DeepSeek V4.1 Flash 1017 vs Muse Ember
DeepSeek V4.1 Flash 1017 leads Muse Ember on coding, 66.9 to 64.9 on the Vibe Coding Index, and Muse Ember costs 1.2x less per output token ($0.50 vs $0.60 per million). Updated November 14, 2026; 15 benchmarks have a result for both.
DeepSeek V4.1 Flash 1017 or Muse Ember: which to pick
Pick DeepSeek V4.1 Flash 1017 for coding: it scores 66.9 on the Vibe Coding Index against 64.9 for Muse Ember.
Pick Muse Ember for output tokens 1.2x cheaper ($0.50 vs $0.60 per million) and work measured by Terminal-Bench 4 (Vals AI) or Terminal-Bench 4.0 (Artificial Analysis run), where it leads.
- Shared results
- 15
- DeepSeek V4.1 Flash 1017 only
- 45
- Muse Ember only
- 0
- Like-for-like categories
- 5 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
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, six public coding benchmarks
DeepSeek V4.1 Flash 1017
DeepSeek V4.1 Flash 1017 scores 66.9 against 64.9.
4 and 3 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only DeepSeek V4.1 Flash 1017 has a AA Intelligence Index result, 28.6.
Directional only
Web design
Design Arena: websites
No call
Only DeepSeek V4.1 Flash 1017 has a Design Arena: websites result, 1294.
Directional only
General
Vals Index
DeepSeek V4.1 Flash 1017
DeepSeek V4.1 Flash 1017 leads, 61.3% against 60.5%.
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
Muse Ember
DeepSeek V4.1 Flash 1017 $0.0004, Muse Ember $0.0003 per turn.
List prices
At a glance
- Coding index
- DeepSeek V4.1 Flash 1017 66.9 from 4 benchmarks, Muse Ember 64.9 from 3 benchmarks.
- Widest category
- Agentic work, 6.6 points apart on average over 4 shared benchmarks.
- Widest single gap
- CritPt v2, hard subset (Artificial Analysis run): DeepSeek V4.1 Flash 1017 27.5% against Muse Ember 39.0%, 11.5 points apart on a 0 to 100 scale.
- Output price
- DeepSeek V4.1 Flash 1017 $0.60 against Muse Ember $0.50 per million output tokens, 1.2x 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 1017 | Bars | Muse Ember | Ties |
|---|---|---|---|---|
| Coding | 5 | 2 | ||
| Agentic work | 2 | 2 | ||
| Reasoning | 1 | 1 | ||
| Knowledge | 0 | 1 | ||
| General | 1 | 0 | ||
| All shared boards | 9 | 6 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index52
| Benchmark | DeepSeek V4.1 Flash 1017 | Muse Ember | Leader |
|---|---|---|---|
| LiveBench coding | 80.4% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| LMArena WebDev | 1664 | 1609 | DeepSeek V4.1 Flash 1017 |
| Terminal-Bench 4 (Vals AI) | 31.8% | 39.4% | Muse Ember |
| Vibe Code Bench (Vals AI) | 87.7% | 83.7% | DeepSeek V4.1 Flash 1017 |
| Code migration (Vals AI) | 44.2% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| SciCode | 55.9% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| Terminal-Bench 4.0 (Artificial Analysis run) | 33.8% | 40.9% | Muse Ember |
| FrontierCode 2.0 | 28.5% | 27.2% | DeepSeek V4.1 Flash 1017 |
| ALE-Bench | 1622.0 | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| LMArena WebDev: React | 1675 | 1616 | DeepSeek V4.1 Flash 1017 |
| LMArena WebDev: HTML | 1696 | 1621 | DeepSeek V4.1 Flash 1017 |
| LMArena WebDev: from an image | 1609 | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| GameBench 2 | 69.9 | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| Terminal-Bench 4.0 | 40.0% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| CursorBench 4.0 | 47.7% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| Neither model has a result on the other 37 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | DeepSeek V4.1 Flash 1017 | Muse Ember | Leader |
|---|---|---|---|
| AA Intelligence Index | 28.6 | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| Epoch Capabilities Index | 159.4 | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index22
| Benchmark | DeepSeek V4.1 Flash 1017 | Muse Ember | Leader |
|---|---|---|---|
| Design Arena: spreadsheets | 1263 | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| LiveBench research | 78.6% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| LiveBench browser | 67.2% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| LiveBench long agentic | 38.8% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| Finance Agent (Vals AI) | 57.0% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| Tax Agent Bench (Vals AI) | 44.4% | 38.2% | DeepSeek V4.1 Flash 1017 |
| Legal Research Bench (Vals AI) | 45.2% | 49.0% | Muse Ember |
| Harvey's Legal Agent Benchmark (Vals AI) | 14.2% | 25.0% | Muse Ember |
| Excel Modeling Benchmark (Vals AI) | 61.8% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| APEX-Agents | 69.8% | 64.3% | DeepSeek V4.1 Flash 1017 |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | DeepSeek V4.1 Flash 1017 | Muse Ember | Leader |
|---|---|---|---|
| LiveBench reasoning | 89.1% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| Humanity's Last Exam (Artificial Analysis run) | 43.3% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| HLE-Diamond (Artificial Analysis run) | 25.3% | 25.1% | DeepSeek V4.1 Flash 1017 |
| CritPt v2, hard subset (Artificial Analysis run) | 27.5% | 39.0% | Muse Ember |
| GPQA Diamond (Epoch AI run) | 93.2% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| ARC-AGI | 94.5% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| ARC-AGI-2 | 78.1% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| Chess puzzles | 46.0% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| Mystery game puzzles | 49.0% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| Humanity's Last Exam (Scale run) | 20.5% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| GoBench | 1633 | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| Neither model has a result on the other 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | DeepSeek V4.1 Flash 1017 | Muse Ember | Leader |
|---|---|---|---|
| OTIS Mock AIME | 99.4% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| FrontierMath, tiers 1 to 3 | 71.2% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| FrontierMath, tier 4 | 46.3% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| MathArena | 46.7% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | DeepSeek V4.1 Flash 1017 | Muse Ember | Leader |
|---|---|---|---|
| AA-Omniscience | 2.1 | 7.7 | Muse Ember |
| SimpleQA Verified | 42.5% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| PRBench Finance | 47.1% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| PRBench Legal | 47.3% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| Neither model has a result on the other 17 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | DeepSeek V4.1 Flash 1017 | Muse Ember | Leader |
|---|---|---|---|
| Design Arena: websites | 1294 | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| Design Arena: UI components | 1283 | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| Design Arena: game dev | 1250 | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| Design Arena: data viz | 1264 | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| Design Arena: 3D | 1342 | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| Design Arena: all code categories | 1286 | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| Design Arena: SVG | 1246 | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| Design Arena: ASCII art | 1231 | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| LiveBench design | 79.8% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | DeepSeek V4.1 Flash 1017 | Muse Ember | Leader |
|---|---|---|---|
| Vals Index | 61.3% | 60.5% | DeepSeek V4.1 Flash 1017 |
| LiveBench data analysis | 79.5% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| Long context reasoning (AA-LCR) | 82.7% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| GDPval-AA | 1746 | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| MultiChallenge | 74.9% | Not measured | Only DeepSeek V4.1 Flash 1017 measured |
| Neither model has a result on the other 44 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | DeepSeek V4.1 Flash 1017 | Muse Ember | 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
Muse Ember costs less
Repository review
50K input + 3K output tokens
Muse Ember costs less
Agent loop
200K input + 10K output tokens
Muse Ember 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 1017 | Meta Muse Ember |
|---|---|---|
| Maker | DeepSeek | Meta |
| Weights | Open weights | No public weights listed |
| Released | October 17, 2026 | November 9, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.15 | $0.10 |
| Output $/Mtok | $0.60 | $0.50 |
| Coding index | 66.9 | 64.9 |
| Independent measurements behind it | 4 | 3 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is DeepSeek V4.1 Flash 1017 better than Muse Ember for coding?
Pick DeepSeek V4.1 Flash 1017 for coding: it scores 66.9 on the Vibe Coding Index against 64.9 for Muse Ember. Pick Muse Ember for output tokens 1.2x cheaper ($0.50 vs $0.60 per million) and work measured by Terminal-Bench 4 (Vals AI) or Terminal-Bench 4.0 (Artificial Analysis run), where it leads.
Which is cheaper, DeepSeek V4.1 Flash 1017 or Muse Ember?
DeepSeek V4.1 Flash 1017 costs $0.15 per million input tokens and $0.60 per million output tokens; Muse Ember costs $0.10 and $0.50. Cost per solved task is known for neither of them.
Which has the bigger context window, DeepSeek V4.1 Flash 1017 or Muse Ember?
Neither: both take 1.05M tokens.
How many benchmarks is the DeepSeek V4.1 Flash 1017 vs Muse Ember comparison based on?
15 benchmarks have a result for both models as of November 14, 2026. DeepSeek V4.1 Flash 1017's coding index rests on 4 independent benchmarks and Muse Ember's on 3. Where only one model has a result, the page says so instead of naming a winner.