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Qwen-Plus vs Qwen3 235B A22B Instruct 2507

Qwen-Plus and Qwen3 235B A22B Instruct 2507 cost about the same per output token ($0.78 vs $0.775 per million). Updated October 23, 2026; 2 benchmarks have a result for both.

Qwen-PlusQwen
Coding
No data
Overall
No data
Output $/M
$0.78
2
Qwen3 235B A22B Instruct 2507Qwen
Coding
No data
Overall
No data
Output $/M
$0.775
0
vs boards won of 2 shared

Qwen-Plus or Qwen3 235B A22B Instruct 2507: which to pick

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

Pick Qwen-Plus for a larger context window (1M against 262K tokens).

Shared results
2
Qwen-Plus only
26
Qwen3 235B A22B Instruct 2507 only
22
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
Qwen-Plus not benchmarked, Qwen3 235B A22B Instruct 2507 not benchmarked.
Widest category
General, 1.6 points apart on average over 2 shared benchmarks.
Widest single gap
DTBench: Qwen-Plus 81.1% against Qwen3 235B A22B Instruct 2507 78.4%, 2.7 points apart on a 0 to 100 scale.
Output price
Qwen-Plus $0.78 against Qwen3 235B A22B Instruct 2507 $0.775 per million output tokens, 1.0x apart.
Context window
Qwen-Plus takes 1M tokens, Qwen3 235B A22B Instruct 2507 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
CategoryQwen-PlusBarsQwen3 235B A22B Instruct 2507Ties
General20
All shared boards20
CodingDirectional onlySix of these boards feed the Vibe Coding Index6 boards, none shared
Coding benchmarks for Qwen-Plus and Qwen3 235B A22B Instruct 2507
BenchmarkQwen-PlusQwen3 235B A22B Instruct 2507Leader
LiveCodeBench (Artificial Analysis run)Not measured78.8%Only Qwen3 235B A22B Instruct 2507 measured
SciCodeNot measured41.4%Only Qwen3 235B A22B Instruct 2507 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured15.2%Only Qwen3 235B A22B Instruct 2507 measured
WeirdMLNot measured38.7%Only Qwen3 235B A22B Instruct 2507 measured
LMArena Text: coding1328Not measuredOnly Qwen-Plus measured
LMArena Text: software and IT1343Not measuredOnly Qwen-Plus measured
Neither model has a result on the other 37 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Intelligence benchmarks for Qwen-Plus and Qwen3 235B A22B Instruct 2507
BenchmarkQwen-PlusQwen3 235B A22B Instruct 2507Leader
AA Intelligence IndexNot measured12.0Only Qwen3 235B A22B Instruct 2507 measured
Neither model has a result on the other 1 board here
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Agentic work benchmarks for Qwen-Plus and Qwen3 235B A22B Instruct 2507
BenchmarkQwen-PlusQwen3 235B A22B Instruct 2507Leader
τ²-Bench TelecomNot measured53.2%Only Qwen3 235B A22B Instruct 2507 measured
Berkeley Function Calling Leaderboard (BFCL)Not measured52.1%Only Qwen3 235B A22B Instruct 2507 measured
Neither model has a result on the other 40 boards here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Reasoning benchmarks for Qwen-Plus and Qwen3 235B A22B Instruct 2507
BenchmarkQwen-PlusQwen3 235B A22B Instruct 2507Leader
GPQA Diamond (Artificial Analysis run)Not measured79.0%Only Qwen3 235B A22B Instruct 2507 measured
Humanity's Last Exam (Artificial Analysis run)Not measured15.9%Only Qwen3 235B A22B Instruct 2507 measured
GPQA Diamond (Epoch AI run)48.1%Not measuredOnly Qwen-Plus measured
ARC-AGINot measured11.0%Only Qwen3 235B A22B Instruct 2507 measured
ARC-AGI-2Not measured1.3%Only Qwen3 235B A22B Instruct 2507 measured
LMArena Text: hard prompts1316Not measuredOnly Qwen-Plus measured
LMArena Text: expert1328Not measuredOnly Qwen-Plus measured
LMArena Text: hard prompts in English1333Not measuredOnly Qwen-Plus measured
Neither model has a result on the other 15 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Math benchmarks for Qwen-Plus and Qwen3 235B A22B Instruct 2507
BenchmarkQwen-PlusQwen3 235B A22B Instruct 2507Leader
AA Math IndexNot measured91.0Only Qwen3 235B A22B Instruct 2507 measured
AIME 2025 (Artificial Analysis run)Not measured91.0%Only Qwen3 235B A22B Instruct 2507 measured
OTIS Mock AIME17.8%Not measuredOnly Qwen-Plus measured
MATH level 565.3%Not measuredOnly Qwen-Plus measured
LMArena Text: math1326Not measuredOnly Qwen-Plus measured
LMArena Text: mathematical work1332Not measuredOnly Qwen-Plus measured
Neither model has a result on the other 8 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Knowledge benchmarks for Qwen-Plus and Qwen3 235B A22B Instruct 2507
BenchmarkQwen-PlusQwen3 235B A22B Instruct 2507Leader
MMLU Pro (Artificial Analysis run)Not measured84.3%Only Qwen3 235B A22B Instruct 2507 measured
LMArena Text: science1352Not measuredOnly Qwen-Plus measured
LMArena Text: medicine and healthcare1350Not measuredOnly Qwen-Plus measured
LMArena Text: legal and government1349Not measuredOnly Qwen-Plus measured
LMArena Text: business and finance1303Not measuredOnly Qwen-Plus measured
Neither model has a result on the other 15 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Web design benchmarks for Qwen-Plus and Qwen3 235B A22B Instruct 2507
BenchmarkQwen-PlusQwen3 235B A22B Instruct 2507Leader
Design Arena: websitesNot measured1058Only Qwen3 235B A22B Instruct 2507 measured
Design Arena: UI componentsNot measured963Only Qwen3 235B A22B Instruct 2507 measured
Design Arena: game devNot measured951Only Qwen3 235B A22B Instruct 2507 measured
Design Arena: data vizNot measured1070Only Qwen3 235B A22B Instruct 2507 measured
Design Arena: 3DNot measured995Only Qwen3 235B A22B Instruct 2507 measured
Design Arena: all code categoriesNot measured1038Only Qwen3 235B A22B Instruct 2507 measured
Neither model has a result on the other 3 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
General benchmarks for Qwen-Plus and Qwen3 235B A22B Instruct 2507
BenchmarkQwen-PlusQwen3 235B A22B Instruct 2507Leader
IFBenchNot measured51.2%Only Qwen3 235B A22B Instruct 2507 measured
Long context reasoning (AA-LCR)Not measured72.0%Only Qwen3 235B A22B Instruct 2507 measured
DTBench81.1%78.4%Qwen-Plus
LMCA24.0%23.5%Qwen-Plus
LMArena Text1326Not measuredOnly Qwen-Plus measured
LMArena Text: instruction following1303Not measuredOnly Qwen-Plus measured
LMArena Text: creative writing1292Not measuredOnly Qwen-Plus measured
LMArena Text: English1338Not measuredOnly Qwen-Plus measured
LMArena Text: non-English1310Not measuredOnly Qwen-Plus measured
LMArena Text: Chinese1347Not measuredOnly Qwen-Plus measured
LMArena Text: Japanese1251Not measuredOnly Qwen-Plus measured
LMArena Text: Russian1323Not measuredOnly Qwen-Plus measured
LMArena Text: multi-turn1336Not measuredOnly Qwen-Plus measured
LMArena Text: longer queries1324Not measuredOnly Qwen-Plus measured
LMArena Text: writing and language1296Not measuredOnly Qwen-Plus measured
LMArena Text: entertainment and media1270Not measuredOnly Qwen-Plus measured
Neither model has a result on the other 32 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Qwen-Plus and Qwen3 235B A22B Instruct 2507
BenchmarkQwen-PlusQwen3 235B A22B Instruct 2507Leader
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

Qwen-Plus$0.0006Fits in one request
Qwen3 235B A22B Instruct 2507$0.0005Fits in one request

Qwen3 235B A22B Instruct 2507 costs less

Repository review

50K input + 3K output tokens

Qwen-Plus$0.015Fits in one request
Qwen3 235B A22B Instruct 2507$0.0096Fits in one request

Qwen3 235B A22B Instruct 2507 costs less

Agent loop

200K input + 10K output tokens

Qwen-Plus$0.060Fits in one request
Qwen3 235B A22B Instruct 2507$0.037Fits in one request

Qwen3 235B A22B 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 Qwen-Plus and Qwen3 235B A22B Instruct 2507
SpecificationQwen-PlusQwen3 235B A22B Instruct 2507
MakerQwenQwen
WeightsNo public weights listedOpen weights
ReleasedFebruary 1, 2025July 21, 2025
Context window1M262K
Input $/Mtok$0.26$0.145
Output $/Mtok$0.78$0.775
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Qwen-Plus better than Qwen3 235B A22B Instruct 2507 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Qwen-Plus for a larger context window (1M against 262K tokens).

Which is cheaper, Qwen-Plus or Qwen3 235B A22B Instruct 2507?

Qwen-Plus costs $0.26 per million input tokens and $0.78 per million output tokens; Qwen3 235B A22B Instruct 2507 costs $0.145 and $0.775. Cost per solved task is known for neither of them.

Which has the bigger context window, Qwen-Plus or Qwen3 235B A22B Instruct 2507?

Qwen-Plus, with 1M tokens against 262K.

How many benchmarks is the Qwen-Plus vs Qwen3 235B A22B Instruct 2507 comparison based on?

2 benchmarks have a result for both models as of October 23, 2026. Qwen-Plus's coding index rests on 0 independent benchmarks and Qwen3 235B A22B Instruct 2507's on 0. Where only one model has a result, the page says so instead of naming a winner.

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