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Mercury 2 vs Qwen3.8 Max (0902)

Qwen3.8 Max (0902) leads Mercury 2 on the Artificial Analysis Intelligence Index, 45.4 to 10.8, and Mercury 2 costs 8.0x less per output token ($0.75 vs $6.00 per million). Updated October 22, 2026; 36 benchmarks have a result for both.

Mercury 2Inception
Coding
No data
Overall
No data
Output $/M
$0.75
0
Qwen3.8 Max (0902)Qwen
Coding
62.4
Overall
68.9
Output $/M
$6.00
36
vs boards won of 36 shared

Mercury 2 or Qwen3.8 Max (0902): which to pick

Only Qwen3.8 Max (0902) has a coding score, 62.4 on the Vibe Coding Index; Mercury 2 has none, so the two cannot be ranked on coding.

Pick Mercury 2 for output tokens 8.0x cheaper ($0.75 vs $6.00 per million).

Shared results
36
Mercury 2 only
6
Qwen3.8 Max (0902) only
77
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, Qwen3.8 Max (0902) 62.4 from 5 benchmarks.
Widest category
Agentic work, 54.4 points apart on average over 1 shared benchmark.
Widest single gap
LMArena WebDev: React: Mercury 2 1160 against Qwen3.8 Max (0902) 1692, 73.4 points apart on a 0 to 100 scale.
Output price
Mercury 2 $0.75 against Qwen3.8 Max (0902) $6.00 per million output tokens, 8.0x apart.
Context window
Mercury 2 takes 128K tokens, Qwen3.8 Max (0902) 1M.

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 2BarsQwen3.8 Max (0902)Ties
Coding07
Intelligence01
Agentic work01
Reasoning05
Knowledge03
Web design07
General012
All shared boards036
CodingLike-for-likeSix of these boards feed the Vibe Coding Index07
Coding benchmarks for Mercury 2 and Qwen3.8 Max (0902)
BenchmarkMercury 2Qwen3.8 Max (0902)Leader
LiveBench codingNot measured60.3%Only Qwen3.8 Max (0902) measured
LMArena WebDev11711674Qwen3.8 Max (0902)
AA Coding Index31.176.2Qwen3.8 Max (0902)
LiveCodeBench (Vals AI)Not measured87.8%Only Qwen3.8 Max (0902) measured
SWE-bench Verified (Vals AI)Not measured85.6%Only Qwen3.8 Max (0902) measured
Terminal-Bench 4 (Vals AI)Not measured34.3%Only Qwen3.8 Max (0902) measured
Vibe Code Bench (Vals AI)Not measured64.7%Only Qwen3.8 Max (0902) measured
Code migration (Vals AI)Not measured24.0%Only Qwen3.8 Max (0902) measured
ProgramBench (Vals AI)Not measured0.0%Only Qwen3.8 Max (0902) measured
IOI (Vals AI)Not measured68.9%Only Qwen3.8 Max (0902) measured
Terminal-Bench 2.1 (Vals AI)Not measured67.4%Only Qwen3.8 Max (0902) measured
SWE-bench Multimodal (Vals AI)Not measured42.5%Only Qwen3.8 Max (0902) measured
Vibe Code Bench 1-100 (Vals AI)Not measured12.8%Only Qwen3.8 Max (0902) measured
SkillsBench (Vals AI)Not measured42.0%Only Qwen3.8 Max (0902) measured
CyberBench (Vals AI)Not measured28.6%Only Qwen3.8 Max (0902) measured
SciCode37.7%53.2%Qwen3.8 Max (0902)
Terminal-Bench Hard (Artificial Analysis run)26.5%Not measuredOnly Mercury 2 measured
FrontierSWENot measured17.8%Only Qwen3.8 Max (0902) measured
WeirdML43.2%Not measuredOnly Mercury 2 measured
ALE-Bench785.6Not measuredOnly Mercury 2 measured
LMArena Text: coding13901502Qwen3.8 Max (0902)
LMArena Text: software and IT13851498Qwen3.8 Max (0902)
LMArena WebDev: React11601692Qwen3.8 Max (0902)
LMArena WebDev: HTML11991649Qwen3.8 Max (0902)
LMArena WebDev: from an imageNot measured1637Only Qwen3.8 Max (0902) measured
Neither model has a result on the other 14 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Mercury 2 and Qwen3.8 Max (0902)
BenchmarkMercury 2Qwen3.8 Max (0902)Leader
AA Intelligence Index10.845.4Qwen3.8 Max (0902)
Epoch Capabilities IndexNot measured157.4Only Qwen3.8 Max (0902) measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Mercury 2 and Qwen3.8 Max (0902)
BenchmarkMercury 2Qwen3.8 Max (0902)Leader
AA Agentic Index1.656.0Qwen3.8 Max (0902)
Design Arena: agents building web appsNot measured1300Only Qwen3.8 Max (0902) measured
Design Arena: agents building full-stack appsNot measured1305Only Qwen3.8 Max (0902) measured
Design Arena: agents building mobile appsNot measured1224Only Qwen3.8 Max (0902) measured
Design Arena: agents building Android appsNot measured1196Only Qwen3.8 Max (0902) measured
Design Arena: agents building Godot gamesNot measured1234Only Qwen3.8 Max (0902) measured
Design Arena: PowerPoint slidesNot measured1233Only Qwen3.8 Max (0902) measured
Design Arena: spreadsheetsNot measured967Only Qwen3.8 Max (0902) measured
LiveBench researchNot measured69.9%Only Qwen3.8 Max (0902) measured
LiveBench browserNot measured32.0%Only Qwen3.8 Max (0902) measured
LiveBench long agenticNot measured42.3%Only Qwen3.8 Max (0902) measured
Finance Agent (Vals AI)Not measured50.6%Only Qwen3.8 Max (0902) measured
Tax Agent Bench (Vals AI)Not measured32.1%Only Qwen3.8 Max (0902) measured
Legal Research Bench (Vals AI)Not measured47.6%Only Qwen3.8 Max (0902) measured
Excel Modeling Benchmark (Vals AI)Not measured60.1%Only Qwen3.8 Max (0902) measured
Terminal-Bench-Science (Vals AI)Not measured12.9%Only Qwen3.8 Max (0902) measured
τ²-Bench Telecom70.8%Not measuredOnly Mercury 2 measured
APEX-AgentsNot measured63.3%Only Qwen3.8 Max (0902) measured
LMArena SearchNot measured1261Only Qwen3.8 Max (0902) measured
Neither model has a result on the other 22 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for Mercury 2 and Qwen3.8 Max (0902)
BenchmarkMercury 2Qwen3.8 Max (0902)Leader
GPQA DiamondNot measured93.7%Only Qwen3.8 Max (0902) measured
LiveBench reasoningNot measured88.2%Only Qwen3.8 Max (0902) measured
MysteryMechanism (Vals AI)Not measured23.9%Only Qwen3.8 Max (0902) measured
MMMU Pro (Vals AI)Not measured88.0%Only Qwen3.8 Max (0902) measured
GPQA Diamond (Artificial Analysis run)77.0%92.8%Qwen3.8 Max (0902)
Humanity's Last Exam (Artificial Analysis run)17.1%43.1%Qwen3.8 Max (0902)
GPQA Diamond (Epoch AI run)Not measured92.7%Only Qwen3.8 Max (0902) measured
Chess puzzlesNot measured46.0%Only Qwen3.8 Max (0902) measured
Mystery game puzzlesNot measured38.0%Only Qwen3.8 Max (0902) measured
LMArena Text: hard prompts13621496Qwen3.8 Max (0902)
LMArena Text: expert13581507Qwen3.8 Max (0902)
LMArena Text: hard prompts in English13741503Qwen3.8 Max (0902)
LMArena Vision: diagramsNot measured1323Only Qwen3.8 Max (0902) measured
LMArena Vision: homeworkNot measured1336Only Qwen3.8 Max (0902) measured
Neither model has a result on the other 8 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Math benchmarks for Mercury 2 and Qwen3.8 Max (0902)
BenchmarkMercury 2Qwen3.8 Max (0902)Leader
OTIS Mock AIMENot measured100.0%Only Qwen3.8 Max (0902) measured
FrontierMath, tiers 1 to 3Not measured74.7%Only Qwen3.8 Max (0902) measured
FrontierMath, tier 4Not measured46.3%Only Qwen3.8 Max (0902) measured
ProofBenchNot measured58.0%Only Qwen3.8 Max (0902) measured
LMArena Text: mathNot measured1501Only Qwen3.8 Max (0902) measured
LMArena Text: mathematical workNot measured1491Only Qwen3.8 Max (0902) 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 Qwen3.8 Max (0902)
BenchmarkMercury 2Qwen3.8 Max (0902)Leader
MMLU ProNot measured88.6%Only Qwen3.8 Max (0902) measured
LegalBench (Vals AI)Not measured83.6%Only Qwen3.8 Max (0902) measured
CorpFin (Vals AI)Not measured65.8%Only Qwen3.8 Max (0902) measured
TaxEval (Vals AI)Not measured75.5%Only Qwen3.8 Max (0902) measured
MortgageTax (Vals AI)Not measured64.0%Only Qwen3.8 Max (0902) measured
MedCode (Vals AI)Not measured40.7%Only Qwen3.8 Max (0902) measured
SimpleQA VerifiedNot measured47.3%Only Qwen3.8 Max (0902) measured
LMArena Text: science13431512Qwen3.8 Max (0902)
LMArena Text: medicine and healthcare13631503Qwen3.8 Max (0902)
LMArena Text: legal and governmentNot measured1492Only Qwen3.8 Max (0902) measured
LMArena Text: business and finance13491480Qwen3.8 Max (0902)
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index07
Web design benchmarks for Mercury 2 and Qwen3.8 Max (0902)
BenchmarkMercury 2Qwen3.8 Max (0902)Leader
Design Arena: websites10361275Qwen3.8 Max (0902)
Design Arena: UI components9961338Qwen3.8 Max (0902)
Design Arena: game dev9841312Qwen3.8 Max (0902)
Design Arena: data viz10091281Qwen3.8 Max (0902)
Design Arena: 3D9821336Qwen3.8 Max (0902)
Design Arena: all code categories10211293Qwen3.8 Max (0902)
Design Arena: SVG998Not measuredOnly Mercury 2 measured
Design Arena: ASCII art9881200Qwen3.8 Max (0902)
LiveBench designNot measured78.6%Only Qwen3.8 Max (0902) measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index012
General benchmarks for Mercury 2 and Qwen3.8 Max (0902)
BenchmarkMercury 2Qwen3.8 Max (0902)Leader
LiveBench data analysisNot measured78.4%Only Qwen3.8 Max (0902) measured
Public Benefits Bench (Vals AI)Not measured67.1%Only Qwen3.8 Max (0902) measured
SAGE (Vals AI)Not measured51.2%Only Qwen3.8 Max (0902) measured
MedScribe (Vals AI)Not measured85.0%Only Qwen3.8 Max (0902) measured
Vals Multimodal IndexNot measured65.4%Only Qwen3.8 Max (0902) measured
IFBench69.8%Not measuredOnly Mercury 2 measured
Long context reasoning (AA-LCR)43.7%80.3%Qwen3.8 Max (0902)
DTBenchNot measured92.0%Only Qwen3.8 Max (0902) measured
LMCANot measured46.2%Only Qwen3.8 Max (0902) measured
Furniture assemblyNot measured20.0%Only Qwen3.8 Max (0902) measured
LMArena Text13541483Qwen3.8 Max (0902)
LMArena Text: instruction following13281481Qwen3.8 Max (0902)
LMArena Text: creative writing12861477Qwen3.8 Max (0902)
LMArena VisionNot measured1313Only Qwen3.8 Max (0902) measured
LMArena Text: English13781491Qwen3.8 Max (0902)
LMArena Text: non-English13301473Qwen3.8 Max (0902)
LMArena Text: Chinese14141539Qwen3.8 Max (0902)
LMArena Text: GermanNot measured1478Only Qwen3.8 Max (0902) measured
LMArena Text: JapaneseNot measured1473Only Qwen3.8 Max (0902) measured
LMArena Text: KoreanNot measured1460Only Qwen3.8 Max (0902) measured
LMArena Text: FrenchNot measured1498Only Qwen3.8 Max (0902) measured
LMArena Text: SpanishNot measured1489Only Qwen3.8 Max (0902) measured
LMArena Text: Russian13041482Qwen3.8 Max (0902)
LMArena Text: PolishNot measured1471Only Qwen3.8 Max (0902) measured
LMArena Text: multi-turn13571489Qwen3.8 Max (0902)
LMArena Text: longer queries13291488Qwen3.8 Max (0902)
LMArena Text: writing and language13001477Qwen3.8 Max (0902)
LMArena Text: entertainment and media13141464Qwen3.8 Max (0902)
LMArena Vision: EnglishNot measured1311Only Qwen3.8 Max (0902) measured
LMArena Vision: ChineseNot measured1358Only Qwen3.8 Max (0902) measured
LMArena Vision: reading textNot measured1322Only Qwen3.8 Max (0902) measured
LMArena Vision: humorNot measured1304Only Qwen3.8 Max (0902) measured
LMArena Vision: creative writingNot measured1312Only Qwen3.8 Max (0902) measured
Neither model has a result on the other 13 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Mercury 2 and Qwen3.8 Max (0902)
BenchmarkMercury 2Qwen3.8 Max (0902)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

Mercury 2$0.0006Fits in one request
Qwen3.8 Max (0902)$0.0050Fits in one request

Mercury 2 costs less

Repository review

50K input + 3K output tokens

Mercury 2$0.015Fits in one request
Qwen3.8 Max (0902)$0.118Fits in one request

Mercury 2 costs less

Agent loop

200K input + 10K output tokens

Mercury 2$0.058Exceeds the context window
Qwen3.8 Max (0902)$0.460Fits 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 Qwen3.8 Max (0902)
SpecificationInception Mercury 2Qwen3.8 Max (0902)
MakerInceptionQwen
WeightsNo public weights listedNo public weights listed
ReleasedMarch 4, 2026September 3, 2026
Context window128K1M
Input $/Mtok$0.25$2.00
Output $/Mtok$0.75$6.00
Coding indexNot benchmarked62.4
Independent measurements behind it15
Cost per solved taskNot computable$1.32
SourceOpenRouter listingOpenRouter listing

Questions

Is Mercury 2 better than Qwen3.8 Max (0902) for coding?

Only Qwen3.8 Max (0902) has a coding score, 62.4 on the Vibe Coding Index; Mercury 2 has none, so the two cannot be ranked on coding. Pick Mercury 2 for output tokens 8.0x cheaper ($0.75 vs $6.00 per million).

Which is cheaper, Mercury 2 or Qwen3.8 Max (0902)?

Mercury 2 costs $0.25 per million input tokens and $0.75 per million output tokens; Qwen3.8 Max (0902) costs $2.00 and $6.00. Cost per solved task is known for Qwen3.8 Max (0902) only.

Which has the bigger context window, Mercury 2 or Qwen3.8 Max (0902)?

Qwen3.8 Max (0902), with 1M tokens against 128K.

How many benchmarks is the Mercury 2 vs Qwen3.8 Max (0902) comparison based on?

36 benchmarks have a result for both models as of October 22, 2026. Mercury 2's coding index rests on 1 independent benchmark and Qwen3.8 Max (0902)'s on 5. Where only one model has a result, the page says so instead of naming a winner.

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