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Qwen2.5 VL 72B Instruct vs Qwen3.5 397B A17B

Qwen2.5 VL 72B Instruct costs 2.3x less per output token than Qwen3.5 397B A17B ($1.00 vs $2.34 per million). Updated October 23, 2026; 3 benchmarks have a result for both.

Qwen2.5 VL 72B InstructQwen
Coding
No data
Overall
No data
Output $/M
$1.00
0
Qwen3.5 397B A17BQwen
Coding
No data
Overall
57.2
Output $/M
$2.34
3
vs boards won of 3 shared

Qwen2.5 VL 72B Instruct or Qwen3.5 397B A17B: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick Qwen2.5 VL 72B Instruct for output tokens 2.3x cheaper ($1.00 vs $2.34 per million) and work measured by LMArena Vision or LMArena Vision: English, where it leads.

Shared results
3
Qwen2.5 VL 72B Instruct only
3
Qwen3.5 397B A17B only
63
Like-for-like categories
1 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
Qwen2.5 VL 72B Instruct not benchmarked, Qwen3.5 397B A17B not benchmarked.
Widest category
General, 28.6 points apart on average over 3 shared benchmarks.
Widest single gap
LMArena Vision: Chinese: Qwen2.5 VL 72B Instruct 1107 against Qwen3.5 397B A17B 1314, 34.5 points apart on a 0 to 100 scale.
Output price
Qwen2.5 VL 72B Instruct $1.00 against Qwen3.5 397B A17B $2.34 per million output tokens, 2.3x apart.
Context window
Qwen2.5 VL 72B Instruct takes 128K tokens, Qwen3.5 397B A17B 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
CategoryQwen2.5 VL 72B InstructBarsQwen3.5 397B A17BTies
General03
All shared boards03
CodingDirectional onlySix of these boards feed the Vibe Coding Index8 boards, none shared
Coding benchmarks for Qwen2.5 VL 72B Instruct and Qwen3.5 397B A17B
BenchmarkQwen2.5 VL 72B InstructQwen3.5 397B A17BLeader
LMArena WebDevNot measured1400Only Qwen3.5 397B A17B measured
SciCodeNot measured44.8%Only Qwen3.5 397B A17B measured
Terminal-Bench Hard (Artificial Analysis run)Not measured40.9%Only Qwen3.5 397B A17B measured
ALE-BenchNot measured621.9Only Qwen3.5 397B A17B measured
LMArena Text: codingNot measured1465Only Qwen3.5 397B A17B measured
LMArena Text: software and ITNot measured1463Only Qwen3.5 397B A17B measured
LMArena WebDev: ReactNot measured1388Only Qwen3.5 397B A17B measured
LMArena WebDev: HTMLNot measured1409Only Qwen3.5 397B A17B measured
Neither model has a result on the other 35 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for Qwen2.5 VL 72B Instruct and Qwen3.5 397B A17B
BenchmarkQwen2.5 VL 72B InstructQwen3.5 397B A17BLeader
AA Intelligence IndexNot measured21.4Only Qwen3.5 397B A17B measured
Epoch Capabilities IndexNot measured146.8Only Qwen3.5 397B A17B measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
Agentic work benchmarks for Qwen2.5 VL 72B Instruct and Qwen3.5 397B A17B
BenchmarkQwen2.5 VL 72B InstructQwen3.5 397B A17BLeader
τ²-Bench TelecomNot measured95.6%Only Qwen3.5 397B A17B measured
APEX-AgentsNot measured24.9%Only Qwen3.5 397B A17B measured
OSWorld5.0%Not measuredOnly Qwen2.5 VL 72B Instruct measured
Neither model has a result on the other 39 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
Reasoning benchmarks for Qwen2.5 VL 72B Instruct and Qwen3.5 397B A17B
BenchmarkQwen2.5 VL 72B InstructQwen3.5 397B A17BLeader
GPQA Diamond (Artificial Analysis run)Not measured89.3%Only Qwen3.5 397B A17B measured
Humanity's Last Exam (Artificial Analysis run)Not measured29.0%Only Qwen3.5 397B A17B measured
GPQA Diamond (Epoch AI run)Not measured86.4%Only Qwen3.5 397B A17B measured
Mystery game puzzlesNot measured18.0%Only Qwen3.5 397B A17B measured
LMArena Text: hard promptsNot measured1448Only Qwen3.5 397B A17B measured
LMArena Text: expertNot measured1462Only Qwen3.5 397B A17B measured
LMArena Text: hard prompts in EnglishNot measured1450Only Qwen3.5 397B A17B measured
LMArena Vision: diagramsNot measured1277Only Qwen3.5 397B A17B measured
LMArena Vision: homeworkNot measured1292Only Qwen3.5 397B A17B measured
Kagi LLM Benchmark36.0%Not measuredOnly Qwen2.5 VL 72B Instruct measured
Neither model has a result on the other 13 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Math benchmarks for Qwen2.5 VL 72B Instruct and Qwen3.5 397B A17B
BenchmarkQwen2.5 VL 72B InstructQwen3.5 397B A17BLeader
OTIS Mock AIMENot measured88.9%Only Qwen3.5 397B A17B measured
FrontierMath, tiers 1 to 3Not measured31.2%Only Qwen3.5 397B A17B measured
LMArena Text: mathNot measured1454Only Qwen3.5 397B A17B measured
LMArena Text: mathematical workNot measured1454Only Qwen3.5 397B A17B measured
MathArenaNot measured19.2%Only Qwen3.5 397B A17B measured
Neither model has a result on the other 9 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Knowledge benchmarks for Qwen2.5 VL 72B Instruct and Qwen3.5 397B A17B
BenchmarkQwen2.5 VL 72B InstructQwen3.5 397B A17BLeader
GeoBench62.0%Not measuredOnly Qwen2.5 VL 72B Instruct measured
LMArena Text: scienceNot measured1457Only Qwen3.5 397B A17B measured
LMArena Text: medicine and healthcareNot measured1455Only Qwen3.5 397B A17B measured
LMArena Text: legal and governmentNot measured1441Only Qwen3.5 397B A17B measured
LMArena Text: business and financeNot measured1435Only Qwen3.5 397B A17B measured
Neither model has a result on the other 15 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for Qwen2.5 VL 72B Instruct and Qwen3.5 397B A17B
BenchmarkQwen2.5 VL 72B InstructQwen3.5 397B A17BLeader
Design Arena: websitesNot measured1190Only Qwen3.5 397B A17B measured
Design Arena: UI componentsNot measured1161Only Qwen3.5 397B A17B measured
Design Arena: game devNot measured1140Only Qwen3.5 397B A17B measured
Design Arena: data vizNot measured1175Only Qwen3.5 397B A17B measured
Design Arena: 3DNot measured1162Only Qwen3.5 397B A17B measured
Design Arena: all code categoriesNot measured1179Only Qwen3.5 397B A17B measured
Design Arena: SVGNot measured1139Only Qwen3.5 397B A17B measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index03
General benchmarks for Qwen2.5 VL 72B Instruct and Qwen3.5 397B A17B
BenchmarkQwen2.5 VL 72B InstructQwen3.5 397B A17BLeader
IFBenchNot measured78.8%Only Qwen3.5 397B A17B measured
Long context reasoning (AA-LCR)Not measured77.3%Only Qwen3.5 397B A17B measured
DTBenchNot measured87.5%Only Qwen3.5 397B A17B measured
LMCANot measured37.9%Only Qwen3.5 397B A17B measured
LMArena TextNot measured1438Only Qwen3.5 397B A17B measured
LMArena Text: instruction followingNot measured1423Only Qwen3.5 397B A17B measured
LMArena Text: creative writingNot measured1402Only Qwen3.5 397B A17B measured
LMArena Vision11071262Qwen3.5 397B A17B
LMArena Text: EnglishNot measured1443Only Qwen3.5 397B A17B measured
LMArena Text: non-EnglishNot measured1430Only Qwen3.5 397B A17B measured
LMArena Text: ChineseNot measured1499Only Qwen3.5 397B A17B measured
LMArena Text: GermanNot measured1444Only Qwen3.5 397B A17B measured
LMArena Text: JapaneseNot measured1430Only Qwen3.5 397B A17B measured
LMArena Text: KoreanNot measured1385Only Qwen3.5 397B A17B measured
LMArena Text: FrenchNot measured1462Only Qwen3.5 397B A17B measured
LMArena Text: SpanishNot measured1441Only Qwen3.5 397B A17B measured
LMArena Text: RussianNot measured1430Only Qwen3.5 397B A17B measured
LMArena Text: PolishNot measured1448Only Qwen3.5 397B A17B measured
LMArena Text: multi-turnNot measured1447Only Qwen3.5 397B A17B measured
LMArena Text: longer queriesNot measured1441Only Qwen3.5 397B A17B measured
LMArena Text: writing and languageNot measured1416Only Qwen3.5 397B A17B measured
LMArena Text: entertainment and mediaNot measured1399Only Qwen3.5 397B A17B measured
LMArena Vision: English11151268Qwen3.5 397B A17B
LMArena Vision: Chinese11071314Qwen3.5 397B A17B
LMArena Vision: reading textNot measured1271Only Qwen3.5 397B A17B measured
LMArena Vision: humorNot measured1262Only Qwen3.5 397B A17B measured
LMArena Vision: captioningNot measured1230Only Qwen3.5 397B A17B measured
LMArena Vision: recognizing thingsNot measured1265Only Qwen3.5 397B A17B measured
LMArena Vision: creative writingNot measured1260Only Qwen3.5 397B A17B measured
Neither model has a result on the other 19 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Qwen2.5 VL 72B Instruct and Qwen3.5 397B A17B
BenchmarkQwen2.5 VL 72B InstructQwen3.5 397B A17BLeader
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

Qwen2.5 VL 72B Instruct$0.0013Fits in one request
Qwen3.5 397B A17B$0.0016Fits in one request

Qwen2.5 VL 72B Instruct costs less

Repository review

50K input + 3K output tokens

Qwen2.5 VL 72B Instruct$0.043Fits in one request
Qwen3.5 397B A17B$0.027Fits in one request

Qwen3.5 397B A17B costs less

Agent loop

200K input + 10K output tokens

Qwen2.5 VL 72B Instruct$0.170Exceeds the context window
Qwen3.5 397B A17B$0.101Fits in one request

Qwen3.5 397B A17B 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 Qwen2.5 VL 72B Instruct and Qwen3.5 397B A17B
SpecificationQwen2.5 VL 72B InstructQwen3.5 397B A17B
MakerQwenQwen
WeightsOpen weightsOpen weights
ReleasedFebruary 1, 2025February 16, 2026
Context window128K262K
Input $/Mtok$0.80$0.39
Output $/Mtok$1.00$2.34
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Qwen2.5 VL 72B Instruct better than Qwen3.5 397B A17B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Qwen2.5 VL 72B Instruct for output tokens 2.3x cheaper ($1.00 vs $2.34 per million) and work measured by LMArena Vision or LMArena Vision: English, where it leads.

Which is cheaper, Qwen2.5 VL 72B Instruct or Qwen3.5 397B A17B?

Qwen2.5 VL 72B Instruct costs $0.80 per million input tokens and $1.00 per million output tokens; Qwen3.5 397B A17B costs $0.39 and $2.34. Cost per solved task is known for neither of them.

Which has the bigger context window, Qwen2.5 VL 72B Instruct or Qwen3.5 397B A17B?

Qwen3.5 397B A17B, with 262K tokens against 128K.

How many benchmarks is the Qwen2.5 VL 72B Instruct vs Qwen3.5 397B A17B comparison based on?

3 benchmarks have a result for both models as of October 23, 2026. Qwen2.5 VL 72B Instruct's coding index rests on 0 independent benchmarks and Qwen3.5 397B A17B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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