# DeepSeek V4 Flash vs Llama 3.1-405B

> DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 30.7 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v4-flash-vs-llama-3-1-405b
- Last updated: 2026-10-12
- Shared benchmarks: 25

## Summary

- They share 25 benchmarks with published results for both. DeepSeek V4 Flash scores higher in 8 categories and Llama 3.1-405B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where DeepSeek V4 Flash leads 60.3 to 18.4.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 94.4% for DeepSeek V4 Flash and 9.7% for Llama 3.1-405B.

## Snapshot

| | DeepSeek V4 Flash | Llama 3.1-405B |
|---|---|---|
| Provider | DeepSeek | Meta |
| Noometry Index | 53.6 | 30.7 |
| Rank | 35 | 288 |
| Context | 1M | — |
| Input $/M | $0.15 | — |
| Output $/M | $0.60 | — |
| Weights | Open | Open |

## Coding

- DeepSeek V4 Flash: 47.9 (#59)
- Llama 3.1-405B: 33.1 (#262)

| Benchmark | DeepSeek V4 Flash | Llama 3.1-405B |
|---|---|---|
| WeirdML | 63% | 21.4% |
| LMArena Coding | 1457 | 1291 |
| FrontierCode | 18.8% | — |
| LMArena WebDev | 1582 | — |
| SciCode | 49.9% | — |
| ALE-Bench | 1,306 | — |

## Agentic & Tool Use

- DeepSeek V4 Flash: —
- Llama 3.1-405B: 21.0 (#140)

| Benchmark | DeepSeek V4 Flash | Llama 3.1-405B |
|---|---|---|
| TheAgentCompany | — | 7.4% |
| Cybench | — | 7.5% |

## Reasoning

- DeepSeek V4 Flash: 53.7 (#30)
- Llama 3.1-405B: 16.8 (#300)

| Benchmark | DeepSeek V4 Flash | Llama 3.1-405B |
|---|---|---|
| SimpleBench | 61.1% | 23% |
| Kagi LLM Benchmark | 52.2% | 45% |
| LMArena Hard Prompts | 1444 | 1269 |
| DTBench | 90.9% | 61.4% |
| Epoch Capabilities Index | 154.49 | 128.75 |
| ARC-AGI-2 | 61.4% | — |
| NYT Connections (extended) | 89.6% | — |
| ARC-AGI-1 | 89% | — |
| CritPt | 16.6% | — |
| Chess Puzzles | 33% | — |
| Mystery Game Puzzles | 34% | — |
| LMCA | 41.7% | — |
| BIG-Bench Hard | — | 82.9% |
| ForecastBench | — | 59.9 |
| HellaSwag | — | 89.2% |
| PIQA | — | 85.9% |
| WinoGrande | — | 89.2% |

## Math

- DeepSeek V4 Flash: 60.3 (#37)
- Llama 3.1-405B: 18.4 (#290)

| Benchmark | DeepSeek V4 Flash | Llama 3.1-405B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 94.4% | 9.7% |
| LMArena Math | 1427 | 1281 |
| FrontierMath (Tiers 1-3) | 57.5% | — |
| FrontierMath Tier 4 | 24.4% | — |
| MathArena Final-Answer Competitions | 76.5% | — |
| ProofBench | 56% | — |
| Omni-MATH | — | 24.9% |
| MATH Level 5 | — | 49.8% |

## Knowledge

- DeepSeek V4 Flash: 55.4 (#48)
- Llama 3.1-405B: 30.4 (#227)

| Benchmark | DeepSeek V4 Flash | Llama 3.1-405B |
|---|---|---|
| GPQA Diamond | 91% | 50.9% |
| LMArena Expert | 1441 | 1243 |
| SimpleQA Verified | 33.6% | — |
| MMLU-Pro | — | 72.3% |
| Confabulations | — | 17.6% |
| GPQA (HELM) | — | 52.2% |
| ARC (AI2) Challenge | — | 95.3% |
| MMLU | — | 84.5% |
| TriviaQA | — | 82.7% |

## Multilingual

- DeepSeek V4 Flash: 53.0 (#72)
- Llama 3.1-405B: 40.7 (#214)

| Benchmark | DeepSeek V4 Flash | Llama 3.1-405B |
|---|---|---|
| LMArena Non-English | 1420 | 1248 |
| LMArena Chinese | 1468 | 1242 |
| LMArena French | 1439 | 1279 |
| LMArena German | 1418 | 1252 |
| LMArena Japanese | 1406 | 1208 |
| LMArena Korean | 1384 | 1184 |
| LMArena Russian | 1428 | 1265 |
| LMArena Spanish | 1436 | 1260 |

## Instruction Following

- DeepSeek V4 Flash: 74.9 (#81)
- Llama 3.1-405B: 65.9 (#214)

| Benchmark | DeepSeek V4 Flash | Llama 3.1-405B |
|---|---|---|
| LMArena Instruction Following | 1421 | 1259 |
| IFEval | — | 81.1% |

## Long Context

- DeepSeek V4 Flash: 43.8 (#85)
- Llama 3.1-405B: 38.4 (#197)

| Benchmark | DeepSeek V4 Flash | Llama 3.1-405B |
|---|---|---|
| LMArena Longer Query | 1434 | 1266 |

## Writing & Preference

- DeepSeek V4 Flash: 63.8 (#61)
- Llama 3.1-405B: 38.9 (#251)

| Benchmark | DeepSeek V4 Flash | Llama 3.1-405B |
|---|---|---|
| LMArena Text | 1432 | 1284 |
| LMArena Creative Writing | 1403 | 1262 |
| EQ-Bench Creative Writing | 1559 | 870 |
| LMArena Multi-Turn | 1449 | 1297 |
| WildBench | — | 78.3% |

## FAQ

### Is DeepSeek V4 Flash better than Llama 3.1-405B?

DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 30.7 on the Noometry Index.

### Is DeepSeek V4 Flash or Llama 3.1-405B better for coding?

DeepSeek V4 Flash scores higher on coding benchmarks: 47.9 versus 33.1 in the Noometry coding category.

### How many benchmarks do DeepSeek V4 Flash and Llama 3.1-405B share?

25 benchmarks have published results for both models. DeepSeek V4 Flash has 41 scored results on Noometry and Llama 3.1-405B has 42.