# Grok 4.7 vs Llama 3.1-8B

> Grok 4.7 is the stronger model overall, scoring 46.6 to 22.8 on the Noometry Index. Llama 3.1-8B costs 52× less per token, which makes it the better buy when Grok 4.7's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/grok-4-7-vs-llama-3-1-8b
- Last updated: 2026-10-10
- Shared benchmarks: 15

## Summary

- They share 15 benchmarks with published results for both. Grok 4.7 scores higher in 8 categories and Llama 3.1-8B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where Grok 4.7 leads 70.1 to 29.9.
- The biggest single-benchmark swing is SciCode: 57.4% for Grok 4.7 and 13.2% for Llama 3.1-8B.
- Llama 3.1-8B is cheaper at $0.05 / $0.08 per million input/output tokens, against $2 / $6 for Grok 4.7.
- Grok 4.7 accepts more context: 500K tokens versus 128K.
- Llama 3.1-8B has downloadable open weights; the other is API-only.

## Snapshot

| | Grok 4.7 | Llama 3.1-8B |
|---|---|---|
| Provider | xAI | Meta |
| Noometry Index | 46.6 | 22.8 |
| Rank | 56 | 347 |
| Context | 500K | 128K |
| Input $/M | $2 | $0.05 |
| Output $/M | $6 | $0.08 |
| Weights | Proprietary | Open |

## Coding

- Grok 4.7: 55.0 (#23)
- Llama 3.1-8B: 19.9 (#335)

| Benchmark | Grok 4.7 | Llama 3.1-8B |
|---|---|---|
| SciCode | 57.4% | 13.2% |
| LMArena Coding | 1423 | 1195 |
| CursorBench | 46.3% | — |
| LMArena WebDev | 1636 | — |
| FrontierSWE | 29.5% | — |
| WeirdML | — | 1.7% |
| BigCodeBench Instruct | — | 32.8% |
| BigCodeBench Complete | — | 40.5% |
| HumanEval+ | — | 62.8% |
| MBPP+ | — | 55.6% |

## Agentic & Tool Use

- Grok 4.7: —
- Llama 3.1-8B: 22.3 (#123)

| Benchmark | Grok 4.7 | Llama 3.1-8B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 25.8% |
| BALROG | — | 15.1% |

## Reasoning

- Grok 4.7: 40.1 (#49)
- Llama 3.1-8B: 14.5 (#316)

| Benchmark | Grok 4.7 | Llama 3.1-8B |
|---|---|---|
| CritPt | 17.7% | 0% |
| LMArena Hard Prompts | 1409 | 1175 |
| NYT Connections (extended) | 76.8% | — |
| Chess Puzzles | — | 0% |
| DTBench | — | 50.9% |
| LMCA | — | 5.4% |
| Epoch Capabilities Index | — | 116.48 |
| PIQA | — | 81.2% |

## Math

- Grok 4.7: 41.1 (#73)
- Llama 3.1-8B: 9.5 (#311)

| Benchmark | Grok 4.7 | Llama 3.1-8B |
|---|---|---|
| LMArena Math | 1393 | 1179 |
| OTIS Mock AIME 2024-2025 | — | 1.7% |
| ProofBench | 34% | — |
| Omni-MATH | — | 13.7% |
| MATH Level 5 | — | 22.9% |
| GSM8K | — | 82.4% |

## Knowledge

- Grok 4.7: 38.7 (#130)
- Llama 3.1-8B: 8.0 (#302)

| Benchmark | Grok 4.7 | Llama 3.1-8B |
|---|---|---|
| LMArena Expert | 1413 | 1144 |
| GPQA Diamond | — | 27% |
| MMLU-Pro | — | 40.6% |
| GPQA (HELM) | — | 24.7% |
| BoolQ | — | 82.8% |
| MMLU | — | 56.1% |

## Multimodal

- Grok 4.7: 28.8 (#107)
- Llama 3.1-8B: —

| Benchmark | Grok 4.7 | Llama 3.1-8B |
|---|---|---|
| Furniture Assembly | 20.8% | — |

## Multilingual

- Grok 4.7: 51.2 (#108)
- Llama 3.1-8B: 34.2 (#244)

| Benchmark | Grok 4.7 | Llama 3.1-8B |
|---|---|---|
| LMArena Non-English | 1392 | 1148 |
| LMArena Chinese | 1476 | 1151 |
| LMArena Russian | 1396 | 1158 |
| LMArena French | — | 1176 |
| LMArena German | — | 1144 |
| LMArena Japanese | — | 1061 |
| LMArena Korean | — | 1053 |
| LMArena Spanish | — | 1169 |

## Instruction Following

- Grok 4.7: 74.3 (#98)
- Llama 3.1-8B: 59.1 (#253)

| Benchmark | Grok 4.7 | Llama 3.1-8B |
|---|---|---|
| LMArena Instruction Following | 1406 | 1159 |
| IFEval | — | 74.3% |

## Long Context

- Grok 4.7: 43.2 (#97)
- Llama 3.1-8B: 35.8 (#233)

| Benchmark | Grok 4.7 | Llama 3.1-8B |
|---|---|---|
| LMArena Longer Query | 1416 | 1182 |

## Writing & Preference

- Grok 4.7: 70.1 (#23)
- Llama 3.1-8B: 29.9 (#285)

| Benchmark | Grok 4.7 | Llama 3.1-8B |
|---|---|---|
| LMArena Text | 1397 | 1187 |
| LMArena Creative Writing | 1391 | 1154 |
| EQ-Bench Creative Writing | 2007 | 713 |
| LMArena Multi-Turn | 1389 | 1172 |
| WildBench | — | 68.7% |

## FAQ

### Is Grok 4.7 better than Llama 3.1-8B?

Grok 4.7 is the stronger model overall, scoring 46.6 to 22.8 on the Noometry Index. Llama 3.1-8B costs 52× less per token, which makes it the better buy when Grok 4.7's lead doesn't matter for your workload.

### Which is cheaper, Grok 4.7 or Llama 3.1-8B?

Llama 3.1-8B is cheaper. It lists at $0.05 per million input tokens and $0.08 per million output tokens; Grok 4.7 lists at $2 and $6.

### Is Grok 4.7 or Llama 3.1-8B better for coding?

Grok 4.7 scores higher on coding benchmarks: 55.0 versus 19.9 in the Noometry coding category.

### Which has the bigger context window?

Grok 4.7 does, with 500K tokens against 128K.

### How many benchmarks do Grok 4.7 and Llama 3.1-8B share?

15 benchmarks have published results for both models. Grok 4.7 has 21 scored results on Noometry and Llama 3.1-8B has 43.