# DeepSeek V4 Pro vs o3

> DeepSeek V4 Pro is the stronger model overall, scoring 54.3 to 47.5 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v4-pro-vs-o3
- Last updated: 2026-10-10
- Shared benchmarks: 35

## Summary

- They share 35 benchmarks with published results for both. DeepSeek V4 Pro scores higher in 7 categories and o3 in 2 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek V4 Pro leads 56.5 to 32.0.
- The biggest single-benchmark swing is ARC-AGI-2: 61.3% for DeepSeek V4 Pro and 6.5% for o3.
- DeepSeek V4 Pro is cheaper at $0.66 / $1.98 per million input/output tokens, against $2 / $8 for o3.
- DeepSeek V4 Pro accepts more context: 1M tokens versus 200K.
- DeepSeek V4 Pro has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek V4 Pro | o3 |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 54.3 | 47.5 |
| Rank | 31 | 61 |
| Context | 1M | 200K |
| Input $/M | $0.66 | $2 |
| Output $/M | $1.98 | $8 |
| Weights | Open | Proprietary |

## Coding

- DeepSeek V4 Pro: 52.4 (#34)
- o3: 46.8 (#64)

| Benchmark | DeepSeek V4 Pro | o3 |
|---|---|---|
| SWE-bench Verified | 77.6% | 62.3% |
| WeirdML | 66.2% | 52.4% |
| LMArena Coding | 1470 | 1408 |
| ALE-Bench | 1,403 | 933.55 |
| FrontierCode | 28.6% | — |
| SWE-bench Verified (bash only) | — | 58.4% |
| Aider Polyglot | — | 81.3% |
| LMArena WebDev | 1582 | — |
| SciCode | 51% | — |
| GSO | — | 8.8% |
| CadEval | — | 74% |

## Agentic & Tool Use

- DeepSeek V4 Pro: 32.8 (#58)
- o3: 34.5 (#44)

| Benchmark | DeepSeek V4 Pro | o3 |
|---|---|---|
| APEX-Agents | 47.3% | — |
| Berkeley Function Calling Leaderboard | — | 63% |
| GDPval | — | 30.8% |
| DeepResearch Bench | — | 45.2% |
| OSWorld | — | 23% |
| LMArena Search | — | 1144 |
| METR Time Horizons | — | 65.4% |
| Vending-Bench 2 | 3,285 | — |

## Reasoning

- DeepSeek V4 Pro: 56.5 (#24)
- o3: 32.0 (#78)

| Benchmark | DeepSeek V4 Pro | o3 |
|---|---|---|
| ARC-AGI-2 | 61.3% | 6.5% |
| Kagi LLM Benchmark | 53.5% | 67.6% |
| ARC-AGI-1 | 90.5% | 60.8% |
| CritPt | 18% | 1.4% |
| Chess Puzzles | 47% | 38% |
| LMArena Hard Prompts | 1461 | 1402 |
| Mystery Game Puzzles | 43% | 29% |
| DTBench | 93.9% | 84.8% |
| LMCA | 45.5% | 39.7% |
| Epoch Capabilities Index | 155.31 | 146.86 |
| ForecastBench | 56.1 | 62.5 |
| SimpleBench | — | 53.1% |
| NYT Connections (extended) | 91.3% | — |
| EnigmaEval | — | 13.1% |
| Surface Evolver Bench | 40% | — |

## Math

- DeepSeek V4 Pro: 64.8 (#30)
- o3: 50.2 (#58)

| Benchmark | DeepSeek V4 Pro | o3 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 64.6% | 33.3% |
| OTIS Mock AIME 2024-2025 | 98.6% | 84.4% |
| LMArena Math | 1455 | 1426 |
| FrontierMath Tier 4 | 26.8% | — |
| MathArena Final-Answer Competitions | 76.6% | — |
| ProofBench | 50% | — |
| Omni-MATH | — | 71.4% |
| MATH Level 5 | — | 97.8% |
| FrontierMath (Feb 2025 set) | — | 18.7% |
| FrontierMath Tier 4 (v1) | — | 2.1% |

## Knowledge

- DeepSeek V4 Pro: 59.5 (#31)
- o3: 54.6 (#52)

| Benchmark | DeepSeek V4 Pro | o3 |
|---|---|---|
| GPQA Diamond | 91.7% | 81.8% |
| SimpleQA Verified | 52.9% | 49.4% |
| LMArena Expert | 1464 | 1402 |
| Humanity's Last Exam | — | 20.3% |
| MMLU-Pro | — | 85.9% |
| Confabulations | — | 14.4% |
| Vectara Hallucination Rate | 8.6% | — |
| GPQA (HELM) | — | 75.3% |

## Multimodal

- DeepSeek V4 Pro: —
- o3: 41.4 (#36)

| Benchmark | DeepSeek V4 Pro | o3 |
|---|---|---|
| LMArena Vision | — | 1214 |
| GeoBench | — | 74% |
| VPCT | — | 52% |

## Multilingual

- DeepSeek V4 Pro: 54.4 (#45)
- o3: 51.7 (#105)

| Benchmark | DeepSeek V4 Pro | o3 |
|---|---|---|
| LMArena Non-English | 1439 | 1401 |
| LMArena Chinese | 1486 | 1437 |
| LMArena French | 1472 | 1430 |
| LMArena German | 1458 | 1420 |
| LMArena Japanese | 1445 | 1403 |
| LMArena Korean | 1447 | 1370 |
| LMArena Russian | 1453 | 1406 |
| LMArena Spanish | 1458 | 1395 |

## Instruction Following

- DeepSeek V4 Pro: 76.1 (#47)
- o3: 72.8 (#127)

| Benchmark | DeepSeek V4 Pro | o3 |
|---|---|---|
| LMArena Instruction Following | 1448 | 1368 |
| IFEval | — | 86.9% |

## Long Context

- DeepSeek V4 Pro: 45.0 (#51)
- o3: 53.3 (#6)

| Benchmark | DeepSeek V4 Pro | o3 |
|---|---|---|
| LMArena Longer Query | 1458 | 1372 |
| Fiction.LiveBench | — | 88.9% |
| CL-bench | — | 17.8% |
| CL-bench Life | 13.5% | — |

## Writing & Preference

- DeepSeek V4 Pro: 65.5 (#46)
- o3: 63.5 (#64)

| Benchmark | DeepSeek V4 Pro | o3 |
|---|---|---|
| LMArena Text | 1451 | 1410 |
| LMArena Creative Writing | 1446 | 1359 |
| EQ-Bench Creative Writing | 1553 | 1676 |
| LMArena Multi-Turn | 1467 | 1405 |
| Short-Story Creative Writing | — | 83.9% |
| WildBench | — | 86.1% |
| EQ-Bench 4 | 1166 | — |

## FAQ

### Is DeepSeek V4 Pro better than o3?

DeepSeek V4 Pro is the stronger model overall, scoring 54.3 to 47.5 on the Noometry Index.

### Which is cheaper, DeepSeek V4 Pro or o3?

DeepSeek V4 Pro is cheaper. It lists at $0.66 per million input tokens and $1.98 per million output tokens; o3 lists at $2 and $8.

### Is DeepSeek V4 Pro or o3 better for coding?

DeepSeek V4 Pro scores higher on coding benchmarks: 52.4 versus 46.8 in the Noometry coding category.

### Which has the bigger context window?

DeepSeek V4 Pro does, with 1M tokens against 200K.

### How many benchmarks do DeepSeek V4 Pro and o3 share?

35 benchmarks have published results for both models. DeepSeek V4 Pro has 48 scored results on Noometry and o3 has 63.