# Granite 3.1 8b Instruct vs Llama 3.1-8B

> Granite 3.1 8b Instruct is the stronger model overall, scoring 32.4 to 23.0 on the Noometry Index.

- Canonical page: https://noometry.com/compare/granite-3-1-8b-instruct-vs-llama-3-1-8b
- Last updated: 2026-10-10
- Shared benchmarks: 13

## Summary

- They share 13 benchmarks with published results for both. Granite 3.1 8b Instruct scores higher in 6 categories and Llama 3.1-8B in 3 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Granite 3.1 8b Instruct leads 31.1 to 8.0.

## Snapshot

| | Granite 3.1 8b Instruct | Llama 3.1-8B |
|---|---|---|
| Provider | IBM | Meta |
| Noometry Index | 32.4 | 23.0 |
| Rank | 258 | 352 |
| Context | — | 128K |
| Input $/M | — | $0.05 |
| Output $/M | — | $0.08 |
| Weights | Open | Open |

## Coding

- Granite 3.1 8b Instruct: 34.5 (#233)
- Llama 3.1-8B: 20.2 (#340)

| Benchmark | Granite 3.1 8b Instruct | Llama 3.1-8B |
|---|---|---|
| LMArena Coding | 1186 | 1195 |
| SciCode | — | 13.2% |
| WeirdML | — | 1.7% |
| BigCodeBench Instruct | — | 32.8% |
| BigCodeBench Complete | — | 40.5% |
| HumanEval+ | — | 62.8% |
| MBPP+ | — | 55.6% |

## Agentic & Tool Use

- Granite 3.1 8b Instruct: 24.1 (#120)
- Llama 3.1-8B: 22.5 (#131)

| Benchmark | Granite 3.1 8b Instruct | Llama 3.1-8B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 27.1% | 25.8% |
| BALROG | — | 15.1% |

## Reasoning

- Granite 3.1 8b Instruct: 22.1 (#207)
- Llama 3.1-8B: 14.9 (#321)

| Benchmark | Granite 3.1 8b Instruct | Llama 3.1-8B |
|---|---|---|
| LMArena Hard Prompts | 1145 | 1175 |
| CritPt | — | 0% |
| Chess Puzzles | — | 0% |
| DTBench | — | 50.9% |
| LMCA | — | 5.4% |
| Epoch Capabilities Index | — | 116.57 |
| PIQA | — | 81.2% |

## Math

- Granite 3.1 8b Instruct: 33.0 (#209)
- Llama 3.1-8B: 10.2 (#317)

| Benchmark | Granite 3.1 8b Instruct | Llama 3.1-8B |
|---|---|---|
| LMArena Math | 1152 | 1179 |
| OTIS Mock AIME 2024-2025 | — | 1.7% |
| Omni-MATH | — | 13.7% |
| MATH Level 5 | — | 22.9% |
| GSM8K | — | 82.4% |

## Knowledge

- Granite 3.1 8b Instruct: 31.1 (#220)
- Llama 3.1-8B: 8.0 (#307)

| Benchmark | Granite 3.1 8b Instruct | Llama 3.1-8B |
|---|---|---|
| LMArena Expert | 1142 | 1144 |
| GPQA Diamond | — | 27% |
| MMLU-Pro | — | 40.6% |
| GPQA (HELM) | — | 24.7% |
| BoolQ | — | 82.8% |
| MMLU | — | 56.1% |

## Multilingual

- Granite 3.1 8b Instruct: 30.9 (#260)
- Llama 3.1-8B: 34.0 (#249)

| Benchmark | Granite 3.1 8b Instruct | Llama 3.1-8B |
|---|---|---|
| LMArena Non-English | 1099 | 1148 |
| LMArena Chinese | 1145 | 1151 |
| LMArena Russian | 1092 | 1158 |
| LMArena French | — | 1177 |
| LMArena German | — | 1144 |
| LMArena Japanese | — | 1061 |
| LMArena Korean | — | 1053 |
| LMArena Spanish | — | 1169 |

## Instruction Following

- Granite 3.1 8b Instruct: 58.6 (#259)
- Llama 3.1-8B: 58.9 (#258)

| Benchmark | Granite 3.1 8b Instruct | Llama 3.1-8B |
|---|---|---|
| LMArena Instruction Following | 1131 | 1159 |
| IFEval | — | 74.3% |

## Long Context

- Granite 3.1 8b Instruct: 35.2 (#241)
- Llama 3.1-8B: 35.8 (#238)

| Benchmark | Granite 3.1 8b Instruct | Llama 3.1-8B |
|---|---|---|
| LMArena Longer Query | 1162 | 1182 |

## Writing & Preference

- Granite 3.1 8b Instruct: 35.5 (#266)
- Llama 3.1-8B: 29.7 (#290)

| Benchmark | Granite 3.1 8b Instruct | Llama 3.1-8B |
|---|---|---|
| LMArena Text | 1150 | 1187 |
| LMArena Creative Writing | 1129 | 1154 |
| LMArena Multi-Turn | 1108 | 1172 |
| EQ-Bench Creative Writing | — | 713 |
| WildBench | — | 68.7% |

## FAQ

### Is Granite 3.1 8b Instruct better than Llama 3.1-8B?

Granite 3.1 8b Instruct is the stronger model overall, scoring 32.4 to 23.0 on the Noometry Index.

### Is Granite 3.1 8b Instruct or Llama 3.1-8B better for coding?

Granite 3.1 8b Instruct scores higher on coding benchmarks: 34.5 versus 20.2 in the Noometry coding category.

### How many benchmarks do Granite 3.1 8b Instruct and Llama 3.1-8B share?

13 benchmarks have published results for both models. Granite 3.1 8b Instruct has 13 scored results on Noometry and Llama 3.1-8B has 43.