Model comparison
Llama-3.3-70B-Instruct vs Muse Spark
Muse Spark is the stronger model overall, scoring 50.6 to 30.6 on the Noometry Index.
Last verified . 21 shared benchmarks.
MetaSummary
- 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 30.6.
- 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.
Side by side
| Llama-3.3-70B-Instruct | Muse Spark | |
|---|---|---|
| Provider | Meta | Meta |
| Noometry Index | 30.6 | 50.6 |
| Released | 2024-12-06 | 2026-04-08 |
| Weights | Open | Proprietary |
| Context window | 128K | — |
| Max output | 4K | — |
| Input $ / M tokens | $0.10 | — |
| Output $ / M tokens | $0.32 | — |
| Results tracked | 43 | 27 |
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Category by category
Coding Muse Spark leads
Llama-3.3-70B-Instruct: 31.0 (#290), Muse Spark: 46.2 (#69)
| Benchmark | Llama-3.3-70B-Instruct | Muse Spark |
|---|---|---|
| SciCode | 26% | 51.5% |
| LMArena Coding | 1268 | 1481 |
| WeirdML | 14.4% | — |
| BigCodeBench Instruct | 46.9% | — |
| LiveBench Coding | 36.6% | — |
| BigCodeBench Complete | 57.5% | — |
Agentic & Tool Use Not comparable
Llama-3.3-70B-Instruct: 25.8 (#105), Muse Spark: —
| Benchmark | Llama-3.3-70B-Instruct | Muse Spark |
|---|---|---|
| Berkeley Function Calling Leaderboard | 31.9% | — |
| BALROG | 23% | — |
Reasoning Muse Spark leads
Llama-3.3-70B-Instruct: 14.1 (#327), Muse Spark: 35.9 (#67)
| Benchmark | Llama-3.3-70B-Instruct | Muse Spark |
|---|---|---|
| CritPt | 0% | 11.3% |
| LMArena Hard Prompts | 1257 | 1474 |
| Epoch Capabilities Index | 127.33 | 152.04 |
| 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 Muse Spark leads
Llama-3.3-70B-Instruct: 15.3 (#298), Muse Spark: 47.8 (#66)
| Benchmark | Llama-3.3-70B-Instruct | Muse Spark |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 5.1% | 88.9% |
| LMArena Math | 1267 | 1455 |
| ProofBench | — | 17% |
| LiveBench Math | 42.2% | — |
| MATH Level 5 | 41.6% | — |
| FrontierMath (Feb 2025 set) | — | 39% |
| FrontierMath Tier 4 (v1) | — | 14.6% |
Knowledge Muse Spark leads
Llama-3.3-70B-Instruct: 30.6 (#226), Muse Spark: 65.7 (#13)
| Benchmark | Llama-3.3-70B-Instruct | Muse Spark |
|---|---|---|
| GPQA Diamond | 47.4% | 89.8% |
| LMArena Expert | 1225 | 1457 |
| Humanity's Last Exam | — | 40.6% |
| Confabulations | 22.8% | — |
| Vectara Hallucination Rate | 4.1% | — |
| MMLU | 86.3% | — |
Multimodal Not comparable
Llama-3.3-70B-Instruct: —, Muse Spark: 43.4 (#24)
| Benchmark | Llama-3.3-70B-Instruct | Muse Spark |
|---|---|---|
| LMArena Vision | — | 1306 |
| LMArena Document | — | 1444 |
Multilingual Muse Spark leads
Llama-3.3-70B-Instruct: 39.9 (#220), Muse Spark: 56.1 (#24)
| Benchmark | Llama-3.3-70B-Instruct | Muse Spark |
|---|---|---|
| LMArena Non-English | 1236 | 1464 |
| LMArena Chinese | 1217 | 1509 |
| LMArena French | 1281 | 1497 |
| LMArena German | 1251 | 1497 |
| LMArena Korean | 1143 | 1459 |
| LMArena Russian | 1252 | 1466 |
| LMArena Spanish | 1270 | 1472 |
| LMArena Japanese | 1150 | — |
Instruction Following Muse Spark leads
Llama-3.3-70B-Instruct: 71.1 (#157), Muse Spark: 75.9 (#51)
| Benchmark | Llama-3.3-70B-Instruct | Muse Spark |
|---|---|---|
| LMArena Instruction Following | 1242 | 1442 |
| LiveBench Instruction Following | 82.7% | — |
Long Context Muse Spark leads
Llama-3.3-70B-Instruct: 26.4 (#295), Muse Spark: 44.4 (#69)
| Benchmark | Llama-3.3-70B-Instruct | Muse Spark |
|---|---|---|
| LMArena Longer Query | 1256 | 1451 |
| Fiction.LiveBench | 33.3% | — |
Writing & Preference Muse Spark leads
Llama-3.3-70B-Instruct: 47.6 (#207), Muse Spark: 66.0 (#39)
| Benchmark | Llama-3.3-70B-Instruct | Muse Spark |
|---|---|---|
| LMArena Text | 1274 | 1474 |
| LMArena Creative Writing | 1250 | 1459 |
| LMArena Multi-Turn | 1280 | 1477 |
| LiveBench Language | 39.2% | — |
Frequently asked questions
Is Llama-3.3-70B-Instruct better than Muse Spark?
Muse Spark is the stronger model overall, scoring 50.6 to 30.6 on the Noometry Index.
Is Llama-3.3-70B-Instruct or Muse Spark better for coding?
Muse Spark scores higher on coding benchmarks: 46.2 versus 31.0 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.