# Llama 3.1-8B vs Mercury

> Mercury is the stronger model overall, scoring 37.6 to 23.0 on the Noometry Index.

- Canonical page: https://noometry.com/compare/llama-3-1-8b-vs-mercury
- Last updated: 2026-10-12
- Shared benchmarks: 8

## Summary

- They share 8 benchmarks with published results for both. Llama 3.1-8B scores higher in 0 categories and Mercury in 6 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in coding, where Mercury leads 38.7 to 20.2.
- Llama 3.1-8B has downloadable open weights; the other is API-only.

## Snapshot

| | Llama 3.1-8B | Mercury |
|---|---|---|
| Provider | Meta | Inception |
| Noometry Index | 23.0 | 37.6 |
| Rank | 352 | 199 |
| Context | 128K | — |
| Input $/M | $0.05 | — |
| Output $/M | $0.08 | — |
| Weights | Open | Proprietary |

## Coding

- Llama 3.1-8B: 20.2 (#340)
- Mercury: 38.7 (#170)

| Benchmark | Llama 3.1-8B | Mercury |
|---|---|---|
| LMArena Coding | 1195 | 1322 |
| SciCode | 13.2% | — |
| WeirdML | 1.7% | — |
| BigCodeBench Instruct | 32.8% | — |
| BigCodeBench Complete | 40.5% | — |
| HumanEval+ | 62.8% | — |
| MBPP+ | 55.6% | — |

## Agentic & Tool Use

- Llama 3.1-8B: 22.5 (#131)
- Mercury: —

| Benchmark | Llama 3.1-8B | Mercury |
|---|---|---|
| Berkeley Function Calling Leaderboard | 25.8% | — |
| BALROG | 15.1% | — |

## Reasoning

- Llama 3.1-8B: 14.9 (#321)
- Mercury: 17.5 (#293)

| Benchmark | Llama 3.1-8B | Mercury |
|---|---|---|
| LMArena Hard Prompts | 1175 | 1285 |
| Kagi LLM Benchmark | — | 21.6% |
| CritPt | 0% | — |
| Chess Puzzles | 0% | — |
| DTBench | 50.9% | — |
| LMCA | 5.4% | — |
| Epoch Capabilities Index | 116.57 | — |
| PIQA | 81.2% | — |

## Math

- Llama 3.1-8B: 10.2 (#317)
- Mercury: —

| Benchmark | Llama 3.1-8B | Mercury |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.7% | — |
| Omni-MATH | 13.7% | — |
| LMArena Math | 1179 | — |
| MATH Level 5 | 22.9% | — |
| GSM8K | 82.4% | — |

## Knowledge

- Llama 3.1-8B: 8.0 (#307)
- Mercury: —

| Benchmark | Llama 3.1-8B | Mercury |
|---|---|---|
| GPQA Diamond | 27% | — |
| MMLU-Pro | 40.6% | — |
| GPQA (HELM) | 24.7% | — |
| LMArena Expert | 1144 | — |
| BoolQ | 82.8% | — |
| MMLU | 56.1% | — |

## Multilingual

- Llama 3.1-8B: 34.0 (#249)
- Mercury: 41.6 (#206)

| Benchmark | Llama 3.1-8B | Mercury |
|---|---|---|
| LMArena Non-English | 1148 | 1260 |
| LMArena Chinese | 1151 | — |
| LMArena French | 1177 | — |
| LMArena German | 1144 | — |
| LMArena Japanese | 1061 | — |
| LMArena Korean | 1053 | — |
| LMArena Russian | 1158 | — |
| LMArena Spanish | 1169 | — |

## Instruction Following

- Llama 3.1-8B: 58.9 (#258)
- Mercury: 65.2 (#224)

| Benchmark | Llama 3.1-8B | Mercury |
|---|---|---|
| LMArena Instruction Following | 1159 | 1239 |
| IFEval | 74.3% | — |

## Long Context

- Llama 3.1-8B: 35.8 (#238)
- Mercury: 38.4 (#198)

| Benchmark | Llama 3.1-8B | Mercury |
|---|---|---|
| LMArena Longer Query | 1182 | 1266 |

## Writing & Preference

- Llama 3.1-8B: 29.7 (#290)
- Mercury: 46.2 (#221)

| Benchmark | Llama 3.1-8B | Mercury |
|---|---|---|
| LMArena Text | 1187 | 1282 |
| LMArena Creative Writing | 1154 | 1191 |
| LMArena Multi-Turn | 1172 | 1282 |
| EQ-Bench Creative Writing | 713 | — |
| WildBench | 68.7% | — |

## FAQ

### Is Llama 3.1-8B better than Mercury?

Mercury is the stronger model overall, scoring 37.6 to 23.0 on the Noometry Index.

### Is Llama 3.1-8B or Mercury better for coding?

Mercury scores higher on coding benchmarks: 38.7 versus 20.2 in the Noometry coding category.

### How many benchmarks do Llama 3.1-8B and Mercury share?

8 benchmarks have published results for both models. Llama 3.1-8B has 43 scored results on Noometry and Mercury has 9.