# Llama 3-8B vs Muse Spark 1.2

> Muse Spark 1.2 is the stronger model overall, scoring 49.8 to 25.3 on the Noometry Index. Llama 3-8B costs 14× less per token, which makes it the better buy when Muse Spark 1.2's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/llama-3-8b-vs-muse-spark-1-2
- Last updated: 2026-10-10
- Shared benchmarks: 13

## Summary

- They share 13 benchmarks with published results for both. Llama 3-8B scores higher in 0 categories and Muse Spark 1.2 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Muse Spark 1.2 leads 53.9 to 7.8.
- The biggest single-benchmark swing is DTBench: 43.9% for Llama 3-8B and 94.7% for Muse Spark 1.2.
- Llama 3-8B is cheaper at $0.14 / $0.14 per million input/output tokens, against $1.25 / $4.25 for Muse Spark 1.2.
- Muse Spark 1.2 accepts more context: 1.05M tokens versus 8K.
- Llama 3-8B has downloadable open weights; the other is API-only.

## Snapshot

| | Llama 3-8B | Muse Spark 1.2 |
|---|---|---|
| Provider | Meta | Meta |
| Noometry Index | 25.3 | 49.8 |
| Rank | 338 | 44 |
| Context | 8K | 1.05M |
| Input $/M | $0.14 | $1.25 |
| Output $/M | $0.14 | $4.25 |
| Weights | Open | Proprietary |

## Coding

- Llama 3-8B: 30.5 (#285)
- Muse Spark 1.2: 48.6 (#49)

| Benchmark | Llama 3-8B | Muse Spark 1.2 |
|---|---|---|
| LMArena Coding | 1152 | 1497 |
| DeepSWE | — | 54.9% |
| LMArena WebDev | — | 1532 |
| FrontierSWE | — | 12% |
| SciCode | — | 56.4% |
| WeirdML | — | 60.3% |
| BigCodeBench Instruct | 31.9% | — |
| BigCodeBench Complete | 36.9% | — |
| HumanEval+ | 56.7% | — |
| MBPP+ | 54.8% | — |

## Agentic & Tool Use

- Llama 3-8B: —
- Muse Spark 1.2: 29.5 (#77)

| Benchmark | Llama 3-8B | Muse Spark 1.2 |
|---|---|---|
| APEX-Agents | — | 36.4% |
| GDP.pdf | — | 16% |

## Reasoning

- Llama 3-8B: 13.8 (#321)
- Muse Spark 1.2: 50.4 (#32)

| Benchmark | Llama 3-8B | Muse Spark 1.2 |
|---|---|---|
| LMArena Hard Prompts | 1133 | 1490 |
| DTBench | 43.9% | 94.7% |
| Epoch Capabilities Index | 116.33 | 155.18 |
| SimpleBench | — | 74.5% |
| NYT Connections (extended) | — | 79.2% |
| CritPt | — | 17.7% |
| Chess Puzzles | 0% | — |
| LMCA | — | 48.4% |
| Adversarial NLI | 57.3% | — |
| ForecastBench | 58.6 | — |
| WinoGrande | 75.7% | — |

## Math

- Llama 3-8B: 8.3 (#317)
- Muse Spark 1.2: 43.8 (#68)

| Benchmark | Llama 3-8B | Muse Spark 1.2 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.9% | — |
| ProofBench | — | 43% |
| LMArena Math | 1151 | — |
| MATH Level 5 | 6.1% | — |

## Knowledge

- Llama 3-8B: 7.8 (#303)
- Muse Spark 1.2: 53.9 (#49)

| Benchmark | Llama 3-8B | Muse Spark 1.2 |
|---|---|---|
| LMArena Expert | 1113 | 1485 |
| GPQA Diamond | 26.1% | — |
| SimpleQA Verified | — | 60.3% |
| ARC (AI2) Challenge | 82.8% | — |
| MMLU | 68.8% | — |
| OpenBookQA | 82.6% | — |
| TriviaQA | 67.7% | — |

## Multimodal

- Llama 3-8B: —
- Muse Spark 1.2: 42.6 (#24)

| Benchmark | Llama 3-8B | Muse Spark 1.2 |
|---|---|---|
| LMArena Vision | — | 1304 |

## Multilingual

- Llama 3-8B: 31.0 (#256)
- Muse Spark 1.2: 57.4 (#10)

| Benchmark | Llama 3-8B | Muse Spark 1.2 |
|---|---|---|
| LMArena Non-English | 1098 | 1479 |
| LMArena Chinese | 1076 | 1519 |
| LMArena Russian | 1109 | 1494 |
| LMArena French | 1158 | — |
| LMArena German | 1104 | — |
| LMArena Japanese | 967 | — |
| LMArena Korean | 1003 | — |
| LMArena Spanish | 1172 | — |

## Instruction Following

- Llama 3-8B: 58.7 (#255)
- Muse Spark 1.2: 77.1 (#30)

| Benchmark | Llama 3-8B | Muse Spark 1.2 |
|---|---|---|
| LMArena Instruction Following | 1127 | 1466 |

## Long Context

- Llama 3-8B: 34.2 (#246)
- Muse Spark 1.2: 45.4 (#35)

| Benchmark | Llama 3-8B | Muse Spark 1.2 |
|---|---|---|
| LMArena Longer Query | 1128 | 1483 |

## Writing & Preference

- Llama 3-8B: 37.7 (#251)
- Muse Spark 1.2: 72.6 (#14)

| Benchmark | Llama 3-8B | Muse Spark 1.2 |
|---|---|---|
| LMArena Text | 1166 | 1486 |
| LMArena Creative Writing | 1150 | 1444 |
| LMArena Multi-Turn | 1152 | 1504 |
| EQ-Bench Creative Writing | — | 1840 |

## FAQ

### Is Llama 3-8B better than Muse Spark 1.2?

Muse Spark 1.2 is the stronger model overall, scoring 49.8 to 25.3 on the Noometry Index. Llama 3-8B costs 14× less per token, which makes it the better buy when Muse Spark 1.2's lead doesn't matter for your workload.

### Which is cheaper, Llama 3-8B or Muse Spark 1.2?

Llama 3-8B is cheaper. It lists at $0.14 per million input tokens and $0.14 per million output tokens; Muse Spark 1.2 lists at $1.25 and $4.25.

### Is Llama 3-8B or Muse Spark 1.2 better for coding?

Muse Spark 1.2 scores higher on coding benchmarks: 48.6 versus 30.5 in the Noometry coding category.

### Which has the bigger context window?

Muse Spark 1.2 does, with 1.05M tokens against 8K.

### How many benchmarks do Llama 3-8B and Muse Spark 1.2 share?

13 benchmarks have published results for both models. Llama 3-8B has 34 scored results on Noometry and Muse Spark 1.2 has 28.