DeepSeek V4.1 Flash vs Muse Spark 1.3
Updated October 21, 2026. 82 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Muse Spark 1.3 for coding: it scores 79.7 on the Vibe Coding Index against 77.2 for DeepSeek V4.1 Flash.
Pick DeepSeek V4.1 Flash when output tokens cost 8.1x less, or when what matters is Terminal-Bench 4 (Vals AI) or Vibe Code Bench (Vals AI), where it leads.
- Shared results
- 82
- DeepSeek V4.1 Flash only
- 19
- Muse Spark 1.3 only
- 10
- Like-for-like categories
- 8 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, four public coding benchmarks
Muse Spark 1.3
Muse Spark 1.3 scores 79.7 against 77.2.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
Muse Spark 1.3
Muse Spark 1.3 leads, 48.1 against 24.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Muse Spark 1.3 has a AA Agentic Index result, 55.5.
Directional only
Web design
Design Arena: websites
Muse Spark 1.3
Muse Spark 1.3 leads, 1356 against 1309.
Same board, both measured
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash $0.0003, Muse Spark 1.3 $0.0034 per turn.
List prices
At a glance
- Coding index
- DeepSeek V4.1 Flash 77.2 from 2 benchmarks, Muse Spark 1.3 79.7 from 2 benchmarks.
- Widest category
- Intelligence, 12.5 points apart on average over 2 shared benchmarks.
- Widest single gap
- AA Intelligence Index: DeepSeek V4.1 Flash 24.7 against Muse Spark 1.3 48.1, 23.4 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4.1 Flash $0.525 against Muse Spark 1.3 $4.25 per million output tokens, 8.1x apart.
- Context window
- Both take 1.05M tokens.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | DeepSeek V4.1 Flash | Bars | Muse Spark 1.3 | Ties |
|---|---|---|---|---|
| Coding | 5 | 9 | 2 ties | |
| Intelligence | 0 | 2 | ||
| Agentic work | 3 | 6 | ||
| Reasoning | 3 | 6 | ||
| Math | 0 | 6 | ||
| Knowledge | 0 | 4 | ||
| Web design | 2 | 7 | ||
| General | 1 | 26 | ||
| All shared boards | 14 | 66 | 2 ties |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index59
| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.3 | Leader |
|---|---|---|---|
| LiveBench coding | 90.2% | 90.2% | Tie |
| LMArena WebDev | 1618 | 1659 | Muse Spark 1.3 |
| AA Coding Index | Not measured | 75.8 | Only Muse Spark 1.3 measured |
| Terminal-Bench 4 (Vals AI) | 19.7% | 10.6% | DeepSeek V4.1 Flash |
| Vibe Code Bench (Vals AI) | 84.7% | 82.9% | DeepSeek V4.1 Flash |
| Code migration (Vals AI) | 45.6% | 27.6% | DeepSeek V4.1 Flash |
| ProgramBench (Vals AI) | 0.5% | 0.5% | Tie |
| IOI (Vals AI) | 40.3% | 43.9% | Muse Spark 1.3 |
| Terminal-Bench 2.1 (Vals AI) | 74.5% | 72.3% | DeepSeek V4.1 Flash |
| SWE-bench Multimodal (Vals AI) | 46.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| Vibe Code Bench 1-100 (Vals AI) | 16.4% | Not measured | Only DeepSeek V4.1 Flash measured |
| SkillsBench (Vals AI) | 69.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| CyberBench (Vals AI) | 73.7% | 69.4% | DeepSeek V4.1 Flash |
| SciCode | 51.9% | 59.7% | Muse Spark 1.3 |
| FrontierCode | 43.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| FrontierSWE | Not measured | 25.8% | Only Muse Spark 1.3 measured |
| ALE-Bench | 1092.3 | 1688.3 | Muse Spark 1.3 |
| LMArena Text: coding | 1502 | 1510 | Muse Spark 1.3 |
| LMArena Text: software and IT | 1496 | 1511 | Muse Spark 1.3 |
| LMArena WebDev: React | 1628 | 1672 | Muse Spark 1.3 |
| LMArena WebDev: HTML | 1612 | 1653 | Muse Spark 1.3 |
| LMArena WebDev: from an image | 1606 | 1640 | Muse Spark 1.3 |
| Neither model has a result on the other 16 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 24.7 | 48.1 | Muse Spark 1.3 |
| Epoch Capabilities Index | 155.9 | 157.2 | Muse Spark 1.3 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index36
| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.3 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 55.5 | Only Muse Spark 1.3 measured |
| Design Arena: agents building web apps | Not measured | 1297 | Only Muse Spark 1.3 measured |
| Design Arena: agents building full-stack apps | Not measured | 1295 | Only Muse Spark 1.3 measured |
| Design Arena: agents building mobile apps | Not measured | 1217 | Only Muse Spark 1.3 measured |
| Design Arena: agents building Godot games | Not measured | 1241 | Only Muse Spark 1.3 measured |
| Design Arena: PowerPoint slides | Not measured | 1244 | Only Muse Spark 1.3 measured |
| Design Arena: spreadsheets | Not measured | 1048 | Only Muse Spark 1.3 measured |
| LiveBench research | 86.8% | 68.6% | DeepSeek V4.1 Flash |
| LiveBench browser | 84.0% | 80.0% | DeepSeek V4.1 Flash |
| LiveBench long agentic | 40.1% | 40.4% | Muse Spark 1.3 |
| SREBench (Vals AI) | 0.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| Finance Agent (Vals AI) | 53.5% | 58.9% | Muse Spark 1.3 |
| Tax Agent Bench (Vals AI) | 26.6% | 36.0% | Muse Spark 1.3 |
| Legal Research Bench (Vals AI) | 41.4% | 40.9% | DeepSeek V4.1 Flash |
| Excel Modeling Benchmark (Vals AI) | 57.2% | 62.7% | Muse Spark 1.3 |
| BioMysteryBench (Vals AI) | 67.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| Terminal-Bench-Science (Vals AI) | 0.0% | 4.3% | Muse Spark 1.3 |
| Vals Science Index | 29.6% | Not measured | Only DeepSeek V4.1 Flash measured |
| APEX-Agents | 39.5% | 58.6% | Muse Spark 1.3 |
| Neither model has a result on the other 20 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index36
| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.3 | Leader |
|---|---|---|---|
| LiveBench reasoning | 86.7% | 89.7% | Muse Spark 1.3 |
| MysteryMechanism (Vals AI) | 21.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 94.1% | Only Muse Spark 1.3 measured |
| Humanity's Last Exam (Artificial Analysis run) | 39.2% | 48.7% | Muse Spark 1.3 |
| GPQA Diamond (Epoch AI run) | 89.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| ARC-AGI | 94.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| ARC-AGI-2 | 72.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| Chess puzzles | 48.0% | 37.0% | DeepSeek V4.1 Flash |
| Mystery game puzzles | 43.0% | 25.0% | DeepSeek V4.1 Flash |
| LMArena Text: hard prompts | 1483 | 1503 | Muse Spark 1.3 |
| LMArena Text: expert | 1501 | 1519 | Muse Spark 1.3 |
| LMArena Text: hard prompts in English | 1488 | 1500 | Muse Spark 1.3 |
| LMArena Vision: diagrams | 1297 | 1330 | Muse Spark 1.3 |
| LMArena Vision: homework | 1307 | 1296 | DeepSeek V4.1 Flash |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.3 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.3% | 99.2% | Muse Spark 1.3 |
| FrontierMath, tiers 1 to 3 | 67.4% | 74.4% | Muse Spark 1.3 |
| FrontierMath, tier 4 | 26.8% | 46.3% | Muse Spark 1.3 |
| ProofBench | 54.0% | 58.0% | Muse Spark 1.3 |
| LMArena Text: math | 1478 | 1497 | Muse Spark 1.3 |
| LMArena Text: mathematical work | 1485 | 1491 | Muse Spark 1.3 |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.3 | Leader |
|---|---|---|---|
| LegalBench (Vals AI) | 83.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| MedCode (Vals AI) | 41.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| SimpleQA Verified | 42.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: science | 1469 | 1507 | Muse Spark 1.3 |
| LMArena Text: medicine and healthcare | 1484 | 1493 | Muse Spark 1.3 |
| LMArena Text: legal and government | 1443 | 1499 | Muse Spark 1.3 |
| LMArena Text: business and finance | 1461 | 1490 | Muse Spark 1.3 |
| Neither model has a result on the other 10 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index27
| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.3 | Leader |
|---|---|---|---|
| Design Arena: websites | 1309 | 1356 | Muse Spark 1.3 |
| Design Arena: UI components | 1314 | 1352 | Muse Spark 1.3 |
| Design Arena: game dev | 1331 | 1329 | DeepSeek V4.1 Flash |
| Design Arena: data viz | 1290 | 1343 | Muse Spark 1.3 |
| Design Arena: 3D | 1356 | 1359 | Muse Spark 1.3 |
| Design Arena: all code categories | 1320 | 1353 | Muse Spark 1.3 |
| Design Arena: SVG | 1243 | 1300 | Muse Spark 1.3 |
| Design Arena: ASCII art | 1265 | 1280 | Muse Spark 1.3 |
| LiveBench design | 79.2% | 74.8% | DeepSeek V4.1 Flash |
GeneralLike-for-likePublic boards, shown as published, kept out of the index126
| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.3 | Leader |
|---|---|---|---|
| LiveBench data analysis | 79.3% | 79.6% | Muse Spark 1.3 |
| Public Benefits Bench (Vals AI) | 64.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| SAGE (Vals AI) | 47.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| MedScribe (Vals AI) | 85.5% | Not measured | Only DeepSeek V4.1 Flash measured |
| Long context reasoning (AA-LCR) | 84.0% | 83.0% | DeepSeek V4.1 Flash |
| DTBench | 89.9% | 96.5% | Muse Spark 1.3 |
| LMCA | 47.0% | 53.9% | Muse Spark 1.3 |
| Surface Evolver Bench | 46.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| Furniture assembly | 34.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text | 1464 | 1490 | Muse Spark 1.3 |
| LMArena Text: instruction following | 1473 | 1479 | Muse Spark 1.3 |
| LMArena Text: creative writing | 1437 | 1462 | Muse Spark 1.3 |
| LMArena Vision | 1278 | 1308 | Muse Spark 1.3 |
| LMArena Text: English | 1473 | 1495 | Muse Spark 1.3 |
| LMArena Text: non-English | 1449 | 1481 | Muse Spark 1.3 |
| LMArena Text: Chinese | 1501 | 1532 | Muse Spark 1.3 |
| LMArena Text: German | 1470 | 1513 | Muse Spark 1.3 |
| LMArena Text: Japanese | 1432 | 1470 | Muse Spark 1.3 |
| LMArena Text: Korean | 1436 | 1490 | Muse Spark 1.3 |
| LMArena Text: French | 1465 | 1511 | Muse Spark 1.3 |
| LMArena Text: Spanish | 1459 | 1496 | Muse Spark 1.3 |
| LMArena Text: Russian | 1467 | 1491 | Muse Spark 1.3 |
| LMArena Text: Polish | 1457 | 1490 | Muse Spark 1.3 |
| LMArena Text: multi-turn | 1461 | 1487 | Muse Spark 1.3 |
| LMArena Text: longer queries | 1473 | 1488 | Muse Spark 1.3 |
| LMArena Text: writing and language | 1450 | 1470 | Muse Spark 1.3 |
| LMArena Text: entertainment and media | 1445 | 1457 | Muse Spark 1.3 |
| LMArena Vision: English | 1288 | 1298 | Muse Spark 1.3 |
| LMArena Vision: Chinese | 1327 | 1384 | Muse Spark 1.3 |
| LMArena Vision: reading text | 1282 | 1319 | Muse Spark 1.3 |
| LMArena Vision: humor | 1260 | 1293 | Muse Spark 1.3 |
| LMArena Vision: creative writing | 1275 | 1296 | Muse Spark 1.3 |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.3 | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
DeepSeek V4.1 Flash costs less
Repository review
50K input + 3K output tokens
DeepSeek V4.1 Flash costs less
Agent loop
200K input + 10K output tokens
DeepSeek V4.1 Flash costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | DeepSeek V4.1 Flash | Meta Muse Spark 1.3 |
|---|---|---|
| Maker | DeepSeek | Meta |
| Weights | Open weights | No public weights listed |
| Released | September 10, 2026 | September 2, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.049 | $1.25 |
| Output $/Mtok | $0.525 | $4.25 |
| Coding index | 77.2 | 79.7 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4.1 Flash better than Muse Spark 1.3 for coding?
Pick Muse Spark 1.3 for coding: it scores 79.7 on the Vibe Coding Index against 77.2 for DeepSeek V4.1 Flash. Pick DeepSeek V4.1 Flash when output tokens cost 8.1x less, or when what matters is Terminal-Bench 4 (Vals AI) or Vibe Code Bench (Vals AI), where it leads.
Which is cheaper, DeepSeek V4.1 Flash or Muse Spark 1.3?
DeepSeek V4.1 Flash costs $0.049 per million input tokens and $0.525 per million output tokens; Muse Spark 1.3 costs $1.25 and $4.25. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V4.1 Flash or Muse Spark 1.3?
Neither: both take 1.05M tokens.
How many benchmarks is the DeepSeek V4.1 Flash vs Muse Spark 1.3 comparison based on?
82 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4.1 Flash's coding index rests on 2 independent benchmarks and Muse Spark 1.3's on 2. Where only one model has a result, the page says so instead of naming a winner.