DeepSeek V4.1 Flash vs Muse Spark 1.1
Updated October 21, 2026. 72 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick DeepSeek V4.1 Flash for coding: it scores 77.2 on the Vibe Coding Index against 48.9 for Muse Spark 1.1.
Pick Muse Spark 1.1 when what matters is SciCode or LMArena Text: software and IT, where it leads.
- Shared results
- 72
- DeepSeek V4.1 Flash only
- 29
- Muse Spark 1.1 only
- 24
- 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
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash scores 77.2 against 48.9.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
Muse Spark 1.1
Muse Spark 1.1 leads, 33.7 against 24.7.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Muse Spark 1.1 has a AA Agentic Index result, 25.8.
Directional only
Reasoning
GPQA Diamond
No call
Only Muse Spark 1.1 has a GPQA Diamond result, 91.2%.
Directional only
Knowledge
MMLU Pro
No call
Only Muse Spark 1.1 has a MMLU Pro result, 88.7%.
Directional only
Web design
Design Arena: websites
DeepSeek V4.1 Flash
DeepSeek V4.1 Flash leads, 1309 against 1270.
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 1.1 $0.0034 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Muse Spark 1.1 has the number, $0.43.
Directional only
At a glance
- Coding index
- DeepSeek V4.1 Flash 77.2 from 2 benchmarks, Muse Spark 1.1 48.9 from 1 benchmark.
- Widest category
- Coding, 7.8 points apart on average over 12 shared benchmarks.
- Widest single gap
- ProofBench: DeepSeek V4.1 Flash 54.0% against Muse Spark 1.1 39.0%, 15.0 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4.1 Flash $0.525 against Muse Spark 1.1 $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 1.1 | Ties |
|---|---|---|---|---|
| Coding | 10 | 2 | ||
| Intelligence | 1 | 1 | ||
| Agentic work | 3 | 1 | ||
| Reasoning | 4 | 3 | ||
| Math | 1 | 2 | ||
| Knowledge | 1 | 5 | ||
| Web design | 7 | 1 | ||
| General | 10 | 20 | ||
| All shared boards | 37 | 35 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index102
| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.1 | Leader |
|---|---|---|---|
| LiveBench coding | 90.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena WebDev | 1618 | 1542 | DeepSeek V4.1 Flash |
| AA Coding Index | Not measured | 71.3 | Only Muse Spark 1.1 measured |
| LiveCodeBench (Vals AI) | Not measured | 85.9% | Only Muse Spark 1.1 measured |
| SWE-bench Verified (Vals AI) | Not measured | 82.0% | Only Muse Spark 1.1 measured |
| Terminal-Bench 4 (Vals AI) | 19.7% | Not measured | Only DeepSeek V4.1 Flash measured |
| Vibe Code Bench (Vals AI) | 84.7% | 72.2% | DeepSeek V4.1 Flash |
| Code migration (Vals AI) | 45.6% | 31.1% | DeepSeek V4.1 Flash |
| ProgramBench (Vals AI) | 0.5% | 0.0% | DeepSeek V4.1 Flash |
| IOI (Vals AI) | 40.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | 74.5% | 69.3% | 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% | 59.2% | DeepSeek V4.1 Flash |
| CyberBench (Vals AI) | 73.7% | Not measured | Only DeepSeek V4.1 Flash measured |
| SciCode | 51.9% | 58.8% | Muse Spark 1.1 |
| FrontierCode | 43.9% | Not measured | Only DeepSeek V4.1 Flash measured |
| ALE-Bench | 1092.3 | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: coding | 1502 | 1498 | DeepSeek V4.1 Flash |
| LMArena Text: software and IT | 1496 | 1498 | Muse Spark 1.1 |
| LMArena WebDev: React | 1628 | 1532 | DeepSeek V4.1 Flash |
| LMArena WebDev: HTML | 1612 | 1540 | DeepSeek V4.1 Flash |
| LMArena WebDev: from an image | 1606 | 1540 | DeepSeek V4.1 Flash |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.1 | Leader |
|---|---|---|---|
| AA Intelligence Index | 24.7 | 33.7 | Muse Spark 1.1 |
| Epoch Capabilities Index | 155.9 | 154.1 | DeepSeek V4.1 Flash |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index31
| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.1 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 25.8 | Only Muse Spark 1.1 measured |
| Design Arena: agents building web apps | Not measured | 1207 | Only Muse Spark 1.1 measured |
| Design Arena: agents building full-stack apps | Not measured | 1199 | Only Muse Spark 1.1 measured |
| Design Arena: agents building mobile apps | Not measured | 1177 | Only Muse Spark 1.1 measured |
| Design Arena: agents building Android apps | Not measured | 1184 | Only Muse Spark 1.1 measured |
| Design Arena: agents building Godot games | Not measured | 1103 | Only Muse Spark 1.1 measured |
| Design Arena: agents building games | Not measured | 1183 | Only Muse Spark 1.1 measured |
| Design Arena: HTML slides | Not measured | 1194 | Only Muse Spark 1.1 measured |
| Design Arena: PowerPoint slides | Not measured | 1156 | Only Muse Spark 1.1 measured |
| Design Arena: spreadsheets | Not measured | 974 | Only Muse Spark 1.1 measured |
| LiveBench research | 86.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| LiveBench browser | 84.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| LiveBench long agentic | 40.1% | Not measured | Only DeepSeek V4.1 Flash measured |
| SREBench (Vals AI) | 0.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| Finance Agent (Vals AI) | 53.5% | 57.2% | Muse Spark 1.1 |
| Tax Agent Bench (Vals AI) | 26.6% | Not measured | Only DeepSeek V4.1 Flash measured |
| Legal Research Bench (Vals AI) | 41.4% | 38.0% | DeepSeek V4.1 Flash |
| Excel Modeling Benchmark (Vals AI) | 57.2% | 56.4% | DeepSeek V4.1 Flash |
| BioMysteryBench (Vals AI) | 67.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| Terminal-Bench-Science (Vals AI) | 0.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| Vals Science Index | 29.6% | Not measured | Only DeepSeek V4.1 Flash measured |
| Time Horizon Index (Vals AI) | Not measured | 1.7% | Only Muse Spark 1.1 measured |
| APEX-Agents | 39.5% | 31.8% | DeepSeek V4.1 Flash |
| Vending-Bench 2 | Not measured | $6,520 | Only Muse Spark 1.1 measured |
| Neither model has a result on the other 15 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index43
| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.1 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 91.2% | Only Muse Spark 1.1 measured |
| LiveBench reasoning | 86.7% | Not measured | Only DeepSeek V4.1 Flash measured |
| MysteryMechanism (Vals AI) | 21.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| MMMU Pro (Vals AI) | Not measured | 86.6% | Only Muse Spark 1.1 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 89.8% | Only Muse Spark 1.1 measured |
| Humanity's Last Exam (Artificial Analysis run) | 39.2% | 46.2% | Muse Spark 1.1 |
| 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% | 34.0% | DeepSeek V4.1 Flash |
| Mystery game puzzles | 43.0% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text: hard prompts | 1483 | 1485 | Muse Spark 1.1 |
| LMArena Text: expert | 1501 | 1478 | DeepSeek V4.1 Flash |
| LMArena Text: hard prompts in English | 1488 | 1480 | DeepSeek V4.1 Flash |
| LMArena Vision: diagrams | 1297 | 1305 | Muse Spark 1.1 |
| LMArena Vision: homework | 1307 | 1287 | DeepSeek V4.1 Flash |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.1 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| FrontierMath, tiers 1 to 3 | 67.4% | Not measured | Only DeepSeek V4.1 Flash measured |
| FrontierMath, tier 4 | 26.8% | Not measured | Only DeepSeek V4.1 Flash measured |
| ProofBench | 54.0% | 39.0% | DeepSeek V4.1 Flash |
| LMArena Text: math | 1478 | 1482 | Muse Spark 1.1 |
| LMArena Text: mathematical work | 1485 | 1487 | Muse Spark 1.1 |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index15
| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.1 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 88.7% | Only Muse Spark 1.1 measured |
| LegalBench (Vals AI) | 83.3% | 85.0% | Muse Spark 1.1 |
| CorpFin (Vals AI) | Not measured | 71.3% | Only Muse Spark 1.1 measured |
| TaxEval (Vals AI) | Not measured | 79.7% | Only Muse Spark 1.1 measured |
| MortgageTax (Vals AI) | Not measured | 66.1% | Only Muse Spark 1.1 measured |
| MedCode (Vals AI) | 41.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| SimpleQA Verified | 42.9% | 57.8% | Muse Spark 1.1 |
| LMArena Text: science | 1469 | 1484 | Muse Spark 1.1 |
| LMArena Text: medicine and healthcare | 1484 | 1479 | DeepSeek V4.1 Flash |
| LMArena Text: legal and government | 1443 | 1481 | Muse Spark 1.1 |
| LMArena Text: business and finance | 1461 | 1470 | Muse Spark 1.1 |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index71
| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.1 | Leader |
|---|---|---|---|
| Design Arena: websites | 1309 | 1270 | DeepSeek V4.1 Flash |
| Design Arena: UI components | 1314 | 1290 | DeepSeek V4.1 Flash |
| Design Arena: game dev | 1331 | 1269 | DeepSeek V4.1 Flash |
| Design Arena: data viz | 1290 | 1268 | DeepSeek V4.1 Flash |
| Design Arena: 3D | 1356 | 1260 | DeepSeek V4.1 Flash |
| Design Arena: all code categories | 1320 | 1276 | DeepSeek V4.1 Flash |
| Design Arena: SVG | 1243 | 1234 | DeepSeek V4.1 Flash |
| Design Arena: ASCII art | 1265 | 1270 | Muse Spark 1.1 |
| LiveBench design | 79.2% | Not measured | Only DeepSeek V4.1 Flash measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index1020
| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.1 | Leader |
|---|---|---|---|
| LiveBench data analysis | 79.3% | Not measured | Only DeepSeek V4.1 Flash measured |
| Public Benefits Bench (Vals AI) | 64.3% | 61.3% | DeepSeek V4.1 Flash |
| SAGE (Vals AI) | 47.9% | 45.6% | DeepSeek V4.1 Flash |
| MedScribe (Vals AI) | 85.5% | 88.9% | Muse Spark 1.1 |
| Vals Multimodal Index | Not measured | 66.7% | Only Muse Spark 1.1 measured |
| Long context reasoning (AA-LCR) | 84.0% | 77.7% | DeepSeek V4.1 Flash |
| DTBench | 89.9% | 94.4% | Muse Spark 1.1 |
| LMCA | 47.0% | 49.9% | Muse Spark 1.1 |
| Surface Evolver Bench | 46.3% | 52.5% | Muse Spark 1.1 |
| Furniture assembly | 34.2% | Not measured | Only DeepSeek V4.1 Flash measured |
| LMArena Text | 1464 | 1478 | Muse Spark 1.1 |
| LMArena Text: instruction following | 1473 | 1457 | DeepSeek V4.1 Flash |
| LMArena Text: creative writing | 1437 | 1435 | DeepSeek V4.1 Flash |
| LMArena Vision | 1278 | 1293 | Muse Spark 1.1 |
| LMArena Text: English | 1473 | 1478 | Muse Spark 1.1 |
| LMArena Text: non-English | 1449 | 1471 | Muse Spark 1.1 |
| LMArena Text: Chinese | 1501 | 1515 | Muse Spark 1.1 |
| LMArena Text: German | 1470 | 1469 | DeepSeek V4.1 Flash |
| LMArena Text: Japanese | 1432 | 1450 | Muse Spark 1.1 |
| LMArena Text: Korean | 1436 | 1459 | Muse Spark 1.1 |
| LMArena Text: French | 1465 | 1492 | Muse Spark 1.1 |
| LMArena Text: Spanish | 1459 | 1464 | Muse Spark 1.1 |
| LMArena Text: Russian | 1467 | 1482 | Muse Spark 1.1 |
| LMArena Text: Polish | 1457 | 1499 | Muse Spark 1.1 |
| LMArena Text: multi-turn | 1461 | 1484 | Muse Spark 1.1 |
| LMArena Text: longer queries | 1473 | 1462 | DeepSeek V4.1 Flash |
| LMArena Text: writing and language | 1450 | 1448 | DeepSeek V4.1 Flash |
| LMArena Text: entertainment and media | 1445 | 1438 | DeepSeek V4.1 Flash |
| LMArena Vision: English | 1288 | 1292 | Muse Spark 1.1 |
| LMArena Vision: Chinese | 1327 | 1348 | Muse Spark 1.1 |
| LMArena Vision: reading text | 1282 | 1301 | Muse Spark 1.1 |
| LMArena Vision: humor | 1260 | 1288 | Muse Spark 1.1 |
| LMArena Vision: creative writing | 1275 | 1253 | DeepSeek V4.1 Flash |
| LMArena Document | Not measured | 1465 | Only Muse Spark 1.1 measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4.1 Flash | Muse Spark 1.1 | 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 1.1 |
|---|---|---|
| Maker | DeepSeek | Meta |
| Weights | Open weights | No public weights listed |
| Released | September 10, 2026 | July 16, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.049 | $1.25 |
| Output $/Mtok | $0.525 | $4.25 |
| Coding index | 77.2 | 48.9 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | Not computable | $0.43 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4.1 Flash better than Muse Spark 1.1 for coding?
Pick DeepSeek V4.1 Flash for coding: it scores 77.2 on the Vibe Coding Index against 48.9 for Muse Spark 1.1. Pick Muse Spark 1.1 when what matters is SciCode or LMArena Text: software and IT, where it leads.
Which is cheaper, DeepSeek V4.1 Flash or Muse Spark 1.1?
DeepSeek V4.1 Flash costs $0.049 per million input tokens and $0.525 per million output tokens; Muse Spark 1.1 costs $1.25 and $4.25. Cost per solved task is known for Muse Spark 1.1 only.
Which has the bigger context window, DeepSeek V4.1 Flash or Muse Spark 1.1?
Neither: both take 1.05M tokens.
How many benchmarks is the DeepSeek V4.1 Flash vs Muse Spark 1.1 comparison based on?
72 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 1.1's on 1. Where only one model has a result, the page says so instead of naming a winner.