Model comparison
Llama 3.1-70B vs Muse Spark 1.3
Muse Spark 1.3 is the stronger model overall, scoring 54.8 to 29.6 on the Noometry Index. Llama 3.1-70B costs 5.0× less per token, which makes it the better buy when Muse Spark 1.3's lead doesn't matter for your workload.
Last verified . 22 shared benchmarks.
MetaSummary
- They share 22 benchmarks with published results for both. Llama 3.1-70B scores higher in 0 categories and Muse Spark 1.3 in 9 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where Muse Spark 1.3 leads 73.1 to 13.5.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 3.6% for Llama 3.1-70B and 99.2% for Muse Spark 1.3.
- Llama 3.1-70B is cheaper at $0.40 / $0.40 per million input/output tokens, against $1.25 / $4.25 for Muse Spark 1.3.
- Muse Spark 1.3 accepts more context: 1.05M tokens versus 128K.
- Llama 3.1-70B has downloadable open weights; the other is API-only.
Side by side
| Llama 3.1-70B | Muse Spark 1.3 | |
|---|---|---|
| Provider | Meta | Meta |
| Noometry Index | 29.6 | 54.8 |
| Released | 2024-07-23 | 2026-09-02 |
| Weights | Open | Proprietary |
| Context window | 128K | 1.05M |
| Max output | 4K | 131K |
| Input $ / M tokens | $0.40 | $1.25 |
| Output $ / M tokens | $0.40 | $4.25 |
| Results tracked | 35 | 37 |
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Category by category
Coding Muse Spark 1.3 leads
Llama 3.1-70B: 30.3 (#296), Muse Spark 1.3: 56.6 (#21)
| Benchmark | Llama 3.1-70B | Muse Spark 1.3 |
|---|---|---|
| LMArena Coding | 1260 | 1514 |
| CursorBench | — | 41.6% |
| LMArena WebDev | — | 1657 |
| SciCode | — | 59.7% |
| WeirdML | 9% | — |
| BigCodeBench Instruct | 46.1% | — |
| BigCodeBench Complete | 54.8% | — |
Agentic & Tool Use Muse Spark 1.3 leads
Llama 3.1-70B: 25.1 (#112), Muse Spark 1.3: 38.6 (#30)
| Benchmark | Llama 3.1-70B | Muse Spark 1.3 |
|---|---|---|
| APEX-Agents | — | 57.8% |
| TheAgentCompany | 6.9% | — |
| BALROG | 27.9% | — |
| GDP.pdf | — | 27.6% |
Reasoning Muse Spark 1.3 leads
Llama 3.1-70B: 21.6 (#220), Muse Spark 1.3: 54.0 (#27)
| Benchmark | Llama 3.1-70B | Muse Spark 1.3 |
|---|---|---|
| LMArena Hard Prompts | 1241 | 1503 |
| DTBench | 60% | 96.5% |
| LMCA | 14.8% | 53.9% |
| Epoch Capabilities Index | 125.92 | 156.75 |
| NYT Connections (extended) | — | 85.1% |
| CritPt | — | 26% |
| Chess Puzzles | — | 38% |
| Mystery Game Puzzles | — | 25% |
| Bench to the Future 3 | — | 0.14 |
Math Muse Spark 1.3 leads
Llama 3.1-70B: 13.5 (#304), Muse Spark 1.3: 73.1 (#21)
| Benchmark | Llama 3.1-70B | Muse Spark 1.3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 3.6% | 99.2% |
| LMArena Math | 1252 | 1494 |
| FrontierMath (Tiers 1-3) | — | 74.4% |
| FrontierMath Tier 4 | — | 46.3% |
| ProofBench | — | 58% |
| Omni-MATH | 21% | — |
| MATH Level 5 | 36.7% | — |
Knowledge Muse Spark 1.3 leads
Llama 3.1-70B: 24.2 (#269), Muse Spark 1.3: 42.6 (#95)
| Benchmark | Llama 3.1-70B | Muse Spark 1.3 |
|---|---|---|
| LMArena Expert | 1209 | 1516 |
| GPQA Diamond | 44.2% | — |
| MMLU-Pro | 65.3% | — |
| GPQA (HELM) | 42.6% | — |
| MMLU | 80.1% | — |
Multimodal Not comparable
Llama 3.1-70B: —, Muse Spark 1.3: 43.7 (#22)
| Benchmark | Llama 3.1-70B | Muse Spark 1.3 |
|---|---|---|
| LMArena Vision | — | 1309 |
| LMArena Document | — | 1471 |
Multilingual Muse Spark 1.3 leads
Llama 3.1-70B: 38.8 (#225), Muse Spark 1.3: 57.4 (#8)
| Benchmark | Llama 3.1-70B | Muse Spark 1.3 |
|---|---|---|
| LMArena Non-English | 1219 | 1481 |
| LMArena Chinese | 1215 | 1529 |
| LMArena French | 1261 | 1524 |
| LMArena German | 1222 | 1515 |
| LMArena Japanese | 1132 | 1474 |
| LMArena Korean | 1140 | 1501 |
| LMArena Russian | 1234 | 1490 |
| LMArena Spanish | 1253 | 1490 |
Instruction Following Muse Spark 1.3 leads
Llama 3.1-70B: 65.3 (#223), Muse Spark 1.3: 77.5 (#22)
| Benchmark | Llama 3.1-70B | Muse Spark 1.3 |
|---|---|---|
| LMArena Instruction Following | 1231 | 1477 |
| IFEval | 82.1% | — |
Long Context Muse Spark 1.3 leads
Llama 3.1-70B: 37.6 (#214), Muse Spark 1.3: 45.6 (#32)
| Benchmark | Llama 3.1-70B | Muse Spark 1.3 |
|---|---|---|
| LMArena Longer Query | 1241 | 1488 |
Writing & Preference Muse Spark 1.3 leads
Llama 3.1-70B: 35.4 (#267), Muse Spark 1.3: 73.6 (#9)
| Benchmark | Llama 3.1-70B | Muse Spark 1.3 |
|---|---|---|
| LMArena Text | 1261 | 1490 |
| LMArena Creative Writing | 1232 | 1455 |
| EQ-Bench Creative Writing | 784 | 1906 |
| LMArena Multi-Turn | 1256 | 1482 |
| WildBench | 75.8% | — |
Frequently asked questions
Is Llama 3.1-70B better than Muse Spark 1.3?
Muse Spark 1.3 is the stronger model overall, scoring 54.8 to 29.6 on the Noometry Index. Llama 3.1-70B costs 5.0× less per token, which makes it the better buy when Muse Spark 1.3's lead doesn't matter for your workload.
Which is cheaper, Llama 3.1-70B or Muse Spark 1.3?
Llama 3.1-70B is cheaper. It lists at $0.40 per million input tokens and $0.40 per million output tokens; Muse Spark 1.3 lists at $1.25 and $4.25.
Is Llama 3.1-70B or Muse Spark 1.3 better for coding?
Muse Spark 1.3 scores higher on coding benchmarks: 56.6 versus 30.3 in the Noometry coding category.
Which has the bigger context window?
Muse Spark 1.3 does, with 1.05M tokens against 128K.
How many benchmarks do Llama 3.1-70B and Muse Spark 1.3 share?
22 benchmarks have published results for both models. Llama 3.1-70B has 35 scored results on Noometry and Muse Spark 1.3 has 37.