Model comparison
DeepSeek-V3.1 vs Muse Spark
Muse Spark is the stronger model overall, scoring 50.6 to 42.8 on the Noometry Index.
Last verified . 17 shared benchmarks.
DeepSeek
MetaSummary
- They share 17 benchmarks with published results for both. DeepSeek-V3.1 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 43.7.
- DeepSeek-V3.1 has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3.1 | Muse Spark | |
|---|---|---|
| Provider | DeepSeek | Meta |
| Noometry Index | 42.8 | 50.6 |
| Released | 2025-08-21 | 2026-04-08 |
| Weights | Open | Proprietary |
| Context window | 164K | — |
| Max output | 8K | — |
| Input $ / M tokens | $0.25 | — |
| Output $ / M tokens | $0.95 | — |
| Results tracked | 27 | 27 |
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Category by category
Coding Muse Spark leads
DeepSeek-V3.1: 40.3 (#144), Muse Spark: 46.2 (#69)
| Benchmark | DeepSeek-V3.1 | Muse Spark |
|---|---|---|
| LMArena Coding | 1417 | 1481 |
| SciCode | — | 51.5% |
| WeirdML | 38.4% | — |
Reasoning Muse Spark leads
DeepSeek-V3.1: 27.9 (#110), Muse Spark: 35.9 (#67)
| Benchmark | DeepSeek-V3.1 | Muse Spark |
|---|---|---|
| LMArena Hard Prompts | 1417 | 1474 |
| Epoch Capabilities Index | 139.92 | 152.04 |
| SimpleBench | 40% | — |
| Kagi LLM Benchmark | 53.2% | — |
| CritPt | — | 11.3% |
| DTBench | 82.7% | — |
| LMCA | 24.3% | — |
| ForecastBench | 58 | — |
Math Muse Spark leads
DeepSeek-V3.1: 38.9 (#122), Muse Spark: 47.8 (#66)
| Benchmark | DeepSeek-V3.1 | Muse Spark |
|---|---|---|
| LMArena Math | 1420 | 1455 |
| OTIS Mock AIME 2024-2025 | — | 88.9% |
| ProofBench | — | 17% |
| FrontierMath (Feb 2025 set) | — | 39% |
| FrontierMath Tier 4 (v1) | — | 14.6% |
Knowledge Muse Spark leads
DeepSeek-V3.1: 43.7 (#90), Muse Spark: 65.7 (#13)
| Benchmark | DeepSeek-V3.1 | Muse Spark |
|---|---|---|
| LMArena Expert | 1405 | 1457 |
| GPQA Diamond | — | 89.8% |
| Humanity's Last Exam | — | 40.6% |
| Vectara Hallucination Rate | 5.5% | — |
Multimodal Not comparable
DeepSeek-V3.1: —, Muse Spark: 43.4 (#24)
| Benchmark | DeepSeek-V3.1 | Muse Spark |
|---|---|---|
| LMArena Vision | — | 1306 |
| LMArena Document | — | 1444 |
Multilingual Muse Spark leads
DeepSeek-V3.1: 51.6 (#106), Muse Spark: 56.1 (#24)
| Benchmark | DeepSeek-V3.1 | Muse Spark |
|---|---|---|
| LMArena Non-English | 1400 | 1464 |
| LMArena Chinese | 1469 | 1509 |
| LMArena French | 1447 | 1497 |
| LMArena German | 1411 | 1497 |
| LMArena Korean | 1337 | 1459 |
| LMArena Russian | 1405 | 1466 |
| LMArena Spanish | 1431 | 1472 |
| LMArena Japanese | 1378 | — |
Instruction Following Muse Spark leads
DeepSeek-V3.1: 73.9 (#110), Muse Spark: 75.9 (#51)
| Benchmark | DeepSeek-V3.1 | Muse Spark |
|---|---|---|
| LMArena Instruction Following | 1400 | 1442 |
Long Context Muse Spark leads
DeepSeek-V3.1: 36.3 (#232), Muse Spark: 44.4 (#69)
| Benchmark | DeepSeek-V3.1 | Muse Spark |
|---|---|---|
| LMArena Longer Query | 1422 | 1451 |
| Fiction.LiveBench | 52.8% | — |
Writing & Preference Muse Spark leads
DeepSeek-V3.1: 60.3 (#98), Muse Spark: 66.0 (#39)
| Benchmark | DeepSeek-V3.1 | Muse Spark |
|---|---|---|
| LMArena Text | 1420 | 1474 |
| LMArena Creative Writing | 1401 | 1459 |
| LMArena Multi-Turn | 1408 | 1477 |
| EQ-Bench Creative Writing | 1436 | — |
Frequently asked questions
Is DeepSeek-V3.1 better than Muse Spark?
Muse Spark is the stronger model overall, scoring 50.6 to 42.8 on the Noometry Index.
Is DeepSeek-V3.1 or Muse Spark better for coding?
Muse Spark scores higher on coding benchmarks: 46.2 versus 40.3 in the Noometry coding category.
How many benchmarks do DeepSeek-V3.1 and Muse Spark share?
17 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and Muse Spark has 27.