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Mercury 2 vs Muse Spark 1.3

Muse Spark 1.3 leads Mercury 2 on the Artificial Analysis Intelligence Index, 48.1 to 10.8, and Mercury 2 costs 5.7x less per output token ($0.75 vs $4.25 per million). Updated October 22, 2026; 38 benchmarks have a result for both.

Replace Mercury 2 Replace Muse Spark 1.3
Mercury 2Inception
Coding
No data
Overall
No data
Output $/M
$0.75
0
Muse Spark 1.3Meta
Coding
57.4
Overall
68.6
Output $/M
$4.25
38
vs boards won of 38 shared

Mercury 2 or Muse Spark 1.3: which to pick

Only Muse Spark 1.3 has a coding score, 57.4 on the Vibe Coding Index; Mercury 2 has none, so the two cannot be ranked on coding.

Pick Mercury 2 for output tokens 5.7x cheaper ($0.75 vs $4.25 per million).

Model AMercury 2InceptionNot benchmarked1 independent benchmarkNo cost per solved taskModel BMuse Spark 1.3Meta57.4/1004 independent benchmarksNo cost per solved task
Shared results
38
Mercury 2 only
4
Muse Spark 1.3 only
54
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 not benchmarked, Muse Spark 1.3 57.4 from 4 benchmarks.
Widest category
Agentic work, 53.9 points apart on average over 1 shared benchmark.
Widest single gap
LMArena WebDev: React: Mercury 2 1160 against Muse Spark 1.3 1672, 73.4 points apart on a 0 to 100 scale.
Output price
Mercury 2 $0.75 against Muse Spark 1.3 $4.25 per million output tokens, 5.7x apart.
Context window
Mercury 2 takes 128K tokens, Muse Spark 1.3 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 2BarsMuse Spark 1.3Ties
Coding08
Intelligence01
Agentic work01
Reasoning05
Knowledge03
Web design08
General012
All shared boards038
CodingLike-for-likeSix of these boards feed the Vibe Coding Index08
Coding benchmarks for Mercury 2 and Muse Spark 1.3
BenchmarkMercury 2Muse Spark 1.3Leader
LiveBench codingNot measured90.2%Only Muse Spark 1.3 measured
LMArena WebDev11711659Muse Spark 1.3
AA Coding Index31.175.8Muse Spark 1.3
Terminal-Bench 4 (Vals AI)Not measured10.6%Only Muse Spark 1.3 measured
Vibe Code Bench (Vals AI)Not measured82.9%Only Muse Spark 1.3 measured
Code migration (Vals AI)Not measured27.6%Only Muse Spark 1.3 measured
ProgramBench (Vals AI)Not measured0.5%Only Muse Spark 1.3 measured
IOI (Vals AI)Not measured43.9%Only Muse Spark 1.3 measured
Terminal-Bench 2.1 (Vals AI)Not measured72.3%Only Muse Spark 1.3 measured
CyberBench (Vals AI)Not measured69.4%Only Muse Spark 1.3 measured
SciCode37.7%59.7%Muse Spark 1.3
Terminal-Bench Hard (Artificial Analysis run)26.5%Not measuredOnly Mercury 2 measured
FrontierSWENot measured25.8%Only Muse Spark 1.3 measured
WeirdML43.2%Not measuredOnly Mercury 2 measured
ALE-Bench785.61688.3Muse Spark 1.3
LMArena Text: coding13901510Muse Spark 1.3
LMArena Text: software and IT13851511Muse Spark 1.3
LMArena WebDev: React11601672Muse Spark 1.3
LMArena WebDev: HTML11991653Muse Spark 1.3
LMArena WebDev: from an imageNot measured1640Only Muse Spark 1.3 measured
Neither model has a result on the other 19 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Mercury 2 and Muse Spark 1.3
BenchmarkMercury 2Muse Spark 1.3Leader
AA Intelligence Index10.848.1Muse Spark 1.3
Epoch Capabilities IndexNot measured157.2Only Muse Spark 1.3 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Mercury 2 and Muse Spark 1.3
BenchmarkMercury 2Muse Spark 1.3Leader
AA Agentic Index1.655.5Muse Spark 1.3
Design Arena: agents building web appsNot measured1297Only Muse Spark 1.3 measured
Design Arena: agents building full-stack appsNot measured1295Only Muse Spark 1.3 measured
Design Arena: agents building mobile appsNot measured1218Only Muse Spark 1.3 measured
Design Arena: agents building Godot gamesNot measured1241Only Muse Spark 1.3 measured
Design Arena: PowerPoint slidesNot measured1219Only Muse Spark 1.3 measured
Design Arena: spreadsheetsNot measured1062Only Muse Spark 1.3 measured
LiveBench researchNot measured68.6%Only Muse Spark 1.3 measured
LiveBench browserNot measured80.0%Only Muse Spark 1.3 measured
LiveBench long agenticNot measured40.4%Only Muse Spark 1.3 measured
Finance Agent (Vals AI)Not measured58.9%Only Muse Spark 1.3 measured
Tax Agent Bench (Vals AI)Not measured36.0%Only Muse Spark 1.3 measured
Legal Research Bench (Vals AI)Not measured40.9%Only Muse Spark 1.3 measured
Excel Modeling Benchmark (Vals AI)Not measured62.7%Only Muse Spark 1.3 measured
Terminal-Bench-Science (Vals AI)Not measured4.3%Only Muse Spark 1.3 measured
τ²-Bench Telecom70.8%Not measuredOnly Mercury 2 measured
APEX-AgentsNot measured58.6%Only Muse Spark 1.3 measured
Neither model has a result on the other 24 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for Mercury 2 and Muse Spark 1.3
BenchmarkMercury 2Muse Spark 1.3Leader
LiveBench reasoningNot measured89.7%Only Muse Spark 1.3 measured
GPQA Diamond (Artificial Analysis run)77.0%94.1%Muse Spark 1.3
Humanity's Last Exam (Artificial Analysis run)17.1%48.7%Muse Spark 1.3
Chess puzzlesNot measured37.0%Only Muse Spark 1.3 measured
Mystery game puzzlesNot measured25.0%Only Muse Spark 1.3 measured
LMArena Text: hard prompts13621503Muse Spark 1.3
LMArena Text: expert13581519Muse Spark 1.3
LMArena Text: hard prompts in English13741500Muse Spark 1.3
LMArena Vision: diagramsNot measured1330Only Muse Spark 1.3 measured
LMArena Vision: homeworkNot measured1296Only Muse Spark 1.3 measured
Neither model has a result on the other 12 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Math benchmarks for Mercury 2 and Muse Spark 1.3
BenchmarkMercury 2Muse Spark 1.3Leader
OTIS Mock AIMENot measured99.2%Only Muse Spark 1.3 measured
FrontierMath, tiers 1 to 3Not measured74.4%Only Muse Spark 1.3 measured
FrontierMath, tier 4Not measured46.3%Only Muse Spark 1.3 measured
ProofBenchNot measured58.0%Only Muse Spark 1.3 measured
LMArena Text: mathNot measured1497Only Muse Spark 1.3 measured
LMArena Text: mathematical workNot measured1491Only Muse Spark 1.3 measured
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index03
Knowledge benchmarks for Mercury 2 and Muse Spark 1.3
BenchmarkMercury 2Muse Spark 1.3Leader
LMArena Text: science13431507Muse Spark 1.3
LMArena Text: medicine and healthcare13631493Muse Spark 1.3
LMArena Text: legal and governmentNot measured1499Only Muse Spark 1.3 measured
LMArena Text: business and finance13491490Muse Spark 1.3
Neither model has a result on the other 14 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index08
Web design benchmarks for Mercury 2 and Muse Spark 1.3
BenchmarkMercury 2Muse Spark 1.3Leader
Design Arena: websites10361356Muse Spark 1.3
Design Arena: UI components9961349Muse Spark 1.3
Design Arena: game dev9841328Muse Spark 1.3
Design Arena: data viz10091343Muse Spark 1.3
Design Arena: 3D9821358Muse Spark 1.3
Design Arena: all code categories10211352Muse Spark 1.3
Design Arena: SVG9981301Muse Spark 1.3
Design Arena: ASCII art9881278Muse Spark 1.3
LiveBench designNot measured74.8%Only Muse Spark 1.3 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index012
General benchmarks for Mercury 2 and Muse Spark 1.3
BenchmarkMercury 2Muse Spark 1.3Leader
LiveBench data analysisNot measured79.6%Only Muse Spark 1.3 measured
IFBench69.8%Not measuredOnly Mercury 2 measured
Long context reasoning (AA-LCR)43.7%83.0%Muse Spark 1.3
DTBenchNot measured96.5%Only Muse Spark 1.3 measured
LMCANot measured53.9%Only Muse Spark 1.3 measured
LMArena Text13541490Muse Spark 1.3
LMArena Text: instruction following13281479Muse Spark 1.3
LMArena Text: creative writing12861462Muse Spark 1.3
LMArena VisionNot measured1308Only Muse Spark 1.3 measured
LMArena Text: English13781495Muse Spark 1.3
LMArena Text: non-English13301481Muse Spark 1.3
LMArena Text: Chinese14141532Muse Spark 1.3
LMArena Text: GermanNot measured1513Only Muse Spark 1.3 measured
LMArena Text: JapaneseNot measured1470Only Muse Spark 1.3 measured
LMArena Text: KoreanNot measured1490Only Muse Spark 1.3 measured
LMArena Text: FrenchNot measured1511Only Muse Spark 1.3 measured
LMArena Text: SpanishNot measured1496Only Muse Spark 1.3 measured
LMArena Text: Russian13041491Muse Spark 1.3
LMArena Text: PolishNot measured1490Only Muse Spark 1.3 measured
LMArena Text: multi-turn13571487Muse Spark 1.3
LMArena Text: longer queries13291488Muse Spark 1.3
LMArena Text: writing and language13001470Muse Spark 1.3
LMArena Text: entertainment and media13141457Muse Spark 1.3
LMArena Vision: EnglishNot measured1298Only Muse Spark 1.3 measured
LMArena Vision: ChineseNot measured1384Only Muse Spark 1.3 measured
LMArena Vision: reading textNot measured1319Only Muse Spark 1.3 measured
LMArena Vision: humorNot measured1293Only Muse Spark 1.3 measured
LMArena Vision: creative writingNot measured1296Only Muse Spark 1.3 measured
Neither model has a result on the other 18 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Mercury 2 and Muse Spark 1.3
BenchmarkMercury 2Muse Spark 1.3Leader
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$0.0006Fits in one request
Muse Spark 1.3$0.0034Fits in one request

Mercury 2 costs less

Repository review

50K input + 3K output tokens

Mercury 2$0.015Fits in one request
Muse Spark 1.3$0.075Fits in one request

Mercury 2 costs less

Agent loop

200K input + 10K output tokens

Mercury 2$0.058Exceeds the context window
Muse Spark 1.3$0.292Fits in one request

Mercury 2 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 and Muse Spark 1.3
SpecificationInception Mercury 2Meta Muse Spark 1.3
MakerInceptionMeta
WeightsNo public weights listedNo public weights listed
ReleasedMarch 4, 2026September 2, 2026
Context window128K1.05M
Input $/Mtok$0.25$1.25
Output $/Mtok$0.75$4.25
Coding indexNot benchmarked57.4
Independent measurements behind it14
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Mercury 2 better than Muse Spark 1.3 for coding?

Only Muse Spark 1.3 has a coding score, 57.4 on the Vibe Coding Index; Mercury 2 has none, so the two cannot be ranked on coding. Pick Mercury 2 for output tokens 5.7x cheaper ($0.75 vs $4.25 per million).

Which is cheaper, Mercury 2 or Muse Spark 1.3?

Mercury 2 costs $0.25 per million input tokens and $0.75 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, Mercury 2 or Muse Spark 1.3?

Muse Spark 1.3, with 1.05M tokens against 128K.

How many benchmarks is the Mercury 2 vs Muse Spark 1.3 comparison based on?

38 benchmarks have a result for both models as of October 22, 2026. Mercury 2's coding index rests on 1 independent benchmark and Muse Spark 1.3's on 4. Where only one model has a result, the page says so instead of naming a winner.

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