# DeepSeek-V3 vs DeepSeek V4.1 Flash

> DeepSeek V4.1 Flash is the stronger model overall, scoring 52.8 to 39.5 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v3-vs-deepseek-v4-1-flash
- Last updated: 2026-10-10
- Shared benchmarks: 25

## Summary

- They share 25 benchmarks with published results for both. DeepSeek-V3 scores higher in 0 categories and DeepSeek V4.1 Flash in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where DeepSeek V4.1 Flash leads 66.7 to 32.1.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 37.8% for DeepSeek-V3 and 98.3% for DeepSeek V4.1 Flash.
- DeepSeek V4.1 Flash is cheaper at $0.15 / $0.60 per million input/output tokens, against $0.24 / $0.90 for DeepSeek-V3.
- DeepSeek V4.1 Flash accepts more context: 1M tokens versus 164K.

## Snapshot

| | DeepSeek-V3 | DeepSeek V4.1 Flash |
|---|---|---|
| Provider | DeepSeek | DeepSeek |
| Noometry Index | 39.5 | 52.8 |
| Rank | 166 | 38 |
| Context | 164K | 1M |
| Input $/M | $0.24 | $0.15 |
| Output $/M | $0.90 | $0.60 |
| Weights | Open | Open |

## Coding

- DeepSeek-V3: 42.3 (#106)
- DeepSeek V4.1 Flash: 52.9 (#32)

| Benchmark | DeepSeek-V3 | DeepSeek V4.1 Flash |
|---|---|---|
| SciCode | 35.8% | 51.9% |
| LMArena Coding | 1368 | 1506 |
| Aider Polyglot | 55.1% | — |
| LMArena WebDev | — | 1619 |
| WeirdML | 36.1% | — |
| BigCodeBench Instruct | 50% | — |
| LiveBench Coding | 70.9% | — |
| BigCodeBench Complete | 62.2% | — |
| ALE-Bench | — | 1,092 |
| HumanEval+ | 86.6% | — |
| MBPP+ | 73% | — |

## Agentic & Tool Use

- DeepSeek-V3: —
- DeepSeek V4.1 Flash: 31.2 (#69)

| Benchmark | DeepSeek-V3 | DeepSeek V4.1 Flash |
|---|---|---|
| APEX-Agents | — | 39.5% |
| GDP.pdf | — | 19.8% |
| METR Time Horizons | 49.6% | — |

## Reasoning

- DeepSeek-V3: 20.5 (#236)
- DeepSeek V4.1 Flash: 50.2 (#36)

| Benchmark | DeepSeek-V3 | DeepSeek V4.1 Flash |
|---|---|---|
| CritPt | 0% | 14.3% |
| LMArena Hard Prompts | 1365 | 1483 |
| DTBench | 64.8% | 89.9% |
| LMCA | 15.5% | 47% |
| Epoch Capabilities Index | 135.94 | 154.9 |
| SimpleBench | 27.2% | — |
| Kagi LLM Benchmark | 52.3% | — |
| NYT Connections (extended) | — | 89.6% |
| LiveBench Reasoning | 65.8% | — |
| Mystery Game Puzzles | — | 43% |
| LiveBench Data Analysis | 60.9% | — |
| Surface Evolver Bench | — | 46.3% |
| BIG-Bench Hard | 87.5% | — |
| ForecastBench | 59.1 | — |
| HellaSwag | 88.9% | — |
| LiveBench | 66.9% | — |
| PIQA | 84.7% | — |
| WinoGrande | 85.2% | — |

## Math

- DeepSeek-V3: 32.1 (#219)
- DeepSeek V4.1 Flash: 66.7 (#25)

| Benchmark | DeepSeek-V3 | DeepSeek V4.1 Flash |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 37.8% | 98.3% |
| LMArena Math | 1373 | 1477 |
| FrontierMath (Tiers 1-3) | — | 67.4% |
| FrontierMath Tier 4 | — | 26.8% |
| ProofBench | — | 54% |
| Omni-MATH | 40.3% | — |
| LiveBench Math | 73.5% | — |
| MATH Level 5 | 75.5% | — |
| FrontierMath (Feb 2025 set) | 1.7% | — |

## Knowledge

- DeepSeek-V3: 37.5 (#155)
- DeepSeek V4.1 Flash: 57.9 (#38)

| Benchmark | DeepSeek-V3 | DeepSeek V4.1 Flash |
|---|---|---|
| GPQA Diamond | 67.6% | 89.8% |
| LMArena Expert | 1351 | 1506 |
| 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: —
- DeepSeek V4.1 Flash: 39.1 (#61)

| Benchmark | DeepSeek-V3 | DeepSeek V4.1 Flash |
|---|---|---|
| LMArena Vision | — | 1277 |
| Furniture Assembly | — | 34.2% |

## Multilingual

- DeepSeek-V3: 48.5 (#143)
- DeepSeek V4.1 Flash: 55.0 (#35)

| Benchmark | DeepSeek-V3 | DeepSeek V4.1 Flash |
|---|---|---|
| LMArena Non-English | 1358 | 1448 |
| LMArena Chinese | 1391 | 1497 |
| LMArena French | 1385 | 1452 |
| LMArena German | 1374 | 1484 |
| LMArena Japanese | 1333 | 1412 |
| LMArena Korean | 1319 | 1452 |
| LMArena Russian | 1373 | 1471 |
| LMArena Spanish | 1358 | 1459 |

## Instruction Following

- DeepSeek-V3: 72.8 (#130)
- DeepSeek V4.1 Flash: 77.3 (#26)

| Benchmark | DeepSeek-V3 | DeepSeek V4.1 Flash |
|---|---|---|
| LMArena Instruction Following | 1345 | 1474 |
| LiveBench Instruction Following | 81.5% | — |
| IFEval | 83.2% | — |

## Long Context

- DeepSeek-V3: 34.0 (#253)
- DeepSeek V4.1 Flash: 45.2 (#47)

| Benchmark | DeepSeek-V3 | DeepSeek V4.1 Flash |
|---|---|---|
| LMArena Longer Query | 1352 | 1475 |
| Fiction.LiveBench | 50% | — |

## Writing & Preference

- DeepSeek-V3: 57.4 (#130)
- DeepSeek V4.1 Flash: 65.4 (#48)

| Benchmark | DeepSeek-V3 | DeepSeek V4.1 Flash |
|---|---|---|
| LMArena Text | 1375 | 1462 |
| LMArena Creative Writing | 1364 | 1435 |
| EQ-Bench Creative Writing | 1472 | 1540 |
| LMArena Multi-Turn | 1389 | 1457 |
| Short-Story Creative Writing | 77% | — |
| WildBench | 83% | — |
| LiveBench Language | 49.1% | — |

## FAQ

### Is DeepSeek-V3 better than DeepSeek V4.1 Flash?

DeepSeek V4.1 Flash is the stronger model overall, scoring 52.8 to 39.5 on the Noometry Index.

### Which is cheaper, DeepSeek-V3 or DeepSeek V4.1 Flash?

DeepSeek V4.1 Flash is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; DeepSeek-V3 lists at $0.24 and $0.90.

### Is DeepSeek-V3 or DeepSeek V4.1 Flash better for coding?

DeepSeek V4.1 Flash scores higher on coding benchmarks: 52.9 versus 42.3 in the Noometry coding category.

### Which has the bigger context window?

DeepSeek V4.1 Flash does, with 1M tokens against 164K.

### How many benchmarks do DeepSeek-V3 and DeepSeek V4.1 Flash share?

25 benchmarks have published results for both models. DeepSeek-V3 has 60 scored results on Noometry and DeepSeek V4.1 Flash has 37.