Enter opens the highlighted result. Esc closes.

Mercury 2.5 vs Muse Spark 1.1

Muse Spark 1.1 leads Mercury 2.5 on coding, 70.3 to 1.6 on the Vibe Coding Index, and Mercury 2.5 costs 28.3x less per output token ($0.15 vs $4.25 per million). Updated October 22, 2026; 15 benchmarks have a result for both.

Mercury 2.5Inception
Coding
1.6
Overall
No data
Output $/M
$0.15
0
Muse Spark 1.1Meta
Coding
70.3
Overall
67.0
Output $/M
$4.25
15
vs boards won of 15 shared

Mercury 2.5 or Muse Spark 1.1: which to pick

Pick Muse Spark 1.1 for coding: it scores 70.3 on the Vibe Coding Index against 1.6 for Mercury 2.5.

Pick Mercury 2.5 for output tokens 28.3x cheaper ($0.15 vs $4.25 per million).

Shared results
15
Mercury 2.5 only
7
Muse Spark 1.1 only
89
Like-for-like categories
7 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.

At a glance

Coding index
Mercury 2.5 1.6 from 2 benchmarks, Muse Spark 1.1 70.3 from 3 benchmarks.
Widest category
Agentic work, 39.8 points apart on average over 3 shared benchmarks.
Widest single gap
Vibe Code Bench (Vals AI): Mercury 2.5 3.7% against Muse Spark 1.1 72.2%, 68.5 points apart on a 0 to 100 scale.
Output price
Mercury 2.5 $0.15 against Muse Spark 1.1 $4.25 per million output tokens, 28.3x apart.
Context window
Mercury 2.5 takes 260K tokens, Muse Spark 1.1 1.05M.

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.

Boards won, where both have a result
CategoryMercury 2.5BarsMuse Spark 1.1Ties
Coding05
Intelligence01
Agentic work03
Reasoning01
Math01
Knowledge01
General03
All shared boards015
CodingLike-for-likeSix of these boards feed the Vibe Coding Index05
Coding benchmarks for Mercury 2.5 and Muse Spark 1.1
BenchmarkMercury 2.5Muse Spark 1.1Leader
LMArena WebDevNot measured1542Only Muse Spark 1.1 measured
AA Coding IndexNot measured71.3Only Muse Spark 1.1 measured
LiveCodeBench (Vals AI)Not measured85.9%Only Muse Spark 1.1 measured
SWE-bench Verified (Vals AI)Not measured82.0%Only Muse Spark 1.1 measured
Terminal-Bench 4 (Vals AI)0.0%Not measuredOnly Mercury 2.5 measured
Vibe Code Bench (Vals AI)3.7%72.2%Muse Spark 1.1
Code migration (Vals AI)4.5%31.1%Muse Spark 1.1
ProgramBench (Vals AI)Not measured0.0%Only Muse Spark 1.1 measured
IOI (Vals AI)2.4%Not measuredOnly Mercury 2.5 measured
Terminal-Bench 2.1 (Vals AI)34.5%69.3%Muse Spark 1.1
SkillsBench (Vals AI)18.1%59.2%Muse Spark 1.1
CyberBench (Vals AI)45.5%Not measuredOnly Mercury 2.5 measured
SciCode38.5%58.8%Muse Spark 1.1
ALE-Bench301.6Not measuredOnly Mercury 2.5 measured
LMArena Text: codingNot measured1498Only Muse Spark 1.1 measured
LMArena Text: software and ITNot measured1498Only Muse Spark 1.1 measured
LMArena WebDev: ReactNot measured1532Only Muse Spark 1.1 measured
LMArena WebDev: HTMLNot measured1540Only Muse Spark 1.1 measured
LMArena WebDev: from an imageNot measured1540Only Muse Spark 1.1 measured
SWE Atlas: Codebase QnANot measured42.2%Only Muse Spark 1.1 measured
SWE Atlas: Test WritingNot measured41.5%Only Muse Spark 1.1 measured
Neither model has a result on the other 22 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Mercury 2.5 and Muse Spark 1.1
BenchmarkMercury 2.5Muse Spark 1.1Leader
AA Intelligence Index12.333.7Muse Spark 1.1
Epoch Capabilities IndexNot measured154.1Only Muse Spark 1.1 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index03
Agentic work benchmarks for Mercury 2.5 and Muse Spark 1.1
BenchmarkMercury 2.5Muse Spark 1.1Leader
AA Agentic IndexNot measured25.8Only Muse Spark 1.1 measured
Design Arena: agents building web appsNot measured1207Only Muse Spark 1.1 measured
Design Arena: agents building full-stack appsNot measured1199Only Muse Spark 1.1 measured
Design Arena: agents building mobile appsNot measured1175Only Muse Spark 1.1 measured
Design Arena: agents building Android appsNot measured1178Only Muse Spark 1.1 measured
Design Arena: agents building Godot gamesNot measured1103Only Muse Spark 1.1 measured
Design Arena: agents building gamesNot measured1183Only Muse Spark 1.1 measured
Design Arena: HTML slidesNot measured1145Only Muse Spark 1.1 measured
Design Arena: PowerPoint slidesNot measured1134Only Muse Spark 1.1 measured
Design Arena: spreadsheetsNot measured1021Only Muse Spark 1.1 measured
Finance Agent (Vals AI)18.9%57.2%Muse Spark 1.1
Tax Agent Bench (Vals AI)2.5%Not measuredOnly Mercury 2.5 measured
Legal Research Bench (Vals AI)4.3%38.0%Muse Spark 1.1
Excel Modeling Benchmark (Vals AI)8.8%56.4%Muse Spark 1.1
Terminal-Bench-Science (Vals AI)0.0%Not measuredOnly Mercury 2.5 measured
Time Horizon Index (Vals AI)Not measured1.7%Only Muse Spark 1.1 measured
APEX-AgentsNot measured31.8%Only Muse Spark 1.1 measured
Vending-Bench 2Not measured$6,520Only Muse Spark 1.1 measured
MCP AtlasNot measured88.1%Only Muse Spark 1.1 measured
Neither model has a result on the other 23 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
Reasoning benchmarks for Mercury 2.5 and Muse Spark 1.1
BenchmarkMercury 2.5Muse Spark 1.1Leader
GPQA DiamondNot measured91.2%Only Muse Spark 1.1 measured
MMMU Pro (Vals AI)Not measured86.6%Only Muse Spark 1.1 measured
GPQA Diamond (Artificial Analysis run)Not measured89.8%Only Muse Spark 1.1 measured
Humanity's Last Exam (Artificial Analysis run)11.8%46.2%Muse Spark 1.1
Chess puzzlesNot measured34.0%Only Muse Spark 1.1 measured
LMArena Text: hard promptsNot measured1485Only Muse Spark 1.1 measured
LMArena Text: expertNot measured1478Only Muse Spark 1.1 measured
LMArena Text: hard prompts in EnglishNot measured1480Only Muse Spark 1.1 measured
LMArena Vision: diagramsNot measured1305Only Muse Spark 1.1 measured
LMArena Vision: homeworkNot measured1287Only Muse Spark 1.1 measured
Neither model has a result on the other 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index01
Math benchmarks for Mercury 2.5 and Muse Spark 1.1
BenchmarkMercury 2.5Muse Spark 1.1Leader
ProofBench3.0%39.0%Muse Spark 1.1
LMArena Text: mathNot measured1482Only Muse Spark 1.1 measured
LMArena Text: mathematical workNot measured1487Only Muse Spark 1.1 measured
MathArenaNot measured42.5%Only Muse Spark 1.1 measured
Neither model has a result on the other 10 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
Knowledge benchmarks for Mercury 2.5 and Muse Spark 1.1
BenchmarkMercury 2.5Muse Spark 1.1Leader
MMLU ProNot measured88.7%Only Muse Spark 1.1 measured
LegalBench (Vals AI)83.1%85.0%Muse Spark 1.1
CorpFin (Vals AI)Not measured71.3%Only Muse Spark 1.1 measured
TaxEval (Vals AI)Not measured79.7%Only Muse Spark 1.1 measured
MortgageTax (Vals AI)Not measured66.1%Only Muse Spark 1.1 measured
MedCode (Vals AI)31.3%Not measuredOnly Mercury 2.5 measured
SimpleQA VerifiedNot measured57.8%Only Muse Spark 1.1 measured
LMArena Text: scienceNot measured1484Only Muse Spark 1.1 measured
LMArena Text: medicine and healthcareNot measured1479Only Muse Spark 1.1 measured
LMArena Text: legal and governmentNot measured1481Only Muse Spark 1.1 measured
LMArena Text: business and financeNot measured1470Only Muse Spark 1.1 measured
PRBench FinanceNot measured55.0%Only Muse Spark 1.1 measured
PRBench LegalNot measured57.0%Only Muse Spark 1.1 measured
Neither model has a result on the other 7 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Mercury 2.5 and Muse Spark 1.1
BenchmarkMercury 2.5Muse Spark 1.1Leader
Design Arena: websitesNot measured1270Only Muse Spark 1.1 measured
Design Arena: UI componentsNot measured1287Only Muse Spark 1.1 measured
Design Arena: game devNot measured1269Only Muse Spark 1.1 measured
Design Arena: data vizNot measured1267Only Muse Spark 1.1 measured
Design Arena: 3DNot measured1259Only Muse Spark 1.1 measured
Design Arena: all code categoriesNot measured1276Only Muse Spark 1.1 measured
Design Arena: SVGNot measured1234Only Muse Spark 1.1 measured
Design Arena: ASCII artNot measured1269Only Muse Spark 1.1 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index03
General benchmarks for Mercury 2.5 and Muse Spark 1.1
BenchmarkMercury 2.5Muse Spark 1.1Leader
Public Benefits Bench (Vals AI)45.3%61.3%Muse Spark 1.1
SAGE (Vals AI)Not measured45.6%Only Muse Spark 1.1 measured
MedScribe (Vals AI)55.1%88.9%Muse Spark 1.1
Vals Multimodal IndexNot measured66.7%Only Muse Spark 1.1 measured
Long context reasoning (AA-LCR)71.7%77.7%Muse Spark 1.1
DTBenchNot measured94.4%Only Muse Spark 1.1 measured
LMCANot measured49.9%Only Muse Spark 1.1 measured
Surface Evolver BenchNot measured52.5%Only Muse Spark 1.1 measured
LMArena TextNot measured1478Only Muse Spark 1.1 measured
LMArena Text: instruction followingNot measured1457Only Muse Spark 1.1 measured
LMArena Text: creative writingNot measured1435Only Muse Spark 1.1 measured
LMArena VisionNot measured1293Only Muse Spark 1.1 measured
LMArena Text: EnglishNot measured1478Only Muse Spark 1.1 measured
LMArena Text: non-EnglishNot measured1471Only Muse Spark 1.1 measured
LMArena Text: ChineseNot measured1515Only Muse Spark 1.1 measured
LMArena Text: GermanNot measured1469Only Muse Spark 1.1 measured
LMArena Text: JapaneseNot measured1450Only Muse Spark 1.1 measured
LMArena Text: KoreanNot measured1459Only Muse Spark 1.1 measured
LMArena Text: FrenchNot measured1492Only Muse Spark 1.1 measured
LMArena Text: SpanishNot measured1464Only Muse Spark 1.1 measured
LMArena Text: RussianNot measured1482Only Muse Spark 1.1 measured
LMArena Text: PolishNot measured1499Only Muse Spark 1.1 measured
LMArena Text: multi-turnNot measured1484Only Muse Spark 1.1 measured
LMArena Text: longer queriesNot measured1462Only Muse Spark 1.1 measured
LMArena Text: writing and languageNot measured1448Only Muse Spark 1.1 measured
LMArena Text: entertainment and mediaNot measured1438Only Muse Spark 1.1 measured
LMArena Vision: EnglishNot measured1292Only Muse Spark 1.1 measured
LMArena Vision: ChineseNot measured1348Only Muse Spark 1.1 measured
LMArena Vision: reading textNot measured1301Only Muse Spark 1.1 measured
LMArena Vision: humorNot measured1288Only Muse Spark 1.1 measured
LMArena Vision: creative writingNot measured1253Only Muse Spark 1.1 measured
LMArena DocumentNot measured1465Only Muse Spark 1.1 measured
MultiChallengeNot measured75.3%Only Muse Spark 1.1 measured
EQ-Bench 4Not measured1260Only Muse Spark 1.1 measured
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
Image generation benchmarks for Mercury 2.5 and Muse Spark 1.1
BenchmarkMercury 2.5Muse Spark 1.1Leader
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

Mercury 2.5$0.0001Fits in one request
Muse Spark 1.1$0.0034Fits in one request

Mercury 2.5 costs less

Repository review

50K input + 3K output tokens

Mercury 2.5$0.0024Fits in one request
Muse Spark 1.1$0.075Fits in one request

Mercury 2.5 costs less

Agent loop

200K input + 10K output tokens

Mercury 2.5$0.0095Fits in one request
Muse Spark 1.1$0.292Fits in one request

Mercury 2.5 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.

Specifications of Mercury 2.5 and Muse Spark 1.1
SpecificationInception Mercury 2.5Meta Muse Spark 1.1
MakerInceptionMeta
WeightsNo public weights listedNo public weights listed
ReleasedSeptember 8, 2026July 16, 2026
Context window260K1.05M
Input $/Mtok$0.04$1.25
Output $/Mtok$0.15$4.25
Coding index1.670.3
Independent measurements behind it23
Cost per solved taskNot computable$0.43
SourceOpenRouter listingOpenRouter listing

Questions

Is Mercury 2.5 better than Muse Spark 1.1 for coding?

Pick Muse Spark 1.1 for coding: it scores 70.3 on the Vibe Coding Index against 1.6 for Mercury 2.5. Pick Mercury 2.5 for output tokens 28.3x cheaper ($0.15 vs $4.25 per million).

Which is cheaper, Mercury 2.5 or Muse Spark 1.1?

Mercury 2.5 costs $0.04 per million input tokens and $0.15 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, Mercury 2.5 or Muse Spark 1.1?

Muse Spark 1.1, with 1.05M tokens against 260K.

How many benchmarks is the Mercury 2.5 vs Muse Spark 1.1 comparison based on?

15 benchmarks have a result for both models as of October 22, 2026. Mercury 2.5's coding index rests on 2 independent benchmarks and Muse Spark 1.1's on 3. Where only one model has a result, the page says so instead of naming a winner.

Compare next

Embed this comparison on your site

Free under CC BY 4.0, while the source link stays visible. Preview the frame · Terms and other embeds

<iframe src="https://llmbenchmark.ai/embed/compare/inception-mercury-2-5-vs-meta-muse-spark-1-1" title="Mercury 2.5 vs Muse Spark 1.1, LLMBenchmark.ai" width="100%" height="360" style="border:0;max-width:100%" loading="lazy"></iframe>
<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/inception-mercury-2-5-vs-meta-muse-spark-1-1">LLMBenchmark.ai, Mercury 2.5 vs Muse Spark 1.1</a></p>