# Llama 3.1-8B vs Yi-34B

> Yi-34B is the stronger model overall, scoring 27.4 to 22.8 on the Noometry Index.

- Canonical page: https://noometry.com/compare/llama-3-1-8b-vs-yi-34b
- Last updated: 2026-10-10
- Shared benchmarks: 22

## Summary

- They share 22 benchmarks with published results for both. Llama 3.1-8B scores higher in 4 categories and Yi-34B in 4 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in coding, where Yi-34B leads 31.8 to 19.9.
- The biggest single-benchmark swing is MATH Level 5: 22.9% for Llama 3.1-8B and 5.1% for Yi-34B.

## Snapshot

| | Llama 3.1-8B | Yi-34B |
|---|---|---|
| Provider | Meta | 01.AI |
| Noometry Index | 22.8 | 27.4 |
| Rank | 347 | 325 |
| Context | 128K | — |
| Input $/M | $0.05 | — |
| Output $/M | $0.08 | — |
| Weights | Open | Open |

## Coding

- Llama 3.1-8B: 19.9 (#335)
- Yi-34B: 31.8 (#269)

| Benchmark | Llama 3.1-8B | Yi-34B |
|---|---|---|
| LMArena Coding | 1195 | 1112 |
| 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: 22.3 (#123)
- Yi-34B: —

| Benchmark | Llama 3.1-8B | Yi-34B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 25.8% | — |
| BALROG | 15.1% | — |

## Reasoning

- Llama 3.1-8B: 14.5 (#316)
- Yi-34B: 20.3 (#222)

| Benchmark | Llama 3.1-8B | Yi-34B |
|---|---|---|
| LMArena Hard Prompts | 1175 | 1104 |
| Epoch Capabilities Index | 116.48 | 117.28 |
| CritPt | 0% | — |
| Chess Puzzles | 0% | — |
| DTBench | 50.9% | — |
| LMCA | 5.4% | — |
| BIG-Bench Hard | — | 71.7% |
| PIQA | 81.2% | — |

## Math

- Llama 3.1-8B: 9.5 (#311)
- Yi-34B: 19.8 (#277)

| Benchmark | Llama 3.1-8B | Yi-34B |
|---|---|---|
| LMArena Math | 1179 | 1114 |
| MATH Level 5 | 22.9% | 5.1% |
| GSM8K | 82.4% | 76% |
| OTIS Mock AIME 2024-2025 | 1.7% | — |
| Omni-MATH | 13.7% | — |

## Knowledge

- Llama 3.1-8B: 8.0 (#302)
- Yi-34B: 7.5 (#304)

| Benchmark | Llama 3.1-8B | Yi-34B |
|---|---|---|
| GPQA Diamond | 27% | 14.7% |
| LMArena Expert | 1144 | 1061 |
| MMLU | 56.1% | 76.3% |
| MMLU-Pro | 40.6% | — |
| GPQA (HELM) | 24.7% | — |
| BoolQ | 82.8% | — |

## Multilingual

- Llama 3.1-8B: 34.2 (#244)
- Yi-34B: 29.9 (#259)

| Benchmark | Llama 3.1-8B | Yi-34B |
|---|---|---|
| LMArena Non-English | 1148 | 1079 |
| LMArena Chinese | 1151 | 1175 |
| LMArena French | 1176 | 1080 |
| LMArena German | 1144 | 1042 |
| LMArena Japanese | 1061 | 993 |
| LMArena Korean | 1053 | 959 |
| LMArena Russian | 1158 | 1050 |
| LMArena Spanish | 1169 | 1070 |

## Instruction Following

- Llama 3.1-8B: 59.1 (#253)
- Yi-34B: 56.4 (#269)

| Benchmark | Llama 3.1-8B | Yi-34B |
|---|---|---|
| LMArena Instruction Following | 1159 | 1091 |
| IFEval | 74.3% | — |

## Long Context

- Llama 3.1-8B: 35.8 (#233)
- Yi-34B: 33.2 (#259)

| Benchmark | Llama 3.1-8B | Yi-34B |
|---|---|---|
| LMArena Longer Query | 1182 | 1094 |

## Writing & Preference

- Llama 3.1-8B: 29.9 (#285)
- Yi-34B: 34.3 (#268)

| Benchmark | Llama 3.1-8B | Yi-34B |
|---|---|---|
| LMArena Text | 1187 | 1129 |
| LMArena Creative Writing | 1154 | 1108 |
| LMArena Multi-Turn | 1172 | 1113 |
| EQ-Bench Creative Writing | 713 | — |
| WildBench | 68.7% | — |

## FAQ

### Is Llama 3.1-8B better than Yi-34B?

Yi-34B is the stronger model overall, scoring 27.4 to 22.8 on the Noometry Index.

### Is Llama 3.1-8B or Yi-34B better for coding?

Yi-34B scores higher on coding benchmarks: 31.8 versus 19.9 in the Noometry coding category.

### How many benchmarks do Llama 3.1-8B and Yi-34B share?

22 benchmarks have published results for both models. Llama 3.1-8B has 43 scored results on Noometry and Yi-34B has 23.