Model comparison
Llama 3-8B vs Muse Spark 1.1
Muse Spark 1.1 is the stronger model overall, scoring 49.9 to 25.3 on the Noometry Index. Llama 3-8B costs 14× less per token, which makes it the better buy when Muse Spark 1.1's lead doesn't matter for your workload.
Last verified . 19 shared benchmarks.
MetaSummary
- They share 19 benchmarks with published results for both. Llama 3-8B scores higher in 0 categories and Muse Spark 1.1 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Muse Spark 1.1 leads 52.8 to 7.8.
- The biggest single-benchmark swing is DTBench: 43.9% for Llama 3-8B and 94.4% for Muse Spark 1.1.
- Llama 3-8B is cheaper at $0.14 / $0.14 per million input/output tokens, against $1.25 / $4.25 for Muse Spark 1.1.
- Muse Spark 1.1 accepts more context: 1.05M tokens versus 8K.
- Llama 3-8B has downloadable open weights; the other is API-only.
Side by side
| Llama 3-8B | Muse Spark 1.1 | |
|---|---|---|
| Provider | Meta | Meta |
| Noometry Index | 25.3 | 49.9 |
| Released | 2024-04-18 | 2026-04-08 |
| Weights | Open | Proprietary |
| Context window | 8K | 1.05M |
| Max output | 8K | 131K |
| Input $ / M tokens | $0.14 | $1.25 |
| Output $ / M tokens | $0.14 | $4.25 |
| Results tracked | 34 | 36 |
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Category by category
Coding Muse Spark 1.1 leads
Llama 3-8B: 30.5 (#285), Muse Spark 1.1: 50.8 (#38)
| Benchmark | Llama 3-8B | Muse Spark 1.1 |
|---|---|---|
| LMArena Coding | 1152 | 1497 |
| DeepSWE | — | 53.3% |
| LMArena WebDev | — | 1542 |
| SciCode | — | 58.8% |
| BigCodeBench Instruct | 31.9% | — |
| BigCodeBench Complete | 36.9% | — |
| HumanEval+ | 56.7% | — |
| MBPP+ | 54.8% | — |
Agentic & Tool Use Not comparable
Llama 3-8B: —, Muse Spark 1.1: 33.9 (#45)
| Benchmark | Llama 3-8B | Muse Spark 1.1 |
|---|---|---|
| τ²-bench Banking | — | 40.5% |
| GBAEval | — | 7.9% |
| GDP.pdf | — | 15% |
| Vending-Bench 2 | — | 6,520 |
Reasoning Muse Spark 1.1 leads
Llama 3-8B: 13.8 (#321), Muse Spark 1.1: 45.9 (#41)
| Benchmark | Llama 3-8B | Muse Spark 1.1 |
|---|---|---|
| LMArena Hard Prompts | 1133 | 1486 |
| DTBench | 43.9% | 94.4% |
| Epoch Capabilities Index | 116.33 | 154.32 |
| NYT Connections (extended) | — | 84.9% |
| CritPt | — | 15.1% |
| Chess Puzzles | 0% | — |
| LMCA | — | 49.9% |
| Surface Evolver Bench | — | 52.5% |
| Adversarial NLI | 57.3% | — |
| ForecastBench | 58.6 | — |
| WinoGrande | 75.7% | — |
Math Muse Spark 1.1 leads
Llama 3-8B: 8.3 (#317), Muse Spark 1.1: 44.0 (#67)
| Benchmark | Llama 3-8B | Muse Spark 1.1 |
|---|---|---|
| LMArena Math | 1151 | 1477 |
| OTIS Mock AIME 2024-2025 | 1.9% | — |
| ProofBench | — | 39% |
| MATH Level 5 | 6.1% | — |
Knowledge Muse Spark 1.1 leads
Llama 3-8B: 7.8 (#303), Muse Spark 1.1: 52.8 (#55)
| Benchmark | Llama 3-8B | Muse Spark 1.1 |
|---|---|---|
| LMArena Expert | 1113 | 1480 |
| GPQA Diamond | 26.1% | — |
| SimpleQA Verified | — | 57.8% |
| ARC (AI2) Challenge | 82.8% | — |
| MMLU | 68.8% | — |
| OpenBookQA | 82.6% | — |
| TriviaQA | 67.7% | — |
Multimodal Not comparable
Llama 3-8B: —, Muse Spark 1.1: 41.9 (#28)
| Benchmark | Llama 3-8B | Muse Spark 1.1 |
|---|---|---|
| LMArena Vision | — | 1292 |
| LMArena Document | — | 1465 |
Multilingual Muse Spark 1.1 leads
Llama 3-8B: 31.0 (#256), Muse Spark 1.1: 56.8 (#16)
| Benchmark | Llama 3-8B | Muse Spark 1.1 |
|---|---|---|
| LMArena Non-English | 1098 | 1471 |
| LMArena Chinese | 1076 | 1518 |
| LMArena French | 1158 | 1494 |
| LMArena German | 1104 | 1466 |
| LMArena Japanese | 967 | 1445 |
| LMArena Korean | 1003 | 1459 |
| LMArena Russian | 1109 | 1482 |
| LMArena Spanish | 1172 | 1471 |
Instruction Following Muse Spark 1.1 leads
Llama 3-8B: 58.7 (#255), Muse Spark 1.1: 76.8 (#36)
| Benchmark | Llama 3-8B | Muse Spark 1.1 |
|---|---|---|
| LMArena Instruction Following | 1127 | 1457 |
Long Context Muse Spark 1.1 leads
Llama 3-8B: 34.2 (#246), Muse Spark 1.1: 44.8 (#55)
| Benchmark | Llama 3-8B | Muse Spark 1.1 |
|---|---|---|
| LMArena Longer Query | 1128 | 1463 |
Writing & Preference Muse Spark 1.1 leads
Llama 3-8B: 37.7 (#251), Muse Spark 1.1: 73.6 (#11)
| Benchmark | Llama 3-8B | Muse Spark 1.1 |
|---|---|---|
| LMArena Text | 1166 | 1479 |
| LMArena Creative Writing | 1150 | 1440 |
| LMArena Multi-Turn | 1152 | 1484 |
| EQ-Bench Creative Writing | — | 1927 |
| EQ-Bench 4 | — | 1260 |
Frequently asked questions
Is Llama 3-8B better than Muse Spark 1.1?
Muse Spark 1.1 is the stronger model overall, scoring 49.9 to 25.3 on the Noometry Index. Llama 3-8B costs 14× less per token, which makes it the better buy when Muse Spark 1.1's lead doesn't matter for your workload.
Which is cheaper, Llama 3-8B or Muse Spark 1.1?
Llama 3-8B is cheaper. It lists at $0.14 per million input tokens and $0.14 per million output tokens; Muse Spark 1.1 lists at $1.25 and $4.25.
Is Llama 3-8B or Muse Spark 1.1 better for coding?
Muse Spark 1.1 scores higher on coding benchmarks: 50.8 versus 30.5 in the Noometry coding category.
Which has the bigger context window?
Muse Spark 1.1 does, with 1.05M tokens against 8K.
How many benchmarks do Llama 3-8B and Muse Spark 1.1 share?
19 benchmarks have published results for both models. Llama 3-8B has 34 scored results on Noometry and Muse Spark 1.1 has 36.