Benchmark | GPT-5 Nano | phi-3-medium 14B |
|---|---|---|
| SWE-bench Verified (bash only) | 34.8% | — |
| WeirdML | 38.1% | — |
| BigCodeBench Instruct | — | 37.6% |
| LMArena Coding | 1351 | — |
| BigCodeBench Complete | — | 48.7% |
| ALE-Bench | 718.67 | — |

## Agentic & Tool Use

- GPT-5 Nano: 25.6 (#99)
- phi-3-medium 14B: —

| Benchmark | GPT-5 Nano | phi-3-medium 14B |
|---|---|---|
| Terminal-Bench | 21.8% | — |
| Berkeley Function Calling Leaderboard | 51.5% | — |

## Reasoning

- GPT-5 Nano: 16.4 (#291)
- phi-3-medium 14B: —

| Benchmark | GPT-5 Nano | phi-3-medium 14B |
|---|---|---|
| Epoch Capabilities Index | 139.39 | 121.18 |
| ARC-AGI-2 | 2.6% | — |
| Kagi LLM Benchmark | 62.2% | — |
| ARC-AGI-1 | 20.7% | — |
| Chess Puzzles | 27% | — |
| LMArena Hard Prompts | 1329 | — |
| Mystery Game Puzzles | 9% | — |
| DTBench | 62.7% | — |
| LMCA | 7.9% | — |
| Adversarial NLI | — | 55.8% |
| BIG-Bench Hard | — | 81.4% |
| ForecastBench | 59.1 | — |
| HellaSwag | — | 82.4% |
| WinoGrande | — | 81.5% |

## Math

- GPT-5 Nano: 29.1 (#221)
- phi-3-medium 14B: 25.2 (#249)

| Benchmark | GPT-5 Nano | phi-3-medium 14B |
|---|---|---|
| MATH Level 5 | 95.2% | 17.6% |
| FrontierMath (Tiers 1-3) | 20% | — |
| FrontierMath Tier 4 | 2.4% | — |
| OTIS Mock AIME 2024-2025 | 81.1% | — |
| ProofBench | 12% | — |
| Omni-MATH | 54.6% | — |
| LMArena Math | 1318 | — |
| FrontierMath (Feb 2025 set) | 8.3% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |

## Knowledge

- GPT-5 Nano: 35.8 (#166)
- phi-3-medium 14B: 9.1 (#301)

| Benchmark | GPT-5 Nano | phi-3-medium 14B |
|---|---|---|
| GPQA Diamond | 69.4% | 27.6% |
| SimpleQA Verified | 11.7% | — |
| MMLU-Pro | 77.8% | — |
| Vectara Hallucination Rate | 10.5% | — |
| GPQA (HELM) | 67.9% | — |
| LMArena Expert | 1321 | — |
| ARC (AI2) Challenge | — | 91.6% |
| MMLU | — | 78% |
| OpenBookQA | — | 87.4% |
| TriviaQA | — | 73.9% |

## Multimodal

- GPT-5 Nano: 30.7 (#102)
- phi-3-medium 14B: —

| Benchmark | GPT-5 Nano | phi-3-medium 14B |
|---|---|---|
| LMArena Vision | 1159 | — |
| VPCT | 37.2% | — |

## Multilingual

- GPT-5 Nano: 45.5 (#167)
- phi-3-medium 14B: —

| Benchmark | GPT-5 Nano | phi-3-medium 14B |
|---|---|---|
| LMArena Non-English | 1313 | — |
| LMArena Chinese | 1355 | — |
| LMArena German | 1329 | — |
| LMArena Korean | 1269 | — |
| LMArena Russian | 1296 | — |
| LMArena Spanish | 1360 | — |

## Instruction Following

- GPT-5 Nano: 75.2 (#72)
- phi-3-medium 14B: —

| Benchmark | GPT-5 Nano | phi-3-medium 14B |
|---|---|---|
| IFEval | 93.2% | — |
| LMArena Instruction Following | 1306 | — |

## Long Context

- GPT-5 Nano: 31.3 (#275)
- phi-3-medium 14B: —

| Benchmark | GPT-5 Nano | phi-3-medium 14B |
|---|---|---|
| Fiction.LiveBench | 44.4% | — |
| LMArena Longer Query | 1313 | — |

## Writing & Preference

- GPT-5 Nano: 39.4 (#244)
- phi-3-medium 14B: —

| Benchmark | GPT-5 Nano | phi-3-medium 14B |
|---|---|---|
| LMArena Text | 1320 | — |
| LMArena Creative Writing | 1250 | — |
| EQ-Bench Creative Writing | 705 | — |
| WildBench | 80.6% | — |
| LMArena Multi-Turn | 1311 | — |

## FAQ

### Is GPT-5 Nano better than phi-3-medium 14B?

GPT-5 Nano is the stronger model overall, scoring 33.4 to 29.1 on the Noometry Index.

### Is GPT-5 Nano or phi-3-medium 14B better for coding?

phi-3-medium 14B scores higher on coding benchmarks: 36.3 versus 33.3 in the Noometry coding category.

### How many benchmarks do GPT-5 Nano and phi-3-medium 14B share?

3 benchmarks have published results for both models. GPT-5 Nano has 48 scored results on Noometry and phi-3-medium 14B has 13.