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Mercury 2.5 vs Qwen3 Coder 480B A35B

Mercury 2.5 leads Qwen3 Coder 480B A35B on the Artificial Analysis Intelligence Index, 12.3 to 11.9, and Mercury 2.5 costs 10.0x less per output token ($0.15 vs $1.50 per million). Updated October 21, 2026; 4 benchmarks have a result for both.

Mercury 2.5Inception
Coding
1.6
Overall
12.3
Output $/M
$0.15
3
Qwen3 Coder 480B A35BQwen
Coding
No data
Overall
11.9
Output $/M
$1.50
1
vs boards won of 4 shared

Mercury 2.5 or Qwen3 Coder 480B A35B: which to pick

Only Mercury 2.5 has a coding score, 1.6 on the Vibe Coding Index; Qwen3 Coder 480B A35B has none, so the two cannot be ranked on coding.

Pick Qwen3 Coder 480B A35B for a larger context window (262K against 260K tokens) and work measured by ALE-Bench, where it leads.

Shared results
4
Mercury 2.5 only
18
Qwen3 Coder 480B A35B only
48
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.

At a glance

Coding index
Mercury 2.5 1.6 from 2 benchmarks, Qwen3 Coder 480B A35B not benchmarked.
Widest category
General, 26.0 points apart on average over 1 shared benchmark.
Widest single gap
Long context reasoning (AA-LCR): Mercury 2.5 71.7% against Qwen3 Coder 480B A35B 45.7%, 26.0 points apart on a 0 to 100 scale.
Output price
Mercury 2.5 $0.15 against Qwen3 Coder 480B A35B $1.50 per million output tokens, 10.0x apart.
Context window
Mercury 2.5 takes 260K tokens, Qwen3 Coder 480B A35B 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.

Boards won, where both have a result
CategoryMercury 2.5BarsQwen3 Coder 480B A35BTies
Coding01
Intelligence10
Reasoning10
General10
All shared boards31
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
Coding benchmarks for Mercury 2.5 and Qwen3 Coder 480B A35B
BenchmarkMercury 2.5Qwen3 Coder 480B A35BLeader
SWE-bench VerifiedNot measured69.6%Only Qwen3 Coder 480B A35B measured
LMArena WebDevNot measured1275Only Qwen3 Coder 480B A35B measured
Terminal-Bench 4 (Vals AI)0.0%Not measuredOnly Mercury 2.5 measured
Vibe Code Bench (Vals AI)3.7%Not measuredOnly Mercury 2.5 measured
Code migration (Vals AI)4.5%Not measuredOnly Mercury 2.5 measured
IOI (Vals AI)2.4%Not measuredOnly Mercury 2.5 measured
Terminal-Bench 2.1 (Vals AI)34.5%Not measuredOnly Mercury 2.5 measured
SkillsBench (Vals AI)18.1%Not measuredOnly Mercury 2.5 measured
CyberBench (Vals AI)45.5%Not measuredOnly Mercury 2.5 measured
LiveCodeBench (Artificial Analysis run)Not measured58.5%Only Qwen3 Coder 480B A35B measured
SciCode38.5%Not measuredOnly Mercury 2.5 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured18.9%Only Qwen3 Coder 480B A35B measured
Terminal-BenchNot measured27.2%Only Qwen3 Coder 480B A35B measured
GSO-BenchNot measured4.9%Only Qwen3 Coder 480B A35B measured
WeirdMLNot measured41.2%Only Qwen3 Coder 480B A35B measured
ALE-Bench301.6461.4Qwen3 Coder 480B A35B
LMArena Text: codingNot measured1412Only Qwen3 Coder 480B A35B measured
LMArena Text: software and ITNot measured1393Only Qwen3 Coder 480B A35B measured
LMArena WebDev: ReactNot measured1257Only Qwen3 Coder 480B A35B measured
LMArena WebDev: HTMLNot measured1287Only Qwen3 Coder 480B A35B measured
Neither model has a result on the other 18 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Mercury 2.5 and Qwen3 Coder 480B A35B
BenchmarkMercury 2.5Qwen3 Coder 480B A35BLeader
AA Intelligence Index12.311.9Mercury 2.5
Neither model has a result on the other 1 board here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Agentic work benchmarks for Mercury 2.5 and Qwen3 Coder 480B A35B
BenchmarkMercury 2.5Qwen3 Coder 480B A35BLeader
Finance Agent (Vals AI)18.9%Not measuredOnly Mercury 2.5 measured
Tax Agent Bench (Vals AI)2.5%Not measuredOnly Mercury 2.5 measured
Legal Research Bench (Vals AI)4.3%Not measuredOnly Mercury 2.5 measured
Excel Modeling Benchmark (Vals AI)8.8%Not measuredOnly Mercury 2.5 measured
Terminal-Bench-Science (Vals AI)0.0%Not measuredOnly Mercury 2.5 measured
τ²-Bench TelecomNot measured43.6%Only Qwen3 Coder 480B A35B measured
Neither model has a result on the other 33 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
Reasoning benchmarks for Mercury 2.5 and Qwen3 Coder 480B A35B
BenchmarkMercury 2.5Qwen3 Coder 480B A35BLeader
GPQA Diamond (Artificial Analysis run)Not measured61.8%Only Qwen3 Coder 480B A35B measured
Humanity's Last Exam (Artificial Analysis run)11.8%4.5%Mercury 2.5
LMArena Text: hard promptsNot measured1372Only Qwen3 Coder 480B A35B measured
LMArena Text: expertNot measured1338Only Qwen3 Coder 480B A35B measured
LMArena Text: hard prompts in EnglishNot measured1380Only Qwen3 Coder 480B A35B measured
Neither model has a result on the other 16 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Math benchmarks for Mercury 2.5 and Qwen3 Coder 480B A35B
BenchmarkMercury 2.5Qwen3 Coder 480B A35BLeader
AA Math IndexNot measured39.3Only Qwen3 Coder 480B A35B measured
AIME 2025 (Artificial Analysis run)Not measured39.3%Only Qwen3 Coder 480B A35B measured
ProofBench3.0%Not measuredOnly Mercury 2.5 measured
LMArena Text: mathNot measured1365Only Qwen3 Coder 480B A35B measured
LMArena Text: mathematical workNot measured1367Only Qwen3 Coder 480B A35B measured
Neither model has a result on the other 8 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Knowledge benchmarks for Mercury 2.5 and Qwen3 Coder 480B A35B
BenchmarkMercury 2.5Qwen3 Coder 480B A35BLeader
LegalBench (Vals AI)83.1%Not measuredOnly Mercury 2.5 measured
MedCode (Vals AI)31.3%Not measuredOnly Mercury 2.5 measured
MMLU Pro (Artificial Analysis run)Not measured78.8%Only Qwen3 Coder 480B A35B measured
LMArena Text: scienceNot measured1347Only Qwen3 Coder 480B A35B measured
LMArena Text: medicine and healthcareNot measured1347Only Qwen3 Coder 480B A35B measured
LMArena Text: legal and governmentNot measured1358Only Qwen3 Coder 480B A35B measured
LMArena Text: business and financeNot measured1343Only Qwen3 Coder 480B A35B measured
Neither model has a result on the other 10 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Web design benchmarks for Mercury 2.5 and Qwen3 Coder 480B A35B
BenchmarkMercury 2.5Qwen3 Coder 480B A35BLeader
Design Arena: websitesNot measured1159Only Qwen3 Coder 480B A35B measured
Design Arena: UI componentsNot measured1113Only Qwen3 Coder 480B A35B measured
Design Arena: game devNot measured1099Only Qwen3 Coder 480B A35B measured
Design Arena: data vizNot measured1084Only Qwen3 Coder 480B A35B measured
Design Arena: all code categoriesNot measured1143Only Qwen3 Coder 480B A35B measured
Neither model has a result on the other 4 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
General benchmarks for Mercury 2.5 and Qwen3 Coder 480B A35B
BenchmarkMercury 2.5Qwen3 Coder 480B A35BLeader
Public Benefits Bench (Vals AI)45.3%Not measuredOnly Mercury 2.5 measured
MedScribe (Vals AI)55.1%Not measuredOnly Mercury 2.5 measured
IFBenchNot measured40.5%Only Qwen3 Coder 480B A35B measured
Long context reasoning (AA-LCR)71.7%45.7%Mercury 2.5
LMArena TextNot measured1357Only Qwen3 Coder 480B A35B measured
LMArena Text: instruction followingNot measured1355Only Qwen3 Coder 480B A35B measured
LMArena Text: creative writingNot measured1333Only Qwen3 Coder 480B A35B measured
LMArena Text: EnglishNot measured1359Only Qwen3 Coder 480B A35B measured
LMArena Text: non-EnglishNot measured1346Only Qwen3 Coder 480B A35B measured
LMArena Text: ChineseNot measured1357Only Qwen3 Coder 480B A35B measured
LMArena Text: GermanNot measured1325Only Qwen3 Coder 480B A35B measured
LMArena Text: JapaneseNot measured1311Only Qwen3 Coder 480B A35B measured
LMArena Text: KoreanNot measured1305Only Qwen3 Coder 480B A35B measured
LMArena Text: FrenchNot measured1398Only Qwen3 Coder 480B A35B measured
LMArena Text: SpanishNot measured1360Only Qwen3 Coder 480B A35B measured
LMArena Text: RussianNot measured1366Only Qwen3 Coder 480B A35B measured
LMArena Text: PolishNot measured1344Only Qwen3 Coder 480B A35B measured
LMArena Text: multi-turnNot measured1366Only Qwen3 Coder 480B A35B measured
LMArena Text: longer queriesNot measured1378Only Qwen3 Coder 480B A35B measured
LMArena Text: writing and languageNot measured1340Only Qwen3 Coder 480B A35B measured
LMArena Text: entertainment and mediaNot measured1317Only Qwen3 Coder 480B A35B measured
Neither model has a result on the other 25 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 Qwen3 Coder 480B A35B
BenchmarkMercury 2.5Qwen3 Coder 480B A35BLeader
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
Qwen3 Coder 480B A35B$0.0010Fits in one request

Mercury 2.5 costs less

Repository review

50K input + 3K output tokens

Mercury 2.5$0.0024Fits in one request
Qwen3 Coder 480B A35B$0.019Fits in one request

Mercury 2.5 costs less

Agent loop

200K input + 10K output tokens

Mercury 2.5$0.0095Fits in one request
Qwen3 Coder 480B A35B$0.075Fits 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 Qwen3 Coder 480B A35B
SpecificationInception Mercury 2.5Qwen3 Coder 480B A35B
MakerInceptionQwen
WeightsNo public weights listedOpen weights
ReleasedSeptember 8, 2026July 23, 2025
Context window260K262K
Input $/Mtok$0.04$0.30
Output $/Mtok$0.15$1.50
Coding index1.6Not benchmarked
Independent measurements behind it21
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Mercury 2.5 better than Qwen3 Coder 480B A35B for coding?

Only Mercury 2.5 has a coding score, 1.6 on the Vibe Coding Index; Qwen3 Coder 480B A35B has none, so the two cannot be ranked on coding. Pick Qwen3 Coder 480B A35B for a larger context window (262K against 260K tokens) and work measured by ALE-Bench, where it leads.

Which is cheaper, Mercury 2.5 or Qwen3 Coder 480B A35B?

Mercury 2.5 costs $0.04 per million input tokens and $0.15 per million output tokens; Qwen3 Coder 480B A35B costs $0.30 and $1.50. Cost per solved task is known for neither of them.

Which has the bigger context window, Mercury 2.5 or Qwen3 Coder 480B A35B?

Qwen3 Coder 480B A35B, with 262K tokens against 260K.

How many benchmarks is the Mercury 2.5 vs Qwen3 Coder 480B A35B comparison based on?

4 benchmarks have a result for both models as of October 21, 2026. Mercury 2.5's coding index rests on 2 independent benchmarks and Qwen3 Coder 480B A35B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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