# Llama 2-70B vs Muse Spark 1.3

> Muse Spark 1.3 is the stronger model overall, scoring 54.8 to 24.4 on the Noometry Index.

- Canonical page: https://noometry.com/compare/llama-2-70b-vs-muse-spark-1-3
- Last updated: 2026-10-12
- Shared benchmarks: 20

## Summary

- They share 20 benchmarks with published results for both. Llama 2-70B scores higher in 0 categories and Muse Spark 1.3 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Muse Spark 1.3 leads 73.1 to 8.1.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 0% for Llama 2-70B and 99.2% for Muse Spark 1.3.
- Llama 2-70B has downloadable open weights; the other is API-only.

## Snapshot

| | Llama 2-70B | Muse Spark 1.3 |
|---|---|---|
| Provider | Meta | Meta |
| Noometry Index | 24.4 | 54.8 |
| Rank | 349 | 27 |
| Context | — | 1.05M |
| Input $/M | — | $1.25 |
| Output $/M | — | $4.25 |
| Weights | Open | Proprietary |

## Coding

- Llama 2-70B: 31.4 (#286)
- Muse Spark 1.3: 56.6 (#21)

| Benchmark | Llama 2-70B | Muse Spark 1.3 |
|---|---|---|
| LMArena Coding | 1079 | 1514 |
| CursorBench | — | 41.6% |
| LMArena WebDev | — | 1657 |
| SciCode | — | 59.7% |

## Agentic & Tool Use

- Llama 2-70B: —
- Muse Spark 1.3: 38.6 (#30)

| Benchmark | Llama 2-70B | Muse Spark 1.3 |
|---|---|---|
| APEX-Agents | — | 57.8% |
| GDP.pdf | — | 27.6% |

## Reasoning

- Llama 2-70B: 14.4 (#325)
- Muse Spark 1.3: 54.0 (#27)

| Benchmark | Llama 2-70B | Muse Spark 1.3 |
|---|---|---|
| LMArena Hard Prompts | 1073 | 1503 |
| DTBench | 41.6% | 96.5% |
| Epoch Capabilities Index | 113.79 | 156.75 |
| NYT Connections (extended) | — | 85.1% |
| CritPt | — | 26% |
| Chess Puzzles | — | 38% |
| Mystery Game Puzzles | — | 25% |
| LMCA | — | 53.9% |
| Bench to the Future 3 | — | 0.14 |
| BIG-Bench Hard | 64.9% | — |
| CommonsenseQA 2.0 | 50% | — |
| ForecastBench | 51.4 | — |
| HellaSwag | 85.3% | — |
| LAMBADA | 78.9% | — |
| PIQA | 82.8% | — |
| WinoGrande | 80.2% | — |

## Math

- Llama 2-70B: 8.1 (#326)
- Muse Spark 1.3: 73.1 (#21)

| Benchmark | Llama 2-70B | Muse Spark 1.3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0% | 99.2% |
| LMArena Math | 1091 | 1494 |
| FrontierMath (Tiers 1-3) | — | 74.4% |
| FrontierMath Tier 4 | — | 46.3% |
| ProofBench | — | 58% |
| MATH Level 5 | 3.3% | — |
| GSM8K | 69.6% | — |

## Knowledge

- Llama 2-70B: 7.4 (#310)
- Muse Spark 1.3: 42.6 (#95)

| Benchmark | Llama 2-70B | Muse Spark 1.3 |
|---|---|---|
| LMArena Expert | 1039 | 1516 |
| GPQA Diamond | 26.3% | — |
| ARC (AI2) Challenge | 78.3% | — |
| BoolQ | 88.6% | — |
| MMLU | 69.9% | — |
| OpenBookQA | 60.2% | — |
| TriviaQA | 87.6% | — |

## Multimodal

- Llama 2-70B: —
- Muse Spark 1.3: 43.7 (#22)

| Benchmark | Llama 2-70B | Muse Spark 1.3 |
|---|---|---|
| LMArena Vision | — | 1309 |
| LMArena Document | — | 1471 |

## Multilingual

- Llama 2-70B: 27.7 (#274)
- Muse Spark 1.3: 57.4 (#8)

| Benchmark | Llama 2-70B | Muse Spark 1.3 |
|---|---|---|
| LMArena Non-English | 1045 | 1481 |
| LMArena Chinese | 995 | 1529 |
| LMArena French | 1090 | 1524 |
| LMArena German | 1041 | 1515 |
| LMArena Japanese | 927 | 1474 |
| LMArena Korean | 964 | 1501 |
| LMArena Russian | 1083 | 1490 |
| LMArena Spanish | 1143 | 1490 |

## Instruction Following

- Llama 2-70B: 54.9 (#278)
- Muse Spark 1.3: 77.5 (#22)

| Benchmark | Llama 2-70B | Muse Spark 1.3 |
|---|---|---|
| LMArena Instruction Following | 1071 | 1477 |

## Long Context

- Llama 2-70B: 32.3 (#270)
- Muse Spark 1.3: 45.6 (#32)

| Benchmark | Llama 2-70B | Muse Spark 1.3 |
|---|---|---|
| LMArena Longer Query | 1062 | 1488 |

## Writing & Preference

- Llama 2-70B: 32.3 (#279)
- Muse Spark 1.3: 73.6 (#9)

| Benchmark | Llama 2-70B | Muse Spark 1.3 |
|---|---|---|
| LMArena Text | 1115 | 1490 |
| LMArena Creative Writing | 1075 | 1455 |
| LMArena Multi-Turn | 1088 | 1482 |
| EQ-Bench Creative Writing | — | 1906 |

## FAQ

### Is Llama 2-70B better than Muse Spark 1.3?

Muse Spark 1.3 is the stronger model overall, scoring 54.8 to 24.4 on the Noometry Index.

### Is Llama 2-70B or Muse Spark 1.3 better for coding?

Muse Spark 1.3 scores higher on coding benchmarks: 56.6 versus 31.4 in the Noometry coding category.

### How many benchmarks do Llama 2-70B and Muse Spark 1.3 share?

20 benchmarks have published results for both models. Llama 2-70B has 35 scored results on Noometry and Muse Spark 1.3 has 37.