# Llama 3-8B vs Mercury

> Mercury is the stronger model overall, scoring 37.3 to 25.3 on the Noometry Index.

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

## Summary

- They share 8 benchmarks with published results for both. Llama 3-8B scores higher in 0 categories and Mercury in 6 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where Mercury leads 41.7 to 31.0.
- Llama 3-8B has downloadable open weights; the other is API-only.

## Snapshot

| | Llama 3-8B | Mercury |
|---|---|---|
| Provider | Meta | Inception |
| Noometry Index | 25.3 | 37.3 |
| Rank | 338 | 192 |
| Context | 8K | — |
| Input $/M | $0.14 | — |
| Output $/M | $0.14 | — |
| Weights | Open | Proprietary |

## Coding

- Llama 3-8B: 30.5 (#285)
- Mercury: 38.1 (#164)

| Benchmark | Llama 3-8B | Mercury |
|---|---|---|
| LMArena Coding | 1152 | 1323 |
| BigCodeBench Instruct | 31.9% | — |
| BigCodeBench Complete | 36.9% | — |
| HumanEval+ | 56.7% | — |
| MBPP+ | 54.8% | — |

## Reasoning

- Llama 3-8B: 13.8 (#321)
- Mercury: 16.8 (#288)

| Benchmark | Llama 3-8B | Mercury |
|---|---|---|
| LMArena Hard Prompts | 1133 | 1284 |
| Kagi LLM Benchmark | — | 21.6% |
| Chess Puzzles | 0% | — |
| DTBench | 43.9% | — |
| Adversarial NLI | 57.3% | — |
| Epoch Capabilities Index | 116.33 | — |
| ForecastBench | 58.6 | — |
| WinoGrande | 75.7% | — |

## Math

- Llama 3-8B: 8.3 (#317)
- Mercury: —

| Benchmark | Llama 3-8B | Mercury |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.9% | — |
| LMArena Math | 1151 | — |
| MATH Level 5 | 6.1% | — |

## Knowledge

- Llama 3-8B: 7.8 (#303)
- Mercury: —

| Benchmark | Llama 3-8B | Mercury |
|---|---|---|
| GPQA Diamond | 26.1% | — |
| LMArena Expert | 1113 | — |
| ARC (AI2) Challenge | 82.8% | — |
| MMLU | 68.8% | — |
| OpenBookQA | 82.6% | — |
| TriviaQA | 67.7% | — |

## Multilingual

- Llama 3-8B: 31.0 (#256)
- Mercury: 41.7 (#201)

| Benchmark | Llama 3-8B | Mercury |
|---|---|---|
| LMArena Non-English | 1098 | 1259 |
| LMArena Chinese | 1076 | — |
| LMArena French | 1158 | — |
| LMArena German | 1104 | — |
| LMArena Japanese | 967 | — |
| LMArena Korean | 1003 | — |
| LMArena Russian | 1109 | — |
| LMArena Spanish | 1172 | — |

## Instruction Following

- Llama 3-8B: 58.7 (#255)
- Mercury: 65.3 (#220)

| Benchmark | Llama 3-8B | Mercury |
|---|---|---|
| LMArena Instruction Following | 1127 | 1238 |

## Long Context

- Llama 3-8B: 34.2 (#246)
- Mercury: 38.3 (#193)

| Benchmark | Llama 3-8B | Mercury |
|---|---|---|
| LMArena Longer Query | 1128 | 1264 |

## Writing & Preference

- Llama 3-8B: 37.7 (#251)
- Mercury: 46.2 (#216)

| Benchmark | Llama 3-8B | Mercury |
|---|---|---|
| LMArena Text | 1166 | 1282 |
| LMArena Creative Writing | 1150 | 1186 |
| LMArena Multi-Turn | 1152 | 1283 |

## FAQ

### Is Llama 3-8B better than Mercury?

Mercury is the stronger model overall, scoring 37.3 to 25.3 on the Noometry Index.

### Is Llama 3-8B or Mercury better for coding?

Mercury scores higher on coding benchmarks: 38.1 versus 30.5 in the Noometry coding category.

### How many benchmarks do Llama 3-8B and Mercury share?

8 benchmarks have published results for both models. Llama 3-8B has 34 scored results on Noometry and Mercury has 9.