# Llama-3.3-70B-Instruct vs Muse Spark

> Muse Spark is the stronger model overall, scoring 50.3 to 30.3 on the Noometry Index.

- Canonical page: https://noometry.com/compare/llama-3-3-70b-instruct-vs-muse-spark
- Last updated: 2026-10-10
- Shared benchmarks: 21

## Summary

- They share 21 benchmarks with published results for both. Llama-3.3-70B-Instruct scores higher in 0 categories and Muse Spark in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Muse Spark leads 65.7 to 30.5.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 5.1% for Llama-3.3-70B-Instruct and 88.9% for Muse Spark.
- Llama-3.3-70B-Instruct has downloadable open weights; the other is API-only.

## Snapshot

| | Llama-3.3-70B-Instruct | Muse Spark |
|---|---|---|
| Provider | Meta | Meta |
| Noometry Index | 30.3 | 50.3 |
| Rank | 283 | 41 |
| Context | 128K | — |
| Input $/M | $0.10 | — |
| Output $/M | $0.32 | — |
| Weights | Open | Proprietary |

## Coding

- Llama-3.3-70B-Instruct: 30.6 (#284)
- Muse Spark: 45.6 (#65)

| Benchmark | Llama-3.3-70B-Instruct | Muse Spark |
|---|---|---|
| SciCode | 26% | 51.5% |
| LMArena Coding | 1268 | 1482 |
| WeirdML | 14.4% | — |
| BigCodeBench Instruct | 46.9% | — |
| LiveBench Coding | 36.6% | — |
| BigCodeBench Complete | 57.5% | — |

## Agentic & Tool Use

- Llama-3.3-70B-Instruct: 25.6 (#100)
- Muse Spark: —

| Benchmark | Llama-3.3-70B-Instruct | Muse Spark |
|---|---|---|
| Berkeley Function Calling Leaderboard | 31.9% | — |
| BALROG | 23% | — |

## Reasoning

- Llama-3.3-70B-Instruct: 13.7 (#325)
- Muse Spark: 34.9 (#61)

| Benchmark | Llama-3.3-70B-Instruct | Muse Spark |
|---|---|---|
| CritPt | 0% | 11.3% |
| LMArena Hard Prompts | 1257 | 1475 |
| Epoch Capabilities Index | 127.32 | 152.09 |
| SimpleBench | 19.9% | — |
| LiveBench Reasoning | 50.8% | — |
| DTBench | 59.5% | — |
| LiveBench Data Analysis | 49.5% | — |
| LMCA | 17.5% | — |
| ForecastBench | 58.6 | — |
| LiveBench | 50.2% | — |

## Math

- Llama-3.3-70B-Instruct: 14.3 (#292)
- Muse Spark: 46.8 (#57)

| Benchmark | Llama-3.3-70B-Instruct | Muse Spark |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 5.1% | 88.9% |
| LMArena Math | 1268 | 1455 |
| ProofBench | — | 17% |
| LiveBench Math | 42.2% | — |
| MATH Level 5 | 41.6% | — |
| FrontierMath (Feb 2025 set) | — | 39% |
| FrontierMath Tier 4 (v1) | — | 14.6% |

## Knowledge

- Llama-3.3-70B-Instruct: 30.5 (#220)
- Muse Spark: 65.7 (#12)

| Benchmark | Llama-3.3-70B-Instruct | Muse Spark |
|---|---|---|
| GPQA Diamond | 47.4% | 89.8% |
| LMArena Expert | 1225 | 1458 |
| Humanity's Last Exam | — | 40.6% |
| Confabulations | 22.8% | — |
| Vectara Hallucination Rate | 4.1% | — |
| MMLU | 86.3% | — |

## Multimodal

- Llama-3.3-70B-Instruct: —
- Muse Spark: 42.7 (#23)

| Benchmark | Llama-3.3-70B-Instruct | Muse Spark |
|---|---|---|
| LMArena Vision | — | 1306 |
| LMArena Document | — | 1444 |

## Multilingual

- Llama-3.3-70B-Instruct: 40.1 (#215)
- Muse Spark: 56.3 (#23)

| Benchmark | Llama-3.3-70B-Instruct | Muse Spark |
|---|---|---|
| LMArena Non-English | 1236 | 1464 |
| LMArena Chinese | 1217 | 1507 |
| LMArena French | 1280 | 1497 |
| LMArena German | 1251 | 1497 |
| LMArena Korean | 1142 | 1457 |
| LMArena Russian | 1252 | 1467 |
| LMArena Spanish | 1269 | 1471 |
| LMArena Japanese | 1149 | — |

## Instruction Following

- Llama-3.3-70B-Instruct: 71.3 (#152)
- Muse Spark: 76.1 (#47)

| Benchmark | Llama-3.3-70B-Instruct | Muse Spark |
|---|---|---|
| LMArena Instruction Following | 1242 | 1443 |
| LiveBench Instruction Following | 82.7% | — |

## Long Context

- Llama-3.3-70B-Instruct: 26.4 (#290)
- Muse Spark: 44.4 (#65)

| Benchmark | Llama-3.3-70B-Instruct | Muse Spark |
|---|---|---|
| LMArena Longer Query | 1256 | 1451 |
| Fiction.LiveBench | 33.3% | — |

## Writing & Preference

- Llama-3.3-70B-Instruct: 47.8 (#203)
- Muse Spark: 66.2 (#37)

| Benchmark | Llama-3.3-70B-Instruct | Muse Spark |
|---|---|---|
| LMArena Text | 1274 | 1474 |
| LMArena Creative Writing | 1250 | 1460 |
| LMArena Multi-Turn | 1279 | 1477 |
| LiveBench Language | 39.2% | — |

## FAQ

### Is Llama-3.3-70B-Instruct better than Muse Spark?

Muse Spark is the stronger model overall, scoring 50.3 to 30.3 on the Noometry Index.

### Is Llama-3.3-70B-Instruct or Muse Spark better for coding?

Muse Spark scores higher on coding benchmarks: 45.6 versus 30.6 in the Noometry coding category.

### How many benchmarks do Llama-3.3-70B-Instruct and Muse Spark share?

21 benchmarks have published results for both models. Llama-3.3-70B-Instruct has 43 scored results on Noometry and Muse Spark has 27.