# DeepSeek-V3 vs GPT-6 Astra

> GPT-6 Astra is the stronger model overall, scoring 70.3 to 39.2 on the Noometry Index. DeepSeek-V3 costs 49× less per token, which makes it the better buy when GPT-6 Astra's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/deepseek-v3-vs-gpt-6-astra
- Last updated: 2026-10-10
- Shared benchmarks: 24

## Summary

- They share 24 benchmarks with published results for both. DeepSeek-V3 scores higher in 0 categories and GPT-6 Astra in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-6 Astra leads 85.1 to 20.0.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 37.8% for DeepSeek-V3 and 100% for GPT-6 Astra.
- DeepSeek-V3 is cheaper at $0.24 / $0.90 per million input/output tokens, against $10 / $50 for GPT-6 Astra.
- GPT-6 Astra accepts more context: 1.05M tokens versus 164K.
- DeepSeek-V3 has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek-V3 | GPT-6 Astra |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 39.2 | 70.3 |
| Rank | 157 | 1 |
| Context | 164K | 1.05M |
| Input $/M | $0.24 | $10 |
| Output $/M | $0.90 | $50 |
| Weights | Open | Proprietary |

## Coding

- DeepSeek-V3: 41.9 (#99)
- GPT-6 Astra: 70.5 (#3)

| Benchmark | DeepSeek-V3 | GPT-6 Astra |
|---|---|---|
| SciCode | 35.8% | 56.5% |
| WeirdML | 36.1% | 93.6% |
| LMArena Coding | 1368 | 1488 |
| DeepSWE | — | 74.1% |
| FrontierCode | — | 53.3% |
| Aider Polyglot | 55.1% | — |
| LMArena WebDev | — | 1792 |
| FrontierSWE | — | 65.5% |
| BigCodeBench Instruct | 50% | — |
| LiveBench Coding | 70.9% | — |
| MirrorCode | — | 46.7% |
| BigCodeBench Complete | 62.2% | — |
| ALE-Bench | — | 2,951 |
| HumanEval+ | 86.6% | — |
| MBPP+ | 73% | — |

## Agentic & Tool Use

- DeepSeek-V3: —
- GPT-6 Astra: 52.3 (#3)

| Benchmark | DeepSeek-V3 | GPT-6 Astra |
|---|---|---|
| APEX-Agents | — | 64.7% |
| Remote Labor Index | — | 20.8% |
| BALROG | — | 68.3% |
| METR Time Horizons | 49.6% | — |
| Vending-Bench 2 | — | 15,515 |

## Reasoning

- DeepSeek-V3: 20.0 (#226)
- GPT-6 Astra: 85.1 (#1)

| Benchmark | DeepSeek-V3 | GPT-6 Astra |
|---|---|---|
| CritPt | 0% | 31.7% |
| LMArena Hard Prompts | 1365 | 1464 |
| DTBench | 64.8% | 97.3% |
| LMCA | 15.5% | 64.4% |
| Epoch Capabilities Index | 135.95 | 166.6 |
| ARC-AGI-2 | — | 95% |
| SimpleBench | 27.2% | — |
| Kagi LLM Benchmark | 52.3% | — |
| NYT Connections (extended) | — | 98.1% |
| ARC-AGI-1 | — | 98.5% |
| Chess Puzzles | — | 72% |
| EBR-Bench | — | 76.2% |
| LiveBench Reasoning | 65.8% | — |
| Mystery Game Puzzles | — | 84% |
| LiveBench Data Analysis | 60.9% | — |
| Bench to the Future 3 | — | 0.14 |
| 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)
- GPT-6 Astra: 93.4 (#1)

| Benchmark | DeepSeek-V3 | GPT-6 Astra |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 37.8% | 100% |
| LMArena Math | 1373 | 1463 |
| FrontierMath (Tiers 1-3) | — | 93.7% |
| FrontierMath Tier 4 | — | 97.6% |
| ProofBench | — | 99% |
| Omni-MATH | 40.3% | — |
| LiveBench Math | 73.5% | — |
| MATH Level 5 | 75.5% | — |
| FrontierMath (Feb 2025 set) | 1.7% | — |
| FrontierMath Erdős | — | 2.9% |

## Knowledge

- DeepSeek-V3: 37.5 (#147)
- GPT-6 Astra: 75.3 (#1)

| Benchmark | DeepSeek-V3 | GPT-6 Astra |
|---|---|---|
| GPQA Diamond | 67.6% | 95.8% |
| Vectara Hallucination Rate | 6.1% | 8.7% |
| LMArena Expert | 1352 | 1486 |
| Humanity's Last Exam | — | 54.8% |
| SimpleQA Verified | — | 75.6% |
| MMLU-Pro | 72.3% | — |
| Confabulations | 26.1% | — |
| GPQA (HELM) | 53.8% | — |
| ARC (AI2) Challenge | 95.3% | — |
| MMLU | 87.2% | — |
| TriviaQA | 82.9% | — |

## Multimodal

- DeepSeek-V3: —
- GPT-6 Astra: 55.1 (#3)

| Benchmark | DeepSeek-V3 | GPT-6 Astra |
|---|---|---|
| LMArena Vision | — | 1280 |
| Blueprint-Bench 2 | — | 49.7% |
| Furniture Assembly | — | 80% |
| LMArena Document | — | 1468 |

## Multilingual

- DeepSeek-V3: 48.8 (#138)
- GPT-6 Astra: 54.0 (#53)

| Benchmark | DeepSeek-V3 | GPT-6 Astra |
|---|---|---|
| LMArena Non-English | 1358 | 1431 |
| LMArena Chinese | 1390 | 1495 |
| LMArena French | 1386 | 1467 |
| LMArena Russian | 1372 | 1434 |
| LMArena Spanish | 1358 | 1412 |
| LMArena German | 1374 | — |
| LMArena Japanese | 1333 | — |
| LMArena Korean | 1321 | — |

## Instruction Following

- DeepSeek-V3: 73.0 (#125)
- GPT-6 Astra: 76.6 (#37)

| Benchmark | DeepSeek-V3 | GPT-6 Astra |
|---|---|---|
| LMArena Instruction Following | 1345 | 1454 |
| LiveBench Instruction Following | 81.5% | — |
| IFEval | 83.2% | — |

## Long Context

- DeepSeek-V3: 34.0 (#248)
- GPT-6 Astra: 44.7 (#57)

| Benchmark | DeepSeek-V3 | GPT-6 Astra |
|---|---|---|
| LMArena Longer Query | 1353 | 1460 |
| Fiction.LiveBench | 50% | — |

## Writing & Preference

- DeepSeek-V3: 57.6 (#124)
- GPT-6 Astra: 75.7 (#7)

| Benchmark | DeepSeek-V3 | GPT-6 Astra |
|---|---|---|
| LMArena Text | 1375 | 1443 |
| LMArena Creative Writing | 1364 | 1423 |
| EQ-Bench Creative Writing | 1472 | 2173 |
| LMArena Multi-Turn | 1389 | 1457 |
| Short-Story Creative Writing | 77% | — |
| WildBench | 83% | — |
| LiveBench Language | 49.1% | — |

## FAQ

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

GPT-6 Astra is the stronger model overall, scoring 70.3 to 39.2 on the Noometry Index. DeepSeek-V3 costs 49× less per token, which makes it the better buy when GPT-6 Astra's lead doesn't matter for your workload.

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

DeepSeek-V3 is cheaper. It lists at $0.24 per million input tokens and $0.90 per million output tokens; GPT-6 Astra lists at $10 and $50.

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

GPT-6 Astra scores higher on coding benchmarks: 70.5 versus 41.9 in the Noometry coding category.

### Which has the bigger context window?

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

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

24 benchmarks have published results for both models. DeepSeek-V3 has 60 scored results on Noometry and GPT-6 Astra has 51.