# DeepSeek V4 Flash vs Llama 3-8B

> DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 25.5 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v4-flash-vs-llama-3-8b
- Last updated: 2026-10-10
- Shared benchmarks: 22

## Summary

- They share 22 benchmarks with published results for both. DeepSeek V4 Flash scores higher in 8 categories and Llama 3-8B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where DeepSeek V4 Flash leads 60.3 to 8.8.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 94.4% for DeepSeek V4 Flash and 1.9% for Llama 3-8B.

## Snapshot

| | DeepSeek V4 Flash | Llama 3-8B |
|---|---|---|
| Provider | DeepSeek | Meta |
| Noometry Index | 53.6 | 25.5 |
| Rank | 35 | 344 |
| Context | 1M | — |
| Input $/M | $0.15 | — |
| Output $/M | $0.60 | — |
| Weights | Open | Open |

## Coding

- DeepSeek V4 Flash: 47.9 (#59)
- Llama 3-8B: 31.0 (#289)

| Benchmark | DeepSeek V4 Flash | Llama 3-8B |
|---|---|---|
| LMArena Coding | 1457 | 1152 |
| FrontierCode | 18.8% | — |
| LMArena WebDev | 1582 | — |
| SciCode | 49.9% | — |
| WeirdML | 63% | — |
| BigCodeBench Instruct | — | 31.9% |
| BigCodeBench Complete | — | 36.9% |
| ALE-Bench | 1,306 | — |
| HumanEval+ | — | 56.7% |
| MBPP+ | — | 54.8% |

## Reasoning

- DeepSeek V4 Flash: 53.7 (#30)
- Llama 3-8B: 14.3 (#326)

| Benchmark | DeepSeek V4 Flash | Llama 3-8B |
|---|---|---|
| Chess Puzzles | 33% | 0% |
| LMArena Hard Prompts | 1444 | 1133 |
| DTBench | 90.9% | 43.9% |
| Epoch Capabilities Index | 154.49 | 116.45 |
| ARC-AGI-2 | 61.4% | — |
| SimpleBench | 61.1% | — |
| Kagi LLM Benchmark | 52.2% | — |
| NYT Connections (extended) | 89.6% | — |
| ARC-AGI-1 | 89% | — |
| CritPt | 16.6% | — |
| Mystery Game Puzzles | 34% | — |
| LMCA | 41.7% | — |
| Adversarial NLI | — | 57.3% |
| ForecastBench | — | 58.6 |
| WinoGrande | — | 75.7% |

## Math

- DeepSeek V4 Flash: 60.3 (#37)
- Llama 3-8B: 8.8 (#323)

| Benchmark | DeepSeek V4 Flash | Llama 3-8B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 94.4% | 1.9% |
| LMArena Math | 1427 | 1151 |
| FrontierMath (Tiers 1-3) | 57.5% | — |
| FrontierMath Tier 4 | 24.4% | — |
| MathArena Final-Answer Competitions | 76.5% | — |
| ProofBench | 56% | — |
| MATH Level 5 | — | 6.1% |

## Knowledge

- DeepSeek V4 Flash: 55.4 (#48)
- Llama 3-8B: 7.8 (#308)

| Benchmark | DeepSeek V4 Flash | Llama 3-8B |
|---|---|---|
| GPQA Diamond | 91% | 26.1% |
| LMArena Expert | 1441 | 1113 |
| SimpleQA Verified | 33.6% | — |
| ARC (AI2) Challenge | — | 82.8% |
| MMLU | — | 68.8% |
| OpenBookQA | — | 82.6% |
| TriviaQA | — | 67.7% |

## Multilingual

- DeepSeek V4 Flash: 53.0 (#72)
- Llama 3-8B: 30.8 (#261)

| Benchmark | DeepSeek V4 Flash | Llama 3-8B |
|---|---|---|
| LMArena Non-English | 1420 | 1098 |
| LMArena Chinese | 1468 | 1076 |
| LMArena French | 1439 | 1159 |
| LMArena German | 1418 | 1104 |
| LMArena Japanese | 1406 | 967 |
| LMArena Korean | 1384 | 1004 |
| LMArena Russian | 1428 | 1109 |
| LMArena Spanish | 1436 | 1173 |

## Instruction Following

- DeepSeek V4 Flash: 74.9 (#81)
- Llama 3-8B: 58.4 (#260)

| Benchmark | DeepSeek V4 Flash | Llama 3-8B |
|---|---|---|
| LMArena Instruction Following | 1421 | 1127 |

## Long Context

- DeepSeek V4 Flash: 43.8 (#85)
- Llama 3-8B: 34.2 (#251)

| Benchmark | DeepSeek V4 Flash | Llama 3-8B |
|---|---|---|
| LMArena Longer Query | 1434 | 1128 |

## Writing & Preference

- DeepSeek V4 Flash: 63.8 (#61)
- Llama 3-8B: 37.5 (#256)

| Benchmark | DeepSeek V4 Flash | Llama 3-8B |
|---|---|---|
| LMArena Text | 1432 | 1166 |
| LMArena Creative Writing | 1403 | 1150 |
| LMArena Multi-Turn | 1449 | 1152 |
| EQ-Bench Creative Writing | 1559 | — |

## FAQ

### Is DeepSeek V4 Flash better than Llama 3-8B?

DeepSeek V4 Flash is the stronger model overall, scoring 53.6 to 25.5 on the Noometry Index.

### Is DeepSeek V4 Flash or Llama 3-8B better for coding?

DeepSeek V4 Flash scores higher on coding benchmarks: 47.9 versus 31.0 in the Noometry coding category.

### How many benchmarks do DeepSeek V4 Flash and Llama 3-8B share?

22 benchmarks have published results for both models. DeepSeek V4 Flash has 41 scored results on Noometry and Llama 3-8B has 34.