Muse Wonder vs Step 3.7 Flash
Step 3.7 Flash costs 17.4x less per output token than Muse Wonder ($1.15 vs $20.00 per million). Updated October 21, 2026; 9 benchmarks have a result for both.
Muse Wonder or Step 3.7 Flash: which to pick
Only Muse Wonder has a coding score, 71.9 on the Vibe Coding Index; Step 3.7 Flash has none, so the two cannot be ranked on coding.
Pick Step 3.7 Flash for output tokens 17.4x cheaper ($1.15 vs $20.00 per million).
- Shared results
- 9
- Muse Wonder only
- 51
- Step 3.7 Flash only
- 9
- Like-for-like categories
- 4 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
No call
Only Muse Wonder has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Step 3.7 Flash has a AA Intelligence Index result, 19.5.
Directional only
Web design
Design Arena: websites
Muse Wonder
Muse Wonder leads, 1362 against 1196.
Same board, both measured
General
Vals Index
No call
Only Muse Wonder has a Vals Index result, 64.9%.
Directional only
Long documents
Listed context window
Muse Wonder
Muse Wonder takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Step 3.7 Flash
Muse Wonder $0.014, Step 3.7 Flash $0.0008 per turn.
List prices
At a glance
- Coding index
- Muse Wonder 71.9 from 3 benchmarks, Step 3.7 Flash not benchmarked.
- Widest category
- Reasoning, 28.7 points apart on average over 1 shared benchmark.
- Widest single gap
- Design Arena: 3D: Muse Wonder 1426 against Step 3.7 Flash 1129, 37.1 points apart on a 0 to 100 scale.
- Output price
- Muse Wonder $20.00 against Step 3.7 Flash $1.15 per million output tokens, 17.4x apart.
- Context window
- Muse Wonder takes 1.05M tokens, Step 3.7 Flash 262K.
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 | Muse Wonder | Bars | Step 3.7 Flash | Ties |
|---|---|---|---|---|
| Coding | 1 | 0 | ||
| Reasoning | 1 | 0 | ||
| Web design | 6 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 9 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
| Benchmark | Muse Wonder | Step 3.7 Flash | Leader |
|---|---|---|---|
| LMArena WebDev | 1652 | Not measured | Only Muse Wonder measured |
| AA Coding Index | Not measured | 39.6 | Only Step 3.7 Flash measured |
| Terminal-Bench 4 (Vals AI) | 49.5% | Not measured | Only Muse Wonder measured |
| Vibe Code Bench (Vals AI) | 83.1% | Not measured | Only Muse Wonder measured |
| Code migration (Vals AI) | 62.5% | Not measured | Only Muse Wonder measured |
| IOI (Vals AI) | 66.9% | Not measured | Only Muse Wonder measured |
| SWE-bench Multimodal (Vals AI) | 45.6% | Not measured | Only Muse Wonder measured |
| Vibe Code Bench 1-100 (Vals AI) | 26.6% | Not measured | Only Muse Wonder measured |
| CyberBench (Vals AI) | 80.4% | Not measured | Only Muse Wonder measured |
| SciCode | 60.3% | 43.9% | Muse Wonder |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 35.6% | Only Step 3.7 Flash measured |
| ALE-Bench | Not measured | 694.1 | Only Step 3.7 Flash measured |
| LMArena Text: coding | 1522 | Not measured | Only Muse Wonder measured |
| LMArena Text: software and IT | 1515 | Not measured | Only Muse Wonder measured |
| LMArena WebDev: React | 1641 | Not measured | Only Muse Wonder measured |
| LMArena WebDev: HTML | 1694 | Not measured | Only Muse Wonder measured |
| Neither model has a result on the other 22 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Muse Wonder | Step 3.7 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 19.5 | Only Step 3.7 Flash measured |
| Epoch Capabilities Index | 161.8 | Not measured | Only Muse Wonder measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | Muse Wonder | Step 3.7 Flash | Leader |
|---|---|---|---|
| Design Arena: spreadsheets | 1227 | Not measured | Only Muse Wonder measured |
| Finance Agent (Vals AI) | 56.6% | Not measured | Only Muse Wonder measured |
| Tax Agent Bench (Vals AI) | 36.3% | Not measured | Only Muse Wonder measured |
| Legal Research Bench (Vals AI) | 50.5% | Not measured | Only Muse Wonder measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 23.8% | Not measured | Only Muse Wonder measured |
| Excel Modeling Benchmark (Vals AI) | 67.1% | Not measured | Only Muse Wonder measured |
| BioMysteryBench (Vals AI) | 67.0% | Not measured | Only Muse Wonder measured |
| Terminal-Bench-Science (Vals AI) | 22.9% | Not measured | Only Muse Wonder measured |
| Vals Science Index | 39.1% | Not measured | Only Muse Wonder measured |
| CUA-bench (Vals AI) | 7.2% | Not measured | Only Muse Wonder measured |
| τ²-Bench Telecom | Not measured | 98.5% | Only Step 3.7 Flash measured |
| Vending-Bench 2 | $9,432 | Not measured | Only Muse Wonder measured |
| Neither model has a result on the other 27 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Muse Wonder | Step 3.7 Flash | Leader |
|---|---|---|---|
| MysteryMechanism (Vals AI) | 27.5% | Not measured | Only Muse Wonder measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 80.9% | Only Step 3.7 Flash measured |
| Humanity's Last Exam (Artificial Analysis run) | 50.1% | 21.4% | Muse Wonder |
| LMArena Text: hard prompts | 1506 | Not measured | Only Muse Wonder measured |
| LMArena Text: expert | 1513 | Not measured | Only Muse Wonder measured |
| LMArena Text: hard prompts in English | 1506 | Not measured | Only Muse Wonder measured |
| Neither model has a result on the other 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Muse Wonder | Step 3.7 Flash | Leader |
|---|---|---|---|
| ProofBench | 84.0% | Not measured | Only Muse Wonder measured |
| LMArena Text: math | 1486 | Not measured | Only Muse Wonder measured |
| LMArena Text: mathematical work | 1514 | Not measured | Only Muse Wonder measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Muse Wonder | Step 3.7 Flash | Leader |
|---|---|---|---|
| LMArena Text: science | 1506 | Not measured | Only Muse Wonder measured |
| LMArena Text: medicine and healthcare | 1512 | Not measured | Only Muse Wonder measured |
| LMArena Text: legal and government | 1505 | Not measured | Only Muse Wonder measured |
| LMArena Text: business and finance | 1483 | Not measured | Only Muse Wonder measured |
| Neither model has a result on the other 13 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | Muse Wonder | Step 3.7 Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1362 | 1196 | Muse Wonder |
| Design Arena: UI components | 1374 | 1179 | Muse Wonder |
| Design Arena: game dev | 1377 | 1158 | Muse Wonder |
| Design Arena: data viz | 1321 | 1172 | Muse Wonder |
| Design Arena: 3D | 1426 | 1129 | Muse Wonder |
| Design Arena: all code categories | 1371 | 1182 | Muse Wonder |
| Design Arena: SVG | Not measured | 1085 | Only Step 3.7 Flash measured |
| Design Arena: ASCII art | Not measured | 1152 | Only Step 3.7 Flash measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Muse Wonder | Step 3.7 Flash | Leader |
|---|---|---|---|
| Vals Index | 64.9% | Not measured | Only Muse Wonder measured |
| Public Benefits Bench (Vals AI) | 70.2% | Not measured | Only Muse Wonder measured |
| IFBench | Not measured | 67.3% | Only Step 3.7 Flash measured |
| Long context reasoning (AA-LCR) | 80.7% | 73.7% | Muse Wonder |
| DTBench | 95.2% | Not measured | Only Muse Wonder measured |
| LMCA | 56.8% | Not measured | Only Muse Wonder measured |
| LMArena Text | 1502 | Not measured | Only Muse Wonder measured |
| LMArena Text: instruction following | 1491 | Not measured | Only Muse Wonder measured |
| LMArena Text: creative writing | 1491 | Not measured | Only Muse Wonder measured |
| LMArena Text: English | 1507 | Not measured | Only Muse Wonder measured |
| LMArena Text: non-English | 1492 | Not measured | Only Muse Wonder measured |
| LMArena Text: Chinese | 1537 | Not measured | Only Muse Wonder measured |
| LMArena Text: French | 1523 | Not measured | Only Muse Wonder measured |
| LMArena Text: Russian | 1522 | Not measured | Only Muse Wonder measured |
| LMArena Text: multi-turn | 1510 | Not measured | Only Muse Wonder measured |
| LMArena Text: longer queries | 1493 | Not measured | Only Muse Wonder measured |
| LMArena Text: writing and language | 1496 | Not measured | Only Muse Wonder measured |
| LMArena Text: entertainment and media | 1482 | Not measured | Only Muse Wonder measured |
| Neither model has a result on the other 28 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Muse Wonder | Step 3.7 Flash | 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
Step 3.7 Flash costs less
Repository review
50K input + 3K output tokens
Step 3.7 Flash costs less
Agent loop
200K input + 10K output tokens
Step 3.7 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 | Meta Muse Wonder | StepFun Step 3.7 Flash |
|---|---|---|
| Maker | Meta | StepFun |
| Weights | No public weights listed | Open weights |
| Released | October 12, 2026 | May 28, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $4.00 | $0.20 |
| Output $/Mtok | $20.00 | $1.15 |
| Coding index | 71.9 | Not benchmarked |
| Independent measurements behind it | 3 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Muse Wonder better than Step 3.7 Flash for coding?
Only Muse Wonder has a coding score, 71.9 on the Vibe Coding Index; Step 3.7 Flash has none, so the two cannot be ranked on coding. Pick Step 3.7 Flash for output tokens 17.4x cheaper ($1.15 vs $20.00 per million).
Which is cheaper, Muse Wonder or Step 3.7 Flash?
Muse Wonder costs $4.00 per million input tokens and $20.00 per million output tokens; Step 3.7 Flash costs $0.20 and $1.15. Cost per solved task is known for neither of them.
Which has the bigger context window, Muse Wonder or Step 3.7 Flash?
Muse Wonder, with 1.05M tokens against 262K.
How many benchmarks is the Muse Wonder vs Step 3.7 Flash comparison based on?
9 benchmarks have a result for both models as of October 21, 2026. Muse Wonder's coding index rests on 3 independent benchmarks and Step 3.7 Flash's on 0. Where only one model has a result, the page says so instead of naming a winner.