# DeepSeek V4.1 Flash vs Llama 2-13B

> DeepSeek V4.1 Flash is the stronger model overall, scoring 50.3 to 29.1 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v4-1-flash-vs-llama-2-13b
- Last updated: 2026-10-10
- Shared benchmarks: 16

## Summary

- They share 16 benchmarks with published results for both. DeepSeek V4.1 Flash scores higher in 8 categories and Llama 2-13B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek V4.1 Flash leads 65.8 to 30.0.
- The biggest single-benchmark swing is DTBench: 89.9% for DeepSeek V4.1 Flash and 42.2% for Llama 2-13B.

## Snapshot

| | DeepSeek V4.1 Flash | Llama 2-13B |
|---|---|---|
| Provider | DeepSeek | Meta |
| Noometry Index | 50.3 | 29.1 |
| Rank | 40 | 304 |
| Context | 1M | — |
| Input $/M | $0.15 | — |
| Output $/M | $0.60 | — |
| Weights | Open | Open |

## Coding

- DeepSeek V4.1 Flash: 52.8 (#29)
- Llama 2-13B: 30.4 (#287)

| Benchmark | DeepSeek V4.1 Flash | Llama 2-13B |
|---|---|---|
| LMArena Coding | 1511 | 1062 |
| LMArena WebDev | 1620 | — |
| SciCode | 51.9% | — |
| ALE-Bench | 1,092 | — |

## Reasoning

- DeepSeek V4.1 Flash: 46.2 (#39)
- Llama 2-13B: 12.3 (#333)

| Benchmark | DeepSeek V4.1 Flash | Llama 2-13B |
|---|---|---|
| LMArena Hard Prompts | 1485 | 1051 |
| DTBench | 89.9% | 42.2% |
| Epoch Capabilities Index | 155.01 | 105.8 |
| NYT Connections (extended) | 89.6% | — |
| CritPt | 14.3% | — |
| Chess Puzzles | — | 0% |
| LMCA | 47% | — |
| Surface Evolver Bench | 46.3% | — |
| BIG-Bench Hard | — | 58.2% |
| HellaSwag | — | 80.7% |
| LAMBADA | — | 76.5% |
| PIQA | — | 80.8% |
| WinoGrande | — | 72.8% |

## Math

- DeepSeek V4.1 Flash: 48.4 (#52)
- Llama 2-13B: 28.7 (#226)

| Benchmark | DeepSeek V4.1 Flash | Llama 2-13B |
|---|---|---|
| LMArena Math | 1493 | 1065 |
| ProofBench | 54% | — |
| GSM8K | — | 36.9% |

## Knowledge

- DeepSeek V4.1 Flash: 41.6 (#97)
- Llama 2-13B: 27.5 (#244)

| Benchmark | DeepSeek V4.1 Flash | Llama 2-13B |
|---|---|---|
| LMArena Expert | 1505 | 1030 |
| ARC (AI2) Challenge | — | 60.3% |
| BoolQ | — | 82.4% |
| MMLU | — | 55.6% |
| OpenBookQA | — | 57% |
| TriviaQA | — | 79.6% |

## Multimodal

- DeepSeek V4.1 Flash: —
- Llama 2-13B: —

| Benchmark | DeepSeek V4.1 Flash | Llama 2-13B |
|---|---|---|
| ScienceQA | — | 55.8% |

## Multilingual

- DeepSeek V4.1 Flash: 55.5 (#29)
- Llama 2-13B: 26.7 (#274)

| Benchmark | DeepSeek V4.1 Flash | Llama 2-13B |
|---|---|---|
| LMArena Non-English | 1452 | 1024 |
| LMArena Chinese | 1506 | 1001 |
| LMArena French | 1448 | 1043 |
| LMArena Russian | 1473 | 1055 |
| LMArena Spanish | 1499 | 1086 |
| LMArena German | — | 1009 |
| LMArena Japanese | — | 894 |
| LMArena Korean | — | 953 |

## Instruction Following

- DeepSeek V4.1 Flash: 77.6 (#24)
- Llama 2-13B: 53.5 (#282)

| Benchmark | DeepSeek V4.1 Flash | Llama 2-13B |
|---|---|---|
| LMArena Instruction Following | 1475 | 1046 |

## Long Context

- DeepSeek V4.1 Flash: 45.2 (#46)
- Llama 2-13B: 32.3 (#264)

| Benchmark | DeepSeek V4.1 Flash | Llama 2-13B |
|---|---|---|
| LMArena Longer Query | 1476 | 1064 |

## Writing & Preference

- DeepSeek V4.1 Flash: 65.8 (#43)
- Llama 2-13B: 30.0 (#284)

| Benchmark | DeepSeek V4.1 Flash | Llama 2-13B |
|---|---|---|
| LMArena Text | 1465 | 1085 |
| LMArena Creative Writing | 1436 | 1047 |
| LMArena Multi-Turn | 1460 | 1050 |
| EQ-Bench Creative Writing | 1540 | — |

## FAQ

### Is DeepSeek V4.1 Flash better than Llama 2-13B?

DeepSeek V4.1 Flash is the stronger model overall, scoring 50.3 to 29.1 on the Noometry Index.

### Is DeepSeek V4.1 Flash or Llama 2-13B better for coding?

DeepSeek V4.1 Flash scores higher on coding benchmarks: 52.8 versus 30.4 in the Noometry coding category.

### How many benchmarks do DeepSeek V4.1 Flash and Llama 2-13B share?

16 benchmarks have published results for both models. DeepSeek V4.1 Flash has 25 scored results on Noometry and Llama 2-13B has 32.