# DeepSeek V4.1 Flash vs GPT-6 Luna

> DeepSeek V4.1 Flash and GPT-6 Luna score almost the same on the Noometry Index (52.8 vs 53.3), so choose on price, context window or the category you care about most.

- Canonical page: https://noometry.com/compare/deepseek-v4-1-flash-vs-gpt-6-luna
- Last updated: 2026-10-10
- Shared benchmarks: 35

## Summary

- They share 35 benchmarks with published results for both. DeepSeek V4.1 Flash scores higher in 6 categories and GPT-6 Luna in 4 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-6 Luna leads 76.1 to 66.7.
- The biggest single-benchmark swing is Mystery Game Puzzles: 43% for DeepSeek V4.1 Flash and 7% for GPT-6 Luna.
- GPT-6 Luna is cheaper at $0.10 / $0.50 per million input/output tokens, against $0.15 / $0.60 for DeepSeek V4.1 Flash.
- GPT-6 Luna accepts more context: 1.05M tokens versus 1M.
- DeepSeek V4.1 Flash has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek V4.1 Flash | GPT-6 Luna |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 52.8 | 53.3 |
| Rank | 38 | 36 |
| Context | 1M | 1.05M |
| Input $/M | $0.15 | $0.10 |
| Output $/M | $0.60 | $0.50 |
| Weights | Open | Proprietary |

## Coding

- DeepSeek V4.1 Flash: 52.9 (#32)
- GPT-6 Luna: 55.5 (#25)

| Benchmark | DeepSeek V4.1 Flash | GPT-6 Luna |
|---|---|---|
| LMArena WebDev | 1619 | 1581 |
| SciCode | 51.9% | 54.6% |
| LMArena Coding | 1506 | 1439 |
| ALE-Bench | 1,092 | 1,577 |
| DeepSWE | — | 66.6% |
| FrontierCode | — | 42.4% |

## Agentic & Tool Use

- DeepSeek V4.1 Flash: 31.2 (#69)
- GPT-6 Luna: 33.3 (#54)

| Benchmark | DeepSeek V4.1 Flash | GPT-6 Luna |
|---|---|---|
| APEX-Agents | 39.5% | 44.3% |
| GDP.pdf | 19.8% | 23% |

## Reasoning

- DeepSeek V4.1 Flash: 50.2 (#36)
- GPT-6 Luna: 48.2 (#41)

| Benchmark | DeepSeek V4.1 Flash | GPT-6 Luna |
|---|---|---|
| NYT Connections (extended) | 89.6% | 68.7% |
| CritPt | 14.3% | 19.4% |
| LMArena Hard Prompts | 1483 | 1411 |
| Mystery Game Puzzles | 43% | 7% |
| DTBench | 89.9% | 90.1% |
| LMCA | 47% | 44.5% |
| Epoch Capabilities Index | 154.9 | 156.28 |
| ARC-AGI-2 | — | 59.3% |
| ARC-AGI-1 | — | 86.7% |
| Chess Puzzles | — | 31% |
| Surface Evolver Bench | 46.3% | — |

## Math

- DeepSeek V4.1 Flash: 66.7 (#25)
- GPT-6 Luna: 76.1 (#15)

| Benchmark | DeepSeek V4.1 Flash | GPT-6 Luna |
|---|---|---|
| FrontierMath (Tiers 1-3) | 67.4% | 78.9% |
| FrontierMath Tier 4 | 26.8% | 56.1% |
| OTIS Mock AIME 2024-2025 | 98.3% | 98.9% |
| ProofBench | 54% | 64% |
| LMArena Math | 1477 | 1416 |

## Knowledge

- DeepSeek V4.1 Flash: 57.9 (#38)
- GPT-6 Luna: 57.0 (#41)

| Benchmark | DeepSeek V4.1 Flash | GPT-6 Luna |
|---|---|---|
| GPQA Diamond | 89.8% | 90.5% |
| LMArena Expert | 1506 | 1444 |
| SimpleQA Verified | — | 41.4% |

## Multimodal

- DeepSeek V4.1 Flash: 39.1 (#61)
- GPT-6 Luna: 42.4 (#30)

| Benchmark | DeepSeek V4.1 Flash | GPT-6 Luna |
|---|---|---|
| LMArena Vision | 1277 | 1217 |
| Furniture Assembly | 34.2% | 44.2% |
| Blueprint-Bench 2 | — | 31.2% |

## Multilingual

- DeepSeek V4.1 Flash: 55.0 (#35)
- GPT-6 Luna: 50.5 (#117)

| Benchmark | DeepSeek V4.1 Flash | GPT-6 Luna |
|---|---|---|
| LMArena Non-English | 1448 | 1386 |
| LMArena Chinese | 1497 | 1433 |
| LMArena French | 1452 | 1420 |
| LMArena German | 1484 | 1369 |
| LMArena Japanese | 1412 | 1369 |
| LMArena Korean | 1452 | 1360 |
| LMArena Russian | 1471 | 1394 |
| LMArena Spanish | 1459 | 1393 |

## Instruction Following

- DeepSeek V4.1 Flash: 77.3 (#26)
- GPT-6 Luna: 74.3 (#99)

| Benchmark | DeepSeek V4.1 Flash | GPT-6 Luna |
|---|---|---|
| LMArena Instruction Following | 1474 | 1409 |

## Long Context

- DeepSeek V4.1 Flash: 45.2 (#47)
- GPT-6 Luna: 43.0 (#111)

| Benchmark | DeepSeek V4.1 Flash | GPT-6 Luna |
|---|---|---|
| LMArena Longer Query | 1475 | 1409 |

## Writing & Preference

- DeepSeek V4.1 Flash: 65.4 (#48)
- GPT-6 Luna: 58.3 (#119)

| Benchmark | DeepSeek V4.1 Flash | GPT-6 Luna |
|---|---|---|
| LMArena Text | 1462 | 1391 |
| LMArena Creative Writing | 1435 | 1363 |
| LMArena Multi-Turn | 1457 | 1396 |
| EQ-Bench Creative Writing | 1540 | — |

## FAQ

### Is DeepSeek V4.1 Flash better than GPT-6 Luna?

DeepSeek V4.1 Flash and GPT-6 Luna score almost the same on the Noometry Index (52.8 vs 53.3), so choose on price, context window or the category you care about most.

### Which is cheaper, DeepSeek V4.1 Flash 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 V4.1 Flash lists at $0.15 and $0.60.

### Is DeepSeek V4.1 Flash or GPT-6 Luna better for coding?

GPT-6 Luna scores higher on coding benchmarks: 55.5 versus 52.9 in the Noometry coding category.

### Which has the bigger context window?

GPT-6 Luna does, with 1.05M tokens against 1M.

### How many benchmarks do DeepSeek V4.1 Flash and GPT-6 Luna share?

35 benchmarks have published results for both models. DeepSeek V4.1 Flash has 37 scored results on Noometry and GPT-6 Luna has 42.