# DeepSeek V4.1 Flash vs Muse Spark 1.1

> DeepSeek V4.1 Flash is the stronger model overall, scoring 52.8 to 49.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v4-1-flash-vs-muse-spark-1-1
- Last updated: 2026-10-12
- Shared benchmarks: 30

## Summary

- They share 30 benchmarks with published results for both. DeepSeek V4.1 Flash scores higher in 7 categories and Muse Spark 1.1 in 3 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where DeepSeek V4.1 Flash leads 66.7 to 45.5.
- The biggest single-benchmark swing is ProofBench: 54% for DeepSeek V4.1 Flash and 39% for Muse Spark 1.1.
- DeepSeek V4.1 Flash is cheaper at $0.15 / $0.60 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 1M.
- DeepSeek V4.1 Flash has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek V4.1 Flash | Muse Spark 1.1 |
|---|---|---|
| Provider | DeepSeek | Meta |
| Noometry Index | 52.8 | 49.9 |
| Rank | 38 | 51 |
| Context | 1M | 1.05M |
| Input $/M | $0.15 | $1.25 |
| Output $/M | $0.60 | $4.25 |
| Weights | Open | Proprietary |

## Coding

- DeepSeek V4.1 Flash: 52.9 (#32)
- Muse Spark 1.1: 51.3 (#40)

| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.1 |
|---|---|---|
| LMArena WebDev | 1619 | 1542 |
| SciCode | 51.9% | 58.8% |
| LMArena Coding | 1506 | 1498 |
| DeepSWE | — | 53.3% |
| ALE-Bench | 1,092 | — |

## Agentic & Tool Use

- DeepSeek V4.1 Flash: 31.2 (#69)
- Muse Spark 1.1: 30.8 (#73)

| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.1 |
|---|---|---|
| APEX-Agents | 39.5% | 31.8% |
| GDP.pdf | 19.8% | 15% |
| τ²-bench Banking | — | 40.5% |
| GBAEval | — | 7.9% |
| Vending-Bench 2 | — | 6,520 |

## Reasoning

- DeepSeek V4.1 Flash: 50.2 (#36)
- Muse Spark 1.1: 47.1 (#44)

| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.1 |
|---|---|---|
| NYT Connections (extended) | 89.6% | 84.9% |
| CritPt | 14.3% | 15.1% |
| LMArena Hard Prompts | 1483 | 1486 |
| DTBench | 89.9% | 94.4% |
| LMCA | 47% | 49.9% |
| Surface Evolver Bench | 46.3% | 52.5% |
| Epoch Capabilities Index | 154.9 | 154.21 |
| Mystery Game Puzzles | 43% | — |

## Math

- DeepSeek V4.1 Flash: 66.7 (#25)
- Muse Spark 1.1: 45.5 (#76)

| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.1 |
|---|---|---|
| ProofBench | 54% | 39% |
| LMArena Math | 1477 | 1483 |
| FrontierMath (Tiers 1-3) | 67.4% | — |
| FrontierMath Tier 4 | 26.8% | — |
| OTIS Mock AIME 2024-2025 | 98.3% | — |

## Knowledge

- DeepSeek V4.1 Flash: 57.9 (#38)
- Muse Spark 1.1: 53.1 (#59)

| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.1 |
|---|---|---|
| LMArena Expert | 1506 | 1478 |
| GPQA Diamond | 89.8% | — |
| SimpleQA Verified | — | 57.8% |

## Multimodal

- DeepSeek V4.1 Flash: 39.1 (#61)
- Muse Spark 1.1: 42.6 (#29)

| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.1 |
|---|---|---|
| LMArena Vision | 1277 | 1293 |
| Furniture Assembly | 34.2% | — |
| LMArena Document | — | 1465 |

## Multilingual

- DeepSeek V4.1 Flash: 55.0 (#35)
- Muse Spark 1.1: 56.7 (#17)

| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.1 |
|---|---|---|
| LMArena Non-English | 1448 | 1472 |
| LMArena Chinese | 1497 | 1518 |
| LMArena French | 1452 | 1494 |
| LMArena German | 1484 | 1466 |
| LMArena Japanese | 1412 | 1451 |
| LMArena Korean | 1452 | 1458 |
| LMArena Russian | 1471 | 1483 |
| LMArena Spanish | 1459 | 1464 |

## Instruction Following

- DeepSeek V4.1 Flash: 77.3 (#26)
- Muse Spark 1.1: 76.5 (#39)

| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.1 |
|---|---|---|
| LMArena Instruction Following | 1474 | 1457 |

## Long Context

- DeepSeek V4.1 Flash: 45.2 (#47)
- Muse Spark 1.1: 44.8 (#58)

| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.1 |
|---|---|---|
| LMArena Longer Query | 1475 | 1462 |

## Writing & Preference

- DeepSeek V4.1 Flash: 65.4 (#48)
- Muse Spark 1.1: 73.4 (#11)

| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.1 |
|---|---|---|
| LMArena Text | 1462 | 1479 |
| LMArena Creative Writing | 1435 | 1437 |
| EQ-Bench Creative Writing | 1540 | 1927 |
| LMArena Multi-Turn | 1457 | 1485 |
| EQ-Bench 4 | — | 1260 |

## FAQ

### Is DeepSeek V4.1 Flash better than Muse Spark 1.1?

DeepSeek V4.1 Flash is the stronger model overall, scoring 52.8 to 49.9 on the Noometry Index.

### Which is cheaper, DeepSeek V4.1 Flash or Muse Spark 1.1?

DeepSeek V4.1 Flash is cheaper. It lists at $0.15 per million input tokens and $0.60 per million output tokens; Muse Spark 1.1 lists at $1.25 and $4.25.

### Is DeepSeek V4.1 Flash or Muse Spark 1.1 better for coding?

DeepSeek V4.1 Flash scores higher on coding benchmarks: 52.9 versus 51.3 in the Noometry coding category.

### Which has the bigger context window?

Muse Spark 1.1 does, with 1.05M tokens against 1M.

### How many benchmarks do DeepSeek V4.1 Flash and Muse Spark 1.1 share?

30 benchmarks have published results for both models. DeepSeek V4.1 Flash has 37 scored results on Noometry and Muse Spark 1.1 has 37.