Model comparison
Llama 3.1-8B vs Muse Spark 1.1
Muse Spark 1.1 is the stronger model overall, scoring 49.9 to 23.0 on the Noometry Index. Llama 3.1-8B costs 35× less per token, which makes it the better buy when Muse Spark 1.1's lead doesn't matter for your workload.
Last verified . 23 shared benchmarks.
MetaSummary
- They share 23 benchmarks with published results for both. Llama 3.1-8B scores higher in 0 categories and Muse Spark 1.1 in 9 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Muse Spark 1.1 leads 53.1 to 8.0.
- The biggest single-benchmark swing is SciCode: 13.2% for Llama 3.1-8B and 58.8% for Muse Spark 1.1.
- Llama 3.1-8B is cheaper at $0.05 / $0.08 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 128K.
- Llama 3.1-8B has downloadable open weights; the other is API-only.
Side by side
| Llama 3.1-8B | Muse Spark 1.1 | |
|---|---|---|
| Provider | Meta | Meta |
| Noometry Index | 23.0 | 49.9 |
| Released | 2024-07-23 | 2026-04-08 |
| Weights | Open | Proprietary |
| Context window | 128K | 1.05M |
| Max output | 4K | 131K |
| Input $ / M tokens | $0.05 | $1.25 |
| Output $ / M tokens | $0.08 | $4.25 |
| Results tracked | 43 | 37 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding Muse Spark 1.1 leads
Llama 3.1-8B: 20.2 (#340), Muse Spark 1.1: 51.3 (#40)
| Benchmark | Llama 3.1-8B | Muse Spark 1.1 |
|---|---|---|
| SciCode | 13.2% | 58.8% |
| LMArena Coding | 1195 | 1498 |
| DeepSWE | — | 53.3% |
| LMArena WebDev | — | 1542 |
| WeirdML | 1.7% | — |
| BigCodeBench Instruct | 32.8% | — |
| BigCodeBench Complete | 40.5% | — |
| HumanEval+ | 62.8% | — |
| MBPP+ | 55.6% | — |
Agentic & Tool Use Muse Spark 1.1 leads
Llama 3.1-8B: 22.5 (#131), Muse Spark 1.1: 30.8 (#73)
| Benchmark | Llama 3.1-8B | Muse Spark 1.1 |
|---|---|---|
| APEX-Agents | — | 31.8% |
| Berkeley Function Calling Leaderboard | 25.8% | — |
| τ²-bench Banking | — | 40.5% |
| BALROG | 15.1% | — |
| GBAEval | — | 7.9% |
| GDP.pdf | — | 15% |
| Vending-Bench 2 | — | 6,520 |
Reasoning Muse Spark 1.1 leads
Llama 3.1-8B: 14.9 (#321), Muse Spark 1.1: 47.1 (#44)
| Benchmark | Llama 3.1-8B | Muse Spark 1.1 |
|---|---|---|
| CritPt | 0% | 15.1% |
| LMArena Hard Prompts | 1175 | 1486 |
| DTBench | 50.9% | 94.4% |
| LMCA | 5.4% | 49.9% |
| Epoch Capabilities Index | 116.57 | 154.21 |
| NYT Connections (extended) | — | 84.9% |
| Chess Puzzles | 0% | — |
| Surface Evolver Bench | — | 52.5% |
| PIQA | 81.2% | — |
Math Muse Spark 1.1 leads
Llama 3.1-8B: 10.2 (#317), Muse Spark 1.1: 45.5 (#76)
| Benchmark | Llama 3.1-8B | Muse Spark 1.1 |
|---|---|---|
| LMArena Math | 1179 | 1483 |
| OTIS Mock AIME 2024-2025 | 1.7% | — |
| ProofBench | — | 39% |
| Omni-MATH | 13.7% | — |
| MATH Level 5 | 22.9% | — |
| GSM8K | 82.4% | — |
Knowledge Muse Spark 1.1 leads
Llama 3.1-8B: 8.0 (#307), Muse Spark 1.1: 53.1 (#59)
| Benchmark | Llama 3.1-8B | Muse Spark 1.1 |
|---|---|---|
| LMArena Expert | 1144 | 1478 |
| GPQA Diamond | 27% | — |
| SimpleQA Verified | — | 57.8% |
| MMLU-Pro | 40.6% | — |
| GPQA (HELM) | 24.7% | — |
| BoolQ | 82.8% | — |
| MMLU | 56.1% | — |
Multimodal Not comparable
Llama 3.1-8B: —, Muse Spark 1.1: 42.6 (#29)
| Benchmark | Llama 3.1-8B | Muse Spark 1.1 |
|---|---|---|
| LMArena Vision | — | 1293 |
| LMArena Document | — | 1465 |
Multilingual Muse Spark 1.1 leads
Llama 3.1-8B: 34.0 (#249), Muse Spark 1.1: 56.7 (#17)
| Benchmark | Llama 3.1-8B | Muse Spark 1.1 |
|---|---|---|
| LMArena Non-English | 1148 | 1472 |
| LMArena Chinese | 1151 | 1518 |
| LMArena French | 1177 | 1494 |
| LMArena German | 1144 | 1466 |
| LMArena Japanese | 1061 | 1451 |
| LMArena Korean | 1053 | 1458 |
| LMArena Russian | 1158 | 1483 |
| LMArena Spanish | 1169 | 1464 |
Instruction Following Muse Spark 1.1 leads
Llama 3.1-8B: 58.9 (#258), Muse Spark 1.1: 76.5 (#39)
| Benchmark | Llama 3.1-8B | Muse Spark 1.1 |
|---|---|---|
| LMArena Instruction Following | 1159 | 1457 |
| IFEval | 74.3% | — |
Long Context Muse Spark 1.1 leads
Llama 3.1-8B: 35.8 (#238), Muse Spark 1.1: 44.8 (#58)
| Benchmark | Llama 3.1-8B | Muse Spark 1.1 |
|---|---|---|
| LMArena Longer Query | 1182 | 1462 |
Writing & Preference Muse Spark 1.1 leads
Llama 3.1-8B: 29.7 (#290), Muse Spark 1.1: 73.4 (#11)
| Benchmark | Llama 3.1-8B | Muse Spark 1.1 |
|---|---|---|
| LMArena Text | 1187 | 1479 |
| LMArena Creative Writing | 1154 | 1437 |
| EQ-Bench Creative Writing | 713 | 1927 |
| LMArena Multi-Turn | 1172 | 1485 |
| WildBench | 68.7% | — |
| EQ-Bench 4 | — | 1260 |
Frequently asked questions
Is Llama 3.1-8B better than Muse Spark 1.1?
Muse Spark 1.1 is the stronger model overall, scoring 49.9 to 23.0 on the Noometry Index. Llama 3.1-8B costs 35× 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 3.1-8B or Muse Spark 1.1?
Llama 3.1-8B is cheaper. It lists at $0.05 per million input tokens and $0.08 per million output tokens; Muse Spark 1.1 lists at $1.25 and $4.25.
Is Llama 3.1-8B or Muse Spark 1.1 better for coding?
Muse Spark 1.1 scores higher on coding benchmarks: 51.3 versus 20.2 in the Noometry coding category.
Which has the bigger context window?
Muse Spark 1.1 does, with 1.05M tokens against 128K.
How many benchmarks do Llama 3.1-8B and Muse Spark 1.1 share?
23 benchmarks have published results for both models. Llama 3.1-8B has 43 scored results on Noometry and Muse Spark 1.1 has 37.