# DeepSeek-V3 vs o3-pro

> o3-pro is the stronger model overall, scoring 42.7 to 39.2 on the Noometry Index. DeepSeek-V3 costs 86× less per token, which makes it the better buy when o3-pro's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/deepseek-v3-vs-o3-pro
- Last updated: 2026-10-10
- Shared benchmarks: 10

## Summary

- They share 10 benchmarks with published results for both. DeepSeek-V3 scores higher in 2 categories and o3-pro in 3 categories; 4 gaps are clear of the uncertainty.
- The widest gap is in long context, where o3-pro leads 72.1 to 34.0.
- The biggest single-benchmark swing is Fiction.LiveBench: 50% for DeepSeek-V3 and 97.2% for o3-pro.
- DeepSeek-V3 is cheaper at $0.24 / $0.90 per million input/output tokens, against $20 / $80 for o3-pro.
- o3-pro accepts more context: 200K tokens versus 164K.
- DeepSeek-V3 has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek-V3 | o3-pro |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 39.2 | 42.7 |
| Rank | 157 | 94 |
| Context | 164K | 200K |
| Input $/M | $0.24 | $20 |
| Output $/M | $0.90 | $80 |
| Weights | Open | Proprietary |

## Coding

- DeepSeek-V3: 41.9 (#99)
- o3-pro: 55.1 (#22)

| Benchmark | DeepSeek-V3 | o3-pro |
|---|---|---|
| Aider Polyglot | 55.1% | 84.9% |
| WeirdML | 36.1% | 58.2% |
| SciCode | 35.8% | — |
| BigCodeBench Instruct | 50% | — |
| LiveBench Coding | 70.9% | — |
| LMArena Coding | 1368 | — |
| BigCodeBench Complete | 62.2% | — |
| HumanEval+ | 86.6% | — |
| MBPP+ | 73% | — |

## Agentic & Tool Use

- DeepSeek-V3: —
- o3-pro: —

| Benchmark | DeepSeek-V3 | o3-pro |
|---|---|---|
| METR Time Horizons | 49.6% | — |

## Reasoning

- DeepSeek-V3: 20.0 (#226)
- o3-pro: 24.1 (#152)

| Benchmark | DeepSeek-V3 | o3-pro |
|---|---|---|
| Kagi LLM Benchmark | 52.3% | 72.1% |
| DTBench | 64.8% | 86.9% |
| LMCA | 15.5% | 38.5% |
| Epoch Capabilities Index | 135.95 | 147.43 |
| ARC-AGI-2 | — | 4.9% |
| SimpleBench | 27.2% | — |
| ARC-AGI-1 | — | 59.3% |
| CritPt | 0% | — |
| LiveBench Reasoning | 65.8% | — |
| LMArena Hard Prompts | 1365 | — |
| LiveBench Data Analysis | 60.9% | — |
| BIG-Bench Hard | 87.5% | — |
| ForecastBench | 59.1 | — |
| HellaSwag | 88.9% | — |
| LiveBench | 66.9% | — |
| PIQA | 84.7% | — |
| WinoGrande | 85.2% | — |

## Math

- DeepSeek-V3: 30.4 (#208)
- o3-pro: —

| Benchmark | DeepSeek-V3 | o3-pro |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 37.8% | — |
| Omni-MATH | 40.3% | — |
| LiveBench Math | 73.5% | — |
| LMArena Math | 1373 | — |
| MATH Level 5 | 75.5% | — |
| FrontierMath (Feb 2025 set) | 1.7% | — |

## Knowledge

- DeepSeek-V3: 37.5 (#147)
- o3-pro: 29.0 (#234)

| Benchmark | DeepSeek-V3 | o3-pro |
|---|---|---|
| Confabulations | 26.1% | 14.2% |
| Vectara Hallucination Rate | 6.1% | 23.3% |
| GPQA Diamond | 67.6% | — |
| MMLU-Pro | 72.3% | — |
| GPQA (HELM) | 53.8% | — |
| LMArena Expert | 1352 | — |
| ARC (AI2) Challenge | 95.3% | — |
| MMLU | 87.2% | — |
| TriviaQA | 82.9% | — |

## Multilingual

- DeepSeek-V3: 48.8 (#138)
- o3-pro: —

| Benchmark | DeepSeek-V3 | o3-pro |
|---|---|---|
| LMArena Non-English | 1358 | — |
| LMArena Chinese | 1390 | — |
| LMArena French | 1386 | — |
| LMArena German | 1374 | — |
| LMArena Japanese | 1333 | — |
| LMArena Korean | 1321 | — |
| LMArena Russian | 1372 | — |
| LMArena Spanish | 1358 | — |

## Instruction Following

- DeepSeek-V3: 73.0 (#125)
- o3-pro: —

| Benchmark | DeepSeek-V3 | o3-pro |
|---|---|---|
| LiveBench Instruction Following | 81.5% | — |
| IFEval | 83.2% | — |
| LMArena Instruction Following | 1345 | — |

## Long Context

- DeepSeek-V3: 34.0 (#248)
- o3-pro: 72.1 (#1)

| Benchmark | DeepSeek-V3 | o3-pro |
|---|---|---|
| Fiction.LiveBench | 50% | 97.2% |
| LMArena Longer Query | 1353 | — |

## Writing & Preference

- DeepSeek-V3: 57.6 (#124)
- o3-pro: 57.1 (#128)

| Benchmark | DeepSeek-V3 | o3-pro |
|---|---|---|
| Short-Story Creative Writing | 77% | 84.4% |
| LMArena Text | 1375 | — |
| LMArena Creative Writing | 1364 | — |
| EQ-Bench Creative Writing | 1472 | — |
| WildBench | 83% | — |
| LMArena Multi-Turn | 1389 | — |
| LiveBench Language | 49.1% | — |

## FAQ

### Is DeepSeek-V3 better than o3-pro?

o3-pro is the stronger model overall, scoring 42.7 to 39.2 on the Noometry Index. DeepSeek-V3 costs 86× less per token, which makes it the better buy when o3-pro's lead doesn't matter for your workload.

### Which is cheaper, DeepSeek-V3 or o3-pro?

DeepSeek-V3 is cheaper. It lists at $0.24 per million input tokens and $0.90 per million output tokens; o3-pro lists at $20 and $80.

### Is DeepSeek-V3 or o3-pro better for coding?

o3-pro scores higher on coding benchmarks: 55.1 versus 41.9 in the Noometry coding category.

### Which has the bigger context window?

o3-pro does, with 200K tokens against 164K.

### How many benchmarks do DeepSeek-V3 and o3-pro share?

10 benchmarks have published results for both models. DeepSeek-V3 has 60 scored results on Noometry and o3-pro has 12.