# DeepSeek-V3.1 vs phi-3-medium 14B

> DeepSeek-V3.1 is the stronger model overall, scoring 42.8 to 29.7 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v3-1-vs-phi-3-medium-14b
- Last updated: 2026-10-11
- Shared benchmarks: 1

## Summary

- They share 1 benchmark with published results for both. DeepSeek-V3.1 scores higher in 3 categories and phi-3-medium 14B in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where DeepSeek-V3.1 leads 43.7 to 9.1.

## Snapshot

| | DeepSeek-V3.1 | phi-3-medium 14B |
|---|---|---|
| Provider | DeepSeek | Microsoft |
| Noometry Index | 42.8 | 29.7 |
| Rank | 108 | 306 |
| Context | 164K | — |
| Input $/M | $0.25 | — |
| Output $/M | $0.95 | — |
| Weights | Open | Open |

## Coding

- DeepSeek-V3.1: 40.3 (#144)
- phi-3-medium 14B: 36.8 (#201)

| Benchmark | DeepSeek-V3.1 | phi-3-medium 14B |
|---|---|---|
| WeirdML | 38.4% | — |
| BigCodeBench Instruct | — | 37.6% |
| LMArena Coding | 1417 | — |
| BigCodeBench Complete | — | 48.7% |

## Reasoning

- DeepSeek-V3.1: 27.9 (#110)
- phi-3-medium 14B: —

| Benchmark | DeepSeek-V3.1 | phi-3-medium 14B |
|---|---|---|
| Epoch Capabilities Index | 139.92 | 121.23 |
| SimpleBench | 40% | — |
| Kagi LLM Benchmark | 53.2% | — |
| LMArena Hard Prompts | 1417 | — |
| DTBench | 82.7% | — |
| LMCA | 24.3% | — |
| Adversarial NLI | — | 55.8% |
| BIG-Bench Hard | — | 81.4% |
| ForecastBench | 58 | — |
| HellaSwag | — | 82.4% |
| WinoGrande | — | 81.5% |

## Math

- DeepSeek-V3.1: 38.9 (#122)
- phi-3-medium 14B: 27.3 (#250)

| Benchmark | DeepSeek-V3.1 | phi-3-medium 14B |
|---|---|---|
| LMArena Math | 1420 | — |
| MATH Level 5 | — | 17.6% |

## Knowledge

- DeepSeek-V3.1: 43.7 (#90)
- phi-3-medium 14B: 9.1 (#306)

| Benchmark | DeepSeek-V3.1 | phi-3-medium 14B |
|---|---|---|
| GPQA Diamond | — | 27.6% |
| Vectara Hallucination Rate | 5.5% | — |
| LMArena Expert | 1405 | — |
| ARC (AI2) Challenge | — | 91.6% |
| MMLU | — | 78% |
| OpenBookQA | — | 87.4% |
| TriviaQA | — | 73.9% |

## Multilingual

- DeepSeek-V3.1: 51.6 (#106)
- phi-3-medium 14B: —

| Benchmark | DeepSeek-V3.1 | phi-3-medium 14B |
|---|---|---|
| LMArena Non-English | 1400 | — |
| LMArena Chinese | 1469 | — |
| LMArena French | 1447 | — |
| LMArena German | 1411 | — |
| LMArena Japanese | 1378 | — |
| LMArena Korean | 1337 | — |
| LMArena Russian | 1405 | — |
| LMArena Spanish | 1431 | — |

## Instruction Following

- DeepSeek-V3.1: 73.9 (#110)
- phi-3-medium 14B: —

| Benchmark | DeepSeek-V3.1 | phi-3-medium 14B |
|---|---|---|
| LMArena Instruction Following | 1400 | — |

## Long Context

- DeepSeek-V3.1: 36.3 (#232)
- phi-3-medium 14B: —

| Benchmark | DeepSeek-V3.1 | phi-3-medium 14B |
|---|---|---|
| Fiction.LiveBench | 52.8% | — |
| LMArena Longer Query | 1422 | — |

## Writing & Preference

- DeepSeek-V3.1: 60.3 (#98)
- phi-3-medium 14B: —

| Benchmark | DeepSeek-V3.1 | phi-3-medium 14B |
|---|---|---|
| LMArena Text | 1420 | — |
| LMArena Creative Writing | 1401 | — |
| EQ-Bench Creative Writing | 1436 | — |
| LMArena Multi-Turn | 1408 | — |

## FAQ

### Is DeepSeek-V3.1 better than phi-3-medium 14B?

DeepSeek-V3.1 is the stronger model overall, scoring 42.8 to 29.7 on the Noometry Index.

### Is DeepSeek-V3.1 or phi-3-medium 14B better for coding?

DeepSeek-V3.1 scores higher on coding benchmarks: 40.3 versus 36.8 in the Noometry coding category.

### How many benchmarks do DeepSeek-V3.1 and phi-3-medium 14B share?

1 benchmark has published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and phi-3-medium 14B has 13.