# DeepSeek-V3.1 vs GPT-5.4 nano

> DeepSeek-V3.1 and GPT-5.4 nano score almost the same on the Noometry Index (42.8 vs 41.9), so choose on price, context window or the category you care about most.

- Canonical page: https://noometry.com/compare/deepseek-v3-1-vs-gpt-5-4-nano
- Last updated: 2026-10-10
- Shared benchmarks: 24

## Summary

- They share 24 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 5 categories and GPT-5.4 nano in 3 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in long context, where GPT-5.4 nano leads 41.6 to 36.3.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 53.2% for DeepSeek-V3.1 and 39.7% for GPT-5.4 nano.
- DeepSeek-V3.1 is cheaper at $0.25 / $0.95 per million input/output tokens, against $0.20 / $1.25 for GPT-5.4 nano.
- GPT-5.4 nano accepts more context: 400K tokens versus 164K.
- DeepSeek-V3.1 has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek-V3.1 | GPT-5.4 nano |
|---|---|---|
| Provider | DeepSeek | OpenAI |
| Noometry Index | 42.8 | 41.9 |
| Rank | 108 | 125 |
| Context | 164K | 400K |
| Input $/M | $0.25 | $0.20 |
| Output $/M | $0.95 | $1.25 |
| Weights | Open | Proprietary |

## Coding

- DeepSeek-V3.1: 40.3 (#144)
- GPT-5.4 nano: 43.6 (#84)

| Benchmark | DeepSeek-V3.1 | GPT-5.4 nano |
|---|---|---|
| WeirdML | 38.4% | 49.2% |
| LMArena Coding | 1417 | 1405 |
| SciCode | — | 46.9% |
| ALE-Bench | — | 1,005 |

## Reasoning

- DeepSeek-V3.1: 27.9 (#110)
- GPT-5.4 nano: 23.7 (#173)

| Benchmark | DeepSeek-V3.1 | GPT-5.4 nano |
|---|---|---|
| Kagi LLM Benchmark | 53.2% | 39.7% |
| LMArena Hard Prompts | 1417 | 1381 |
| DTBench | 82.7% | 80.3% |
| LMCA | 24.3% | 36.9% |
| Epoch Capabilities Index | 139.92 | 145.81 |
| ForecastBench | 58 | 57.3 |
| ARC-AGI-2 | — | 5.7% |
| SimpleBench | 40% | — |
| ARC-AGI-1 | — | 51.5% |
| CritPt | — | 9.3% |
| Chess Puzzles | — | 30% |
| Mystery Game Puzzles | — | 9% |

## Math

- DeepSeek-V3.1: 38.9 (#122)
- GPT-5.4 nano: 40.9 (#88)

| Benchmark | DeepSeek-V3.1 | GPT-5.4 nano |
|---|---|---|
| LMArena Math | 1420 | 1406 |
| FrontierMath (Tiers 1-3) | — | 44.9% |
| FrontierMath Tier 4 | — | 12.2% |
| OTIS Mock AIME 2024-2025 | — | 87.8% |
| ProofBench | — | 5% |
| FrontierMath (Feb 2025 set) | — | 25.9% |
| FrontierMath Tier 4 (v1) | — | 6.3% |

## Knowledge

- DeepSeek-V3.1: 43.7 (#90)
- GPT-5.4 nano: 41.9 (#103)

| Benchmark | DeepSeek-V3.1 | GPT-5.4 nano |
|---|---|---|
| Vectara Hallucination Rate | 5.5% | 3.1% |
| LMArena Expert | 1405 | 1396 |
| GPQA Diamond | — | 78.5% |
| SimpleQA Verified | — | 11.7% |

## Multimodal

- DeepSeek-V3.1: —
- GPT-5.4 nano: 36.7 (#78)

| Benchmark | DeepSeek-V3.1 | GPT-5.4 nano |
|---|---|---|
| LMArena Vision | — | 1196 |

## Multilingual

- DeepSeek-V3.1: 51.6 (#106)
- GPT-5.4 nano: 48.6 (#140)

| Benchmark | DeepSeek-V3.1 | GPT-5.4 nano |
|---|---|---|
| LMArena Non-English | 1400 | 1359 |
| LMArena Chinese | 1469 | 1392 |
| LMArena French | 1447 | 1396 |
| LMArena German | 1411 | 1367 |
| LMArena Japanese | 1378 | 1343 |
| LMArena Korean | 1337 | 1320 |
| LMArena Russian | 1405 | 1363 |
| LMArena Spanish | 1431 | 1371 |

## Instruction Following

- DeepSeek-V3.1: 73.9 (#110)
- GPT-5.4 nano: 71.9 (#144)

| Benchmark | DeepSeek-V3.1 | GPT-5.4 nano |
|---|---|---|
| LMArena Instruction Following | 1400 | 1362 |

## Long Context

- DeepSeek-V3.1: 36.3 (#232)
- GPT-5.4 nano: 41.6 (#137)

| Benchmark | DeepSeek-V3.1 | GPT-5.4 nano |
|---|---|---|
| LMArena Longer Query | 1422 | 1366 |
| Fiction.LiveBench | 52.8% | — |

## Writing & Preference

- DeepSeek-V3.1: 60.3 (#98)
- GPT-5.4 nano: 55.7 (#142)

| Benchmark | DeepSeek-V3.1 | GPT-5.4 nano |
|---|---|---|
| LMArena Text | 1420 | 1372 |
| LMArena Creative Writing | 1401 | 1314 |
| LMArena Multi-Turn | 1408 | 1382 |
| EQ-Bench Creative Writing | 1436 | — |

## FAQ

### Is DeepSeek-V3.1 better than GPT-5.4 nano?

DeepSeek-V3.1 and GPT-5.4 nano score almost the same on the Noometry Index (42.8 vs 41.9), so choose on price, context window or the category you care about most.

### Which is cheaper, DeepSeek-V3.1 or GPT-5.4 nano?

DeepSeek-V3.1 is cheaper. It lists at $0.25 per million input tokens and $0.95 per million output tokens; GPT-5.4 nano lists at $0.20 and $1.25.

### Is DeepSeek-V3.1 or GPT-5.4 nano better for coding?

GPT-5.4 nano scores higher on coding benchmarks: 43.6 versus 40.3 in the Noometry coding category.

### Which has the bigger context window?

GPT-5.4 nano does, with 400K tokens against 164K.

### How many benchmarks do DeepSeek-V3.1 and GPT-5.4 nano share?

24 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and GPT-5.4 nano has 40.