# DeepSeek V4.1 Flash vs GPT-5

> DeepSeek V4.1 Flash is the stronger model overall, scoring 52.8 to 50.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v4-1-flash-vs-gpt-5
- Last updated: 2026-10-10
- Shared benchmarks: 32

## Summary

- They share 32 benchmarks with published results for both. DeepSeek V4.1 Flash scores higher in 7 categories and GPT-5 in 3 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in long context, where GPT-5 leads 69.5 to 45.2.
- The biggest single-benchmark swing is ProofBench: 54% for DeepSeek V4.1 Flash and 18% for GPT-5.
- DeepSeek V4.1 Flash is cheaper at $0.15 / $0.60 per million input/output tokens, against $1.25 / $10 for GPT-5.
- DeepSeek V4.1 Flash accepts more context: 1M tokens versus 400K.
- DeepSeek V4.1 Flash has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek V4.1 Flash | GPT-5 |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 52.8 | 50.9 |
| Rank | 38 | 45 |
| Context | 1M | 400K |
| Input $/M | $0.15 | $1.25 |
| Output $/M | $0.60 | $10 |
| Weights | Open | Proprietary |

## Coding

- DeepSeek V4.1 Flash: 52.9 (#32)
- GPT-5: 50.3 (#47)

| Benchmark | DeepSeek V4.1 Flash | GPT-5 |
|---|---|---|
| LMArena WebDev | 1619 | 1418 |
| SciCode | 51.9% | 42.9% |
| LMArena Coding | 1506 | 1436 |
| ALE-Bench | 1,092 | 1,162 |
| SWE-bench Verified | — | 73.6% |
| SWE-bench Verified (bash only) | — | 65% |
| Aider Polyglot | — | 88% |
| GSO | — | 6.9% |
| WeirdML | — | 60.7% |
| AlgoTune | — | 1.67 |

## Agentic & Tool Use

- DeepSeek V4.1 Flash: 31.2 (#69)
- GPT-5: 33.1 (#56)

| Benchmark | DeepSeek V4.1 Flash | GPT-5 |
|---|---|---|
| Terminal-Bench | — | 49.6% |
| APEX-Agents | 39.5% | — |
| GDPval | — | 34.8% |
| Remote Labor Index | — | 1.7% |
| DeepResearch Bench | — | 49.6% |
| BALROG | — | 32.8% |
| GDP.pdf | 19.8% | — |
| LMArena Search | — | 1133 |
| METR Time Horizons | — | 69.6% |

## Reasoning

- DeepSeek V4.1 Flash: 50.2 (#36)
- GPT-5: 38.3 (#64)

| Benchmark | DeepSeek V4.1 Flash | GPT-5 |
|---|---|---|
| CritPt | 14.3% | 12.6% |
| LMArena Hard Prompts | 1483 | 1416 |
| Mystery Game Puzzles | 43% | 23% |
| DTBench | 89.9% | 90.7% |
| LMCA | 47% | 40% |
| Epoch Capabilities Index | 154.9 | 150 |
| ARC-AGI-2 | — | 9.9% |
| SimpleBench | — | 56.7% |
| Kagi LLM Benchmark | — | 72.7% |
| NYT Connections (extended) | 89.6% | — |
| ARC-AGI-1 | — | 65.7% |
| Chess Puzzles | — | 37% |
| EnigmaEval | — | 10.5% |
| EBR-Bench | — | 12.7% |
| Surface Evolver Bench | 46.3% | — |
| ForecastBench | — | 61.4 |

## Math

- DeepSeek V4.1 Flash: 66.7 (#25)
- GPT-5: 55.0 (#44)

| Benchmark | DeepSeek V4.1 Flash | GPT-5 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 67.4% | 55.4% |
| FrontierMath Tier 4 | 26.8% | 22% |
| OTIS Mock AIME 2024-2025 | 98.3% | 91.4% |
| ProofBench | 54% | 18% |
| LMArena Math | 1477 | 1407 |
| Omni-MATH | — | 64.7% |
| MATH Level 5 | — | 98.1% |
| FrontierMath (Feb 2025 set) | — | 32.4% |
| FrontierMath Tier 4 (v1) | — | 12.5% |

## Knowledge

- DeepSeek V4.1 Flash: 57.9 (#38)
- GPT-5: 56.6 (#43)

| Benchmark | DeepSeek V4.1 Flash | GPT-5 |
|---|---|---|
| GPQA Diamond | 89.8% | 86.2% |
| LMArena Expert | 1506 | 1419 |
| Humanity's Last Exam | — | 25.3% |
| SimpleQA Verified | — | 50.1% |
| MMLU-Pro | — | 86.3% |
| Confabulations | — | 10.3% |
| Vectara Hallucination Rate | — | 14.7% |
| GPQA (HELM) | — | 79.2% |

## Multimodal

- DeepSeek V4.1 Flash: 39.1 (#61)
- GPT-5: 46.8 (#13)

| Benchmark | DeepSeek V4.1 Flash | GPT-5 |
|---|---|---|
| LMArena Vision | 1277 | 1232 |
| GeoBench | — | 81% |
| VPCT | — | 66% |
| Furniture Assembly | 34.2% | — |

## Multilingual

- DeepSeek V4.1 Flash: 55.0 (#35)
- GPT-5: 51.4 (#110)

| Benchmark | DeepSeek V4.1 Flash | GPT-5 |
|---|---|---|
| LMArena Non-English | 1448 | 1397 |
| LMArena Chinese | 1497 | 1422 |
| LMArena French | 1452 | 1410 |
| LMArena German | 1484 | 1416 |
| LMArena Japanese | 1412 | 1409 |
| LMArena Korean | 1452 | 1360 |
| LMArena Russian | 1471 | 1406 |
| LMArena Spanish | 1459 | 1399 |

## Instruction Following

- DeepSeek V4.1 Flash: 77.3 (#26)
- GPT-5: 73.8 (#113)

| Benchmark | DeepSeek V4.1 Flash | GPT-5 |
|---|---|---|
| LMArena Instruction Following | 1474 | 1388 |
| IFEval | — | 87.5% |

## Long Context

- DeepSeek V4.1 Flash: 45.2 (#47)
- GPT-5: 69.5 (#2)

| Benchmark | DeepSeek V4.1 Flash | GPT-5 |
|---|---|---|
| LMArena Longer Query | 1475 | 1399 |
| Fiction.LiveBench | — | 97.2% |

## Writing & Preference

- DeepSeek V4.1 Flash: 65.4 (#48)
- GPT-5: 63.4 (#65)

| Benchmark | DeepSeek V4.1 Flash | GPT-5 |
|---|---|---|
| LMArena Text | 1462 | 1406 |
| LMArena Creative Writing | 1435 | 1365 |
| EQ-Bench Creative Writing | 1540 | 1627 |
| LMArena Multi-Turn | 1457 | 1426 |
| Short-Story Creative Writing | — | 86% |
| WildBench | — | 85.7% |

## FAQ

### Is DeepSeek V4.1 Flash better than GPT-5?

DeepSeek V4.1 Flash is the stronger model overall, scoring 52.8 to 50.9 on the Noometry Index.

### Which is cheaper, DeepSeek V4.1 Flash or GPT-5?

DeepSeek V4.1 Flash is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; GPT-5 lists at $1.25 and $10.

### Is DeepSeek V4.1 Flash or GPT-5 better for coding?

DeepSeek V4.1 Flash scores higher on coding benchmarks: 52.9 versus 50.3 in the Noometry coding category.

### Which has the bigger context window?

DeepSeek V4.1 Flash does, with 1M tokens against 400K.

### How many benchmarks do DeepSeek V4.1 Flash and GPT-5 share?

32 benchmarks have published results for both models. DeepSeek V4.1 Flash has 37 scored results on Noometry and GPT-5 has 69.