Enter opens the highlighted result. Esc closes.

Qwen2.5 Coder 32B Instruct vs Qwen3.5-35B-A3B

Qwen3.5-35B-A3B leads Qwen2.5 Coder 32B Instruct on the Artificial Analysis Intelligence Index, 19.3 to 6.7, and Qwen2.5 Coder 32B Instruct costs 1.3x less per output token ($1.00 vs $1.30 per million). Updated October 22, 2026; 26 benchmarks have a result for both.

Qwen2.5 Coder 32B InstructQwen
Coding
No data
Overall
No data
Output $/M
$1.00
0
Qwen3.5-35B-A3BQwen
Coding
No data
Overall
53.5
Output $/M
$1.30
26
vs boards won of 26 shared

Qwen2.5 Coder 32B Instruct or Qwen3.5-35B-A3B: which to pick

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

Pick Qwen2.5 Coder 32B Instruct for output tokens 1.3x cheaper ($1.00 vs $1.30 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Shared results
26
Qwen2.5 Coder 32B Instruct only
9
Qwen3.5-35B-A3B only
19
Like-for-like categories
6 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 Coder 32B Instruct not benchmarked, Qwen3.5-35B-A3B not benchmarked.
Widest category
Knowledge, 30.8 points apart on average over 4 shared benchmarks.
Widest single gap
GPQA Diamond (Artificial Analysis run): Qwen2.5 Coder 32B Instruct 41.7% against Qwen3.5-35B-A3B 84.5%, 42.8 points apart on a 0 to 100 scale.
Output price
Qwen2.5 Coder 32B Instruct $1.00 against Qwen3.5-35B-A3B $1.30 per million output tokens, 1.3x apart.
Context window
Qwen2.5 Coder 32B Instruct takes 33K tokens, Qwen3.5-35B-A3B 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 Coder 32B InstructBarsQwen3.5-35B-A3BTies
Coding02
Intelligence02
Reasoning05
Math02
Knowledge04
General011
All shared boards026
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for Qwen2.5 Coder 32B Instruct and Qwen3.5-35B-A3B
BenchmarkQwen2.5 Coder 32B InstructQwen3.5-35B-A3BLeader
Aider polyglot16.4%Not measuredOnly Qwen2.5 Coder 32B Instruct measured
SWE-bench Verified47.0%Not measuredOnly Qwen2.5 Coder 32B Instruct measured
LMArena WebDevNot measured1254Only Qwen3.5-35B-A3B measured
LiveCodeBench (Artificial Analysis run)29.5%Not measuredOnly Qwen2.5 Coder 32B Instruct measured
Terminal-Bench Hard (Artificial Analysis run)Not measured26.5%Only Qwen3.5-35B-A3B measured
ALE-BenchNot measured221.8Only Qwen3.5-35B-A3B measured
LMArena Text: coding12761410Qwen3.5-35B-A3B
LMArena Text: software and IT12611415Qwen3.5-35B-A3B
LMArena WebDev: ReactNot measured1238Only Qwen3.5-35B-A3B measured
LMArena WebDev: HTMLNot measured1301Only Qwen3.5-35B-A3B measured
Neither model has a result on the other 29 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Qwen2.5 Coder 32B Instruct and Qwen3.5-35B-A3B
BenchmarkQwen2.5 Coder 32B InstructQwen3.5-35B-A3BLeader
AA Intelligence Index6.719.3Qwen3.5-35B-A3B
Epoch Capabilities Index119.5142.5Qwen3.5-35B-A3B
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Agentic work benchmarks for Qwen2.5 Coder 32B Instruct and Qwen3.5-35B-A3B
BenchmarkQwen2.5 Coder 32B InstructQwen3.5-35B-A3BLeader
τ²-Bench TelecomNot measured89.2%Only Qwen3.5-35B-A3B measured
Vending-Bench 2Not measured$463Only Qwen3.5-35B-A3B measured
Neither model has a result on the other 39 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for Qwen2.5 Coder 32B Instruct and Qwen3.5-35B-A3B
BenchmarkQwen2.5 Coder 32B InstructQwen3.5-35B-A3BLeader
GPQA Diamond (Artificial Analysis run)41.7%84.5%Qwen3.5-35B-A3B
Humanity's Last Exam (Artificial Analysis run)3.5%21.0%Qwen3.5-35B-A3B
GPQA Diamond (Epoch AI run)Not measured83.5%Only Qwen3.5-35B-A3B measured
LMArena Text: hard prompts12511400Qwen3.5-35B-A3B
LMArena Text: expert12211408Qwen3.5-35B-A3B
LMArena Text: hard prompts in English12691411Qwen3.5-35B-A3B
Neither model has a result on the other 16 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Qwen2.5 Coder 32B Instruct and Qwen3.5-35B-A3B
BenchmarkQwen2.5 Coder 32B InstructQwen3.5-35B-A3BLeader
OTIS Mock AIMENot measured70.0%Only Qwen3.5-35B-A3B measured
GSM8K93.0%Not measuredOnly Qwen2.5 Coder 32B Instruct measured
LMArena Text: math12511404Qwen3.5-35B-A3B
LMArena Text: mathematical work12431410Qwen3.5-35B-A3B
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Qwen2.5 Coder 32B Instruct and Qwen3.5-35B-A3B
BenchmarkQwen2.5 Coder 32B InstructQwen3.5-35B-A3BLeader
MMLU Pro (Artificial Analysis run)63.5%Not measuredOnly Qwen2.5 Coder 32B Instruct measured
MMLU79.1%Not measuredOnly Qwen2.5 Coder 32B Instruct measured
AI2 Reasoning Challenge70.5%Not measuredOnly Qwen2.5 Coder 32B Instruct measured
LMArena Text: science12211413Qwen3.5-35B-A3B
LMArena Text: medicine and healthcare11871421Qwen3.5-35B-A3B
LMArena Text: legal and government12571399Qwen3.5-35B-A3B
LMArena Text: business and finance12241394Qwen3.5-35B-A3B
Neither model has a result on the other 11 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Qwen2.5 Coder 32B Instruct and Qwen3.5-35B-A3B
BenchmarkQwen2.5 Coder 32B InstructQwen3.5-35B-A3BLeader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index011
General benchmarks for Qwen2.5 Coder 32B Instruct and Qwen3.5-35B-A3B
BenchmarkQwen2.5 Coder 32B InstructQwen3.5-35B-A3BLeader
IFBenchNot measured72.5%Only Qwen3.5-35B-A3B measured
Long context reasoning (AA-LCR)Not measured72.0%Only Qwen3.5-35B-A3B measured
DTBenchNot measured80.0%Only Qwen3.5-35B-A3B measured
LMCANot measured29.5%Only Qwen3.5-35B-A3B measured
HellaSwag83.0%Not measuredOnly Qwen2.5 Coder 32B Instruct measured
WinoGrande80.8%Not measuredOnly Qwen2.5 Coder 32B Instruct measured
LMArena Text12301395Qwen3.5-35B-A3B
LMArena Text: instruction following12231379Qwen3.5-35B-A3B
LMArena Text: creative writing11741347Qwen3.5-35B-A3B
LMArena Text: English12481407Qwen3.5-35B-A3B
LMArena Text: non-English12051378Qwen3.5-35B-A3B
LMArena Text: Chinese12221457Qwen3.5-35B-A3B
LMArena Text: GermanNot measured1367Only Qwen3.5-35B-A3B measured
LMArena Text: JapaneseNot measured1326Only Qwen3.5-35B-A3B measured
LMArena Text: KoreanNot measured1355Only Qwen3.5-35B-A3B measured
LMArena Text: FrenchNot measured1412Only Qwen3.5-35B-A3B measured
LMArena Text: SpanishNot measured1390Only Qwen3.5-35B-A3B measured
LMArena Text: Russian12281376Qwen3.5-35B-A3B
LMArena Text: PolishNot measured1385Only Qwen3.5-35B-A3B measured
LMArena Text: multi-turn12221390Qwen3.5-35B-A3B
LMArena Text: longer queries12511389Qwen3.5-35B-A3B
LMArena Text: writing and language11911365Qwen3.5-35B-A3B
LMArena Text: entertainment and media11501347Qwen3.5-35B-A3B
Neither model has a result on the other 23 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Qwen2.5 Coder 32B Instruct and Qwen3.5-35B-A3B
BenchmarkQwen2.5 Coder 32B InstructQwen3.5-35B-A3BLeader
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 Coder 32B Instruct$0.0012Fits in one request
Qwen3.5-35B-A3B$0.0008Fits in one request

Qwen3.5-35B-A3B costs less

Repository review

50K input + 3K output tokens

Qwen2.5 Coder 32B Instruct$0.036Exceeds the context window
Qwen3.5-35B-A3B$0.012Fits in one request

Qwen3.5-35B-A3B costs less

Agent loop

200K input + 10K output tokens

Qwen2.5 Coder 32B Instruct$0.142Exceeds the context window
Qwen3.5-35B-A3B$0.045Fits in one request

Qwen3.5-35B-A3B 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 Coder 32B Instruct and Qwen3.5-35B-A3B
SpecificationQwen2.5 Coder 32B InstructQwen3.5-35B-A3B
MakerQwenQwen
WeightsOpen weightsOpen weights
ReleasedNovember 11, 2024February 25, 2026
Context window33K262K
Input $/Mtok$0.66$0.1625
Output $/Mtok$1.00$1.30
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it01
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Qwen2.5 Coder 32B Instruct better than Qwen3.5-35B-A3B for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Qwen2.5 Coder 32B Instruct for output tokens 1.3x cheaper ($1.00 vs $1.30 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, Qwen2.5 Coder 32B Instruct or Qwen3.5-35B-A3B?

Qwen2.5 Coder 32B Instruct costs $0.66 per million input tokens and $1.00 per million output tokens; Qwen3.5-35B-A3B costs $0.1625 and $1.30. Cost per solved task is known for neither of them.

Which has the bigger context window, Qwen2.5 Coder 32B Instruct or Qwen3.5-35B-A3B?

Qwen3.5-35B-A3B, with 262K tokens against 33K.

How many benchmarks is the Qwen2.5 Coder 32B Instruct vs Qwen3.5-35B-A3B comparison based on?

26 benchmarks have a result for both models as of October 22, 2026. Qwen2.5 Coder 32B Instruct's coding index rests on 0 independent benchmarks and Qwen3.5-35B-A3B's on 1. Where only one model has a result, the page says so instead of naming a winner.

Compare next