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Qwen3 30B A3B Instruct 2507 vs Qwen3.7 Plus

Qwen3.7 Plus leads Qwen3 30B A3B Instruct 2507 on the Artificial Analysis Intelligence Index, 25.2 to 7.5, and Qwen3 30B A3B Instruct 2507 costs 4.3x less per output token ($0.30 vs $1.28 per million). Updated October 22, 2026; 40 benchmarks have a result for both.

Replace Qwen3 30B A3B Instruct 2507 Replace Qwen3.7 Plus
Qwen3 30B A3B Instruct 2507Qwen
Coding
No data
Overall
41.5
Output $/M
$0.30
0
Qwen3.7 PlusQwen
Coding
33.2
Overall
54.0
Output $/M
$1.28
40
vs boards won of 40 shared

Qwen3 30B A3B Instruct 2507 or Qwen3.7 Plus: which to pick

Only Qwen3.7 Plus has a coding score, 33.2 on the Vibe Coding Index; Qwen3 30B A3B Instruct 2507 has none, so the two cannot be ranked on coding.

Pick Qwen3 30B A3B Instruct 2507 for output tokens 4.3x cheaper ($0.30 vs $1.28 per million).

Model AQwen3 30B A3B Instruct 2507QwenNot benchmarkedNo coding benchmarkNo cost per solved taskModel BQwen3.7 PlusQwen33.2/1002 independent benchmarksNo cost per solved task
Shared results
40
Qwen3 30B A3B Instruct 2507 only
5
Qwen3.7 Plus only
35
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
Qwen3 30B A3B Instruct 2507 not benchmarked, Qwen3.7 Plus 33.2 from 2 benchmarks.
Widest category
Agentic work, 64.9 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: Qwen3 30B A3B Instruct 2507 28.1% against Qwen3.7 Plus 93.0%, 64.9 points apart on a 0 to 100 scale.
Output price
Qwen3 30B A3B Instruct 2507 $0.30 against Qwen3.7 Plus $1.28 per million output tokens, 4.3x apart.
Context window
Qwen3 30B A3B Instruct 2507 takes 262K tokens, Qwen3.7 Plus 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
CategoryQwen3 30B A3B Instruct 2507BarsQwen3.7 PlusTies
Coding04
Intelligence01
Agentic work01
Reasoning06
Math03
Knowledge04
General021
All shared boards040
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
Coding benchmarks for Qwen3 30B A3B Instruct 2507 and Qwen3.7 Plus
BenchmarkQwen3 30B A3B Instruct 2507Qwen3.7 PlusLeader
AA Coding IndexNot measured55.9Only Qwen3.7 Plus measured
Vibe Code Bench (Vals AI)Not measured46.4%Only Qwen3.7 Plus measured
Code migration (Vals AI)Not measured12.9%Only Qwen3.7 Plus measured
Terminal-Bench 2.1 (Vals AI)Not measured52.8%Only Qwen3.7 Plus measured
SkillsBench (Vals AI)Not measured54.3%Only Qwen3.7 Plus measured
LiveCodeBench (Artificial Analysis run)70.7%Not measuredOnly Qwen3 30B A3B Instruct 2507 measured
SciCode33.0%46.1%Qwen3.7 Plus
Terminal-Bench Hard (Artificial Analysis run)6.1%47.0%Qwen3.7 Plus
FrontierCodeNot measured10.2%Only Qwen3.7 Plus measured
LMArena Text: coding14161473Qwen3.7 Plus
LMArena Text: software and IT14171473Qwen3.7 Plus
Neither model has a result on the other 32 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Qwen3 30B A3B Instruct 2507 and Qwen3.7 Plus
BenchmarkQwen3 30B A3B Instruct 2507Qwen3.7 PlusLeader
AA Intelligence Index7.525.2Qwen3.7 Plus
Epoch Capabilities IndexNot measured147.0Only Qwen3.7 Plus measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Qwen3 30B A3B Instruct 2507 and Qwen3.7 Plus
BenchmarkQwen3 30B A3B Instruct 2507Qwen3.7 PlusLeader
AA Agentic IndexNot measured17.5Only Qwen3.7 Plus measured
Finance Agent (Vals AI)Not measured38.2%Only Qwen3.7 Plus measured
Tax Agent Bench (Vals AI)Not measured10.5%Only Qwen3.7 Plus measured
Legal Research Bench (Vals AI)Not measured16.4%Only Qwen3.7 Plus measured
Excel Modeling Benchmark (Vals AI)Not measured49.3%Only Qwen3.7 Plus measured
τ²-Bench Telecom28.1%93.0%Qwen3.7 Plus
OSWorld 2.0Not measured2.8%Only Qwen3.7 Plus measured
Berkeley Function Calling Leaderboard (BFCL)41.4%Not measuredOnly Qwen3 30B A3B Instruct 2507 measured
Neither model has a result on the other 34 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
Reasoning benchmarks for Qwen3 30B A3B Instruct 2507 and Qwen3.7 Plus
BenchmarkQwen3 30B A3B Instruct 2507Qwen3.7 PlusLeader
GPQA Diamond (Artificial Analysis run)70.7%90.0%Qwen3.7 Plus
Humanity's Last Exam (Artificial Analysis run)10.3%35.6%Qwen3.7 Plus
GPQA Diamond (Epoch AI run)55.6%87.9%Qwen3.7 Plus
Mystery game puzzlesNot measured17.0%Only Qwen3.7 Plus measured
LMArena Text: hard prompts13981460Qwen3.7 Plus
LMArena Text: expert13971466Qwen3.7 Plus
LMArena Text: hard prompts in English14061460Qwen3.7 Plus
LMArena Vision: diagramsNot measured1292Only Qwen3.7 Plus measured
LMArena Vision: homeworkNot measured1295Only Qwen3.7 Plus measured
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for Qwen3 30B A3B Instruct 2507 and Qwen3.7 Plus
BenchmarkQwen3 30B A3B Instruct 2507Qwen3.7 PlusLeader
AA Math Index66.3Not measuredOnly Qwen3 30B A3B Instruct 2507 measured
AIME 2025 (Artificial Analysis run)66.3%Not measuredOnly Qwen3 30B A3B Instruct 2507 measured
OTIS Mock AIME62.2%93.3%Qwen3.7 Plus
FrontierMath, tiers 1 to 3Not measured34.4%Only Qwen3.7 Plus measured
LMArena Text: math13941467Qwen3.7 Plus
LMArena Text: mathematical work14111470Qwen3.7 Plus
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Qwen3 30B A3B Instruct 2507 and Qwen3.7 Plus
BenchmarkQwen3 30B A3B Instruct 2507Qwen3.7 PlusLeader
MortgageTax (Vals AI)Not measured66.2%Only Qwen3.7 Plus measured
MMLU Pro (Artificial Analysis run)80.5%Not measuredOnly Qwen3 30B A3B Instruct 2507 measured
LMArena Text: science13931464Qwen3.7 Plus
LMArena Text: medicine and healthcare13921464Qwen3.7 Plus
LMArena Text: legal and government13871451Qwen3.7 Plus
LMArena Text: business and finance13891435Qwen3.7 Plus
Neither model has a result on the other 14 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Qwen3 30B A3B Instruct 2507 and Qwen3.7 Plus
BenchmarkQwen3 30B A3B Instruct 2507Qwen3.7 PlusLeader
Design Arena: websitesNot measured1269Only Qwen3.7 Plus measured
Design Arena: UI componentsNot measured1258Only Qwen3.7 Plus measured
Design Arena: game devNot measured1262Only Qwen3.7 Plus measured
Design Arena: data vizNot measured1277Only Qwen3.7 Plus measured
Design Arena: 3DNot measured1238Only Qwen3.7 Plus measured
Design Arena: all code categoriesNot measured1268Only Qwen3.7 Plus measured
Design Arena: SVGNot measured1207Only Qwen3.7 Plus measured
Design Arena: ASCII artNot measured1143Only Qwen3.7 Plus measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index021
General benchmarks for Qwen3 30B A3B Instruct 2507 and Qwen3.7 Plus
BenchmarkQwen3 30B A3B Instruct 2507Qwen3.7 PlusLeader
SAGE (Vals AI)Not measured39.3%Only Qwen3.7 Plus measured
Vals Multimodal IndexNot measured53.9%Only Qwen3.7 Plus measured
IFBench50.7%78.0%Qwen3.7 Plus
Long context reasoning (AA-LCR)61.3%73.0%Qwen3.7 Plus
DTBench67.2%84.0%Qwen3.7 Plus
LMCA22.4%37.6%Qwen3.7 Plus
LMArena Text13841454Qwen3.7 Plus
LMArena Text: instruction following13631439Qwen3.7 Plus
LMArena Text: creative writing13171438Qwen3.7 Plus
LMArena VisionNot measured1278Only Qwen3.7 Plus measured
LMArena Text: English13911458Qwen3.7 Plus
LMArena Text: non-English13721445Qwen3.7 Plus
LMArena Text: Chinese14321509Qwen3.7 Plus
LMArena Text: German13791471Qwen3.7 Plus
LMArena Text: Japanese13371412Qwen3.7 Plus
LMArena Text: Korean13301413Qwen3.7 Plus
LMArena Text: French14191472Qwen3.7 Plus
LMArena Text: Spanish14041457Qwen3.7 Plus
LMArena Text: Russian13691457Qwen3.7 Plus
LMArena Text: Polish13531449Qwen3.7 Plus
LMArena Text: multi-turn13781459Qwen3.7 Plus
LMArena Text: longer queries13781454Qwen3.7 Plus
LMArena Text: writing and language13361437Qwen3.7 Plus
LMArena Text: entertainment and media13341422Qwen3.7 Plus
LMArena Vision: EnglishNot measured1280Only Qwen3.7 Plus measured
LMArena Vision: ChineseNot measured1332Only Qwen3.7 Plus measured
LMArena Vision: reading textNot measured1288Only Qwen3.7 Plus measured
LMArena Vision: humorNot measured1261Only Qwen3.7 Plus measured
LMArena Vision: creative writingNot measured1258Only Qwen3.7 Plus measured
LMArena DocumentNot measured1444Only Qwen3.7 Plus 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 Qwen3 30B A3B Instruct 2507 and Qwen3.7 Plus
BenchmarkQwen3 30B A3B Instruct 2507Qwen3.7 PlusLeader
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

Qwen3 30B A3B Instruct 2507$0.0002Fits in one request
Qwen3.7 Plus$0.0010Fits in one request

Qwen3 30B A3B Instruct 2507 costs less

Repository review

50K input + 3K output tokens

Qwen3 30B A3B Instruct 2507$0.0054Fits in one request
Qwen3.7 Plus$0.020Fits in one request

Qwen3 30B A3B Instruct 2507 costs less

Agent loop

200K input + 10K output tokens

Qwen3 30B A3B Instruct 2507$0.021Fits in one request
Qwen3.7 Plus$0.077Fits in one request

Qwen3 30B A3B Instruct 2507 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 Qwen3 30B A3B Instruct 2507 and Qwen3.7 Plus
SpecificationQwen3 30B A3B Instruct 2507Qwen3.7 Plus
MakerQwenQwen
WeightsOpen weightsNo public weights listed
ReleasedJuly 29, 2025June 3, 2026
Context window262K1M
Input $/Mtok$0.09$0.32
Output $/Mtok$0.30$1.28
Coding indexNot benchmarked33.2
Independent measurements behind it02
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Qwen3 30B A3B Instruct 2507 better than Qwen3.7 Plus for coding?

Only Qwen3.7 Plus has a coding score, 33.2 on the Vibe Coding Index; Qwen3 30B A3B Instruct 2507 has none, so the two cannot be ranked on coding. Pick Qwen3 30B A3B Instruct 2507 for output tokens 4.3x cheaper ($0.30 vs $1.28 per million).

Which is cheaper, Qwen3 30B A3B Instruct 2507 or Qwen3.7 Plus?

Qwen3 30B A3B Instruct 2507 costs $0.09 per million input tokens and $0.30 per million output tokens; Qwen3.7 Plus costs $0.32 and $1.28. Cost per solved task is known for neither of them.

Which has the bigger context window, Qwen3 30B A3B Instruct 2507 or Qwen3.7 Plus?

Qwen3.7 Plus, with 1M tokens against 262K.

How many benchmarks is the Qwen3 30B A3B Instruct 2507 vs Qwen3.7 Plus comparison based on?

40 benchmarks have a result for both models as of October 22, 2026. Qwen3 30B A3B Instruct 2507's coding index rests on 0 independent benchmarks and Qwen3.7 Plus's on 2. Where only one model has a result, the page says so instead of naming a winner.

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