# DeepSeek-V3 vs GPT-6 Luna

> GPT-6 Luna is the stronger model overall, scoring 45.1 to 39.2 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v3-vs-gpt-6-luna
- Last updated: 2026-10-10
- Shared benchmarks: 13

## Summary

- They share 13 benchmarks with published results for both. DeepSeek-V3 scores higher in 0 categories and GPT-6 Luna in 8 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in coding, where GPT-6 Luna leads 54.7 to 41.9.
- GPT-6 Luna is cheaper at $0.10 / $0.50 per million input/output tokens, against $0.24 / $0.90 for DeepSeek-V3.
- GPT-6 Luna accepts more context: 1.05M tokens versus 164K.
- DeepSeek-V3 has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek-V3 | GPT-6 Luna |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 39.2 | 45.1 |
| Rank | 157 | 65 |
| Context | 164K | 1.05M |
| Input $/M | $0.24 | $0.10 |
| Output $/M | $0.90 | $0.50 |
| Weights | Open | Proprietary |

## Coding

- DeepSeek-V3: 41.9 (#99)
- GPT-6 Luna: 54.7 (#24)

| Benchmark | DeepSeek-V3 | GPT-6 Luna |
|---|---|---|
| LMArena Coding | 1368 | 1448 |
| DeepSWE | — | 66.6% |
| FrontierCode | — | 42.4% |
| Aider Polyglot | 55.1% | — |
| LMArena WebDev | — | 1583 |
| SciCode | 35.8% | — |
| WeirdML | 36.1% | — |
| BigCodeBench Instruct | 50% | — |
| LiveBench Coding | 70.9% | — |
| BigCodeBench Complete | 62.2% | — |
| HumanEval+ | 86.6% | — |
| MBPP+ | 73% | — |

## Agentic & Tool Use

- DeepSeek-V3: —
- GPT-6 Luna: —

| Benchmark | DeepSeek-V3 | GPT-6 Luna |
|---|---|---|
| METR Time Horizons | 49.6% | — |

## Reasoning

- DeepSeek-V3: 20.0 (#226)
- GPT-6 Luna: 31.7 (#68)

| Benchmark | DeepSeek-V3 | GPT-6 Luna |
|---|---|---|
| LMArena Hard Prompts | 1365 | 1415 |
| SimpleBench | 27.2% | — |
| Kagi LLM Benchmark | 52.3% | — |
| NYT Connections (extended) | — | 68.7% |
| CritPt | 0% | — |
| LiveBench Reasoning | 65.8% | — |
| DTBench | 64.8% | — |
| LiveBench Data Analysis | 60.9% | — |
| LMCA | 15.5% | — |
| BIG-Bench Hard | 87.5% | — |
| Epoch Capabilities Index | 135.95 | — |
| ForecastBench | 59.1 | — |
| HellaSwag | 88.9% | — |
| LiveBench | 66.9% | — |
| PIQA | 84.7% | — |
| WinoGrande | 85.2% | — |

## Math

- DeepSeek-V3: 30.4 (#208)
- GPT-6 Luna: 35.6 (#140)

| Benchmark | DeepSeek-V3 | GPT-6 Luna |
|---|---|---|
| LMArena Math | 1373 | 1396 |
| OTIS Mock AIME 2024-2025 | 37.8% | — |
| Omni-MATH | 40.3% | — |
| LiveBench Math | 73.5% | — |
| MATH Level 5 | 75.5% | — |
| FrontierMath (Feb 2025 set) | 1.7% | — |

## Knowledge

- DeepSeek-V3: 37.5 (#147)
- GPT-6 Luna: 40.1 (#110)

| Benchmark | DeepSeek-V3 | GPT-6 Luna |
|---|---|---|
| LMArena Expert | 1352 | 1458 |
| GPQA Diamond | 67.6% | — |
| MMLU-Pro | 72.3% | — |
| Confabulations | 26.1% | — |
| Vectara Hallucination Rate | 6.1% | — |
| GPQA (HELM) | 53.8% | — |
| ARC (AI2) Challenge | 95.3% | — |
| MMLU | 87.2% | — |
| TriviaQA | 82.9% | — |

## Multimodal

- DeepSeek-V3: —
- GPT-6 Luna: 42.0 (#27)

| Benchmark | DeepSeek-V3 | GPT-6 Luna |
|---|---|---|
| Furniture Assembly | — | 44.2% |

## Multilingual

- DeepSeek-V3: 48.8 (#138)
- GPT-6 Luna: 51.0 (#111)

| Benchmark | DeepSeek-V3 | GPT-6 Luna |
|---|---|---|
| LMArena Non-English | 1358 | 1390 |
| LMArena Chinese | 1390 | 1425 |
| LMArena Russian | 1372 | 1392 |
| LMArena Spanish | 1358 | 1416 |
| LMArena French | 1386 | — |
| LMArena German | 1374 | — |
| LMArena Japanese | 1333 | — |
| LMArena Korean | 1321 | — |

## Instruction Following

- DeepSeek-V3: 73.0 (#125)
- GPT-6 Luna: 74.7 (#85)

| Benchmark | DeepSeek-V3 | GPT-6 Luna |
|---|---|---|
| LMArena Instruction Following | 1345 | 1414 |
| LiveBench Instruction Following | 81.5% | — |
| IFEval | 83.2% | — |

## Long Context

- DeepSeek-V3: 34.0 (#248)
- GPT-6 Luna: 43.3 (#95)

| Benchmark | DeepSeek-V3 | GPT-6 Luna |
|---|---|---|
| LMArena Longer Query | 1353 | 1417 |
| Fiction.LiveBench | 50% | — |

## Writing & Preference

- DeepSeek-V3: 57.6 (#124)
- GPT-6 Luna: 58.4 (#115)

| Benchmark | DeepSeek-V3 | GPT-6 Luna |
|---|---|---|
| LMArena Text | 1375 | 1392 |
| LMArena Creative Writing | 1364 | 1357 |
| LMArena Multi-Turn | 1389 | 1400 |
| Short-Story Creative Writing | 77% | — |
| EQ-Bench Creative Writing | 1472 | — |
| WildBench | 83% | — |
| LiveBench Language | 49.1% | — |

## FAQ

### Is DeepSeek-V3 better than GPT-6 Luna?

GPT-6 Luna is the stronger model overall, scoring 45.1 to 39.2 on the Noometry Index.

### Which is cheaper, DeepSeek-V3 or GPT-6 Luna?

GPT-6 Luna is cheaper. It lists at $0.10 per million input tokens and $0.50 per million output tokens; DeepSeek-V3 lists at $0.24 and $0.90.

### Is DeepSeek-V3 or GPT-6 Luna better for coding?

GPT-6 Luna scores higher on coding benchmarks: 54.7 versus 41.9 in the Noometry coding category.

### Which has the bigger context window?

GPT-6 Luna does, with 1.05M tokens against 164K.

### How many benchmarks do DeepSeek-V3 and GPT-6 Luna share?

13 benchmarks have published results for both models. DeepSeek-V3 has 60 scored results on Noometry and GPT-6 Luna has 18.