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o3 vs Qwen3.6 Plus

Qwen3.6 Plus leads o3 on the Artificial Analysis Intelligence Index, 27.0 to 20.2, and Qwen3.6 Plus costs 4.1x less per output token ($1.95 vs $8.00 per million). Updated October 22, 2026; 63 benchmarks have a result for both.

Replace o3 Replace Qwen3.6 Plus
o3OpenAI
Coding
No data
Overall
51.1
Output $/M
$8.00
10
Qwen3.6 PlusQwen
Coding
44.1
Overall
56.2
Output $/M
$1.95
53
vs boards won of 63 shared

o3 or Qwen3.6 Plus: which to pick

Only Qwen3.6 Plus has a coding score, 44.1 on the Vibe Coding Index; o3 has none, so the two cannot be ranked on coding.

Pick o3 for a lower cost per solved task ($0.571 against $1.19) and work measured by ALE-Bench or Chess puzzles, where it leads.

Model Ao3OpenAINot benchmarkedNo coding benchmark$0.571 per solved taskModel BQwen3.6 PlusQwen44.1/1003 independent benchmarks$1.19 per solved task
Shared results
63
o3 only
39
Qwen3.6 Plus only
20
Like-for-like categories
8 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
o3 not benchmarked, Qwen3.6 Plus 44.1 from 3 benchmarks.
Widest category
Web design, 21.0 points apart on average over 5 shared benchmarks.
Widest single gap
Design Arena: all code categories: o3 1020 against Qwen3.6 Plus 1236, 27.0 points apart on a 0 to 100 scale.
Output price
o3 $8.00 against Qwen3.6 Plus $1.95 per million output tokens, 4.1x apart.
Context window
o3 takes 200K tokens, Qwen3.6 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
Categoryo3BarsQwen3.6 PlusTies
Coding14
Intelligence02
Agentic work01
Reasoning28
Math05
Knowledge38
Web design05
General420
All shared boards1053
CodingLike-for-likeSix of these boards feed the Vibe Coding Index14
Coding benchmarks for o3 and Qwen3.6 Plus
Benchmarko3Qwen3.6 PlusLeader
Aider polyglot81.3%Not measuredOnly o3 measured
SWE-bench Verified58.4%Not measuredOnly o3 measured
SWE-bench Multimodal36.0%Not measuredOnly o3 measured
LMArena WebDevNot measured1461Only Qwen3.6 Plus measured
AA Coding IndexNot measured54.5Only Qwen3.6 Plus measured
LiveCodeBench (Vals AI)83.9%86.0%Qwen3.6 Plus
SWE-bench Verified (Vals AI)Not measured73.4%Only Qwen3.6 Plus measured
Vibe Code Bench (Vals AI)Not measured25.6%Only Qwen3.6 Plus measured
Code migration (Vals AI)Not measured11.1%Only Qwen3.6 Plus measured
ProgramBench (Vals AI)Not measured0.0%Only Qwen3.6 Plus measured
Terminal-Bench 2.1 (Vals AI)Not measured53.2%Only Qwen3.6 Plus measured
LiveCodeBench (Artificial Analysis run)80.8%Not measuredOnly o3 measured
Terminal-Bench Hard (Artificial Analysis run)37.1%43.9%Qwen3.6 Plus
GSO-Bench8.8%Not measuredOnly o3 measured
WeirdML52.4%Not measuredOnly o3 measured
ALE-Bench933.5670.1o3
LMArena Text: coding14071467Qwen3.6 Plus
LMArena Text: software and IT14151462Qwen3.6 Plus
LMArena WebDev: ReactNot measured1454Only Qwen3.6 Plus measured
LMArena WebDev: HTMLNot measured1463Only Qwen3.6 Plus measured
LMArena WebDev: from an imageNot measured1472Only Qwen3.6 Plus measured
SciCode9.2%Not measuredOnly o3 measured
Neither model has a result on the other 17 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for o3 and Qwen3.6 Plus
Benchmarko3Qwen3.6 PlusLeader
AA Intelligence Index20.227.0Qwen3.6 Plus
Epoch Capabilities Index146.7147.3Qwen3.6 Plus
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for o3 and Qwen3.6 Plus
Benchmarko3Qwen3.6 PlusLeader
Finance Agent (Vals AI)Not measured40.9%Only Qwen3.6 Plus measured
Tax Agent Bench (Vals AI)Not measured7.7%Only Qwen3.6 Plus measured
Legal Research Bench (Vals AI)Not measured14.9%Only Qwen3.6 Plus measured
Excel Modeling Benchmark (Vals AI)Not measured32.9%Only Qwen3.6 Plus measured
τ²-Bench Telecom80.7%97.7%Qwen3.6 Plus
METR time horizons65.4%Not measuredOnly o3 measured
GDPval30.8%Not measuredOnly o3 measured
DeepResearch Bench45.2%Not measuredOnly o3 measured
OSWorld23.0%Not measuredOnly o3 measured
Vending-Bench 2Not measured$5,115Only Qwen3.6 Plus measured
Berkeley Function Calling Leaderboard (BFCL)63.0%Not measuredOnly o3 measured
BrowseComp-Plus65.9%Not measuredOnly o3 measured
Neither model has a result on the other 29 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index28
Reasoning benchmarks for o3 and Qwen3.6 Plus
Benchmarko3Qwen3.6 PlusLeader
GPQA Diamond84.1%87.4%Qwen3.6 Plus
MMMU Pro (Vals AI)80.4%84.2%Qwen3.6 Plus
GPQA Diamond (Artificial Analysis run)82.7%88.2%Qwen3.6 Plus
Humanity's Last Exam (Artificial Analysis run)20.1%27.8%Qwen3.6 Plus
GPQA Diamond (Epoch AI run)81.8%88.4%Qwen3.6 Plus
ARC-AGI60.8%Not measuredOnly o3 measured
ARC-AGI-26.5%Not measuredOnly o3 measured
SimpleBench53.1%Not measuredOnly o3 measured
Chess puzzles37.0%14.0%o3
Mystery game puzzles29.0%12.0%o3
VPCT52.0%Not measuredOnly o3 measured
LMArena Text: hard prompts14021448Qwen3.6 Plus
LMArena Text: expert14021454Qwen3.6 Plus
LMArena Text: hard prompts in English14111455Qwen3.6 Plus
LMArena Vision: diagrams1220Not measuredOnly o3 measured
LMArena Vision: homework1234Not measuredOnly o3 measured
Kagi LLM Benchmark67.6%Not measuredOnly o3 measured
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index05
Math benchmarks for o3 and Qwen3.6 Plus
Benchmarko3Qwen3.6 PlusLeader
AIME85.3%94.6%Qwen3.6 Plus
MATH 500 (Vals AI)94.6%Not measuredOnly o3 measured
MGSM (Vals AI)91.8%Not measuredOnly o3 measured
AA Math Index88.3Not measuredOnly o3 measured
AIME 2025 (Artificial Analysis run)88.3%Not measuredOnly o3 measured
OTIS Mock AIME84.4%93.3%Qwen3.6 Plus
FrontierMath, tiers 1 to 333.3%38.2%Qwen3.6 Plus
MATH level 597.8%Not measuredOnly o3 measured
LMArena Text: math14261449Qwen3.6 Plus
LMArena Text: mathematical work14231448Qwen3.6 Plus
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index38
Knowledge benchmarks for o3 and Qwen3.6 Plus
Benchmarko3Qwen3.6 PlusLeader
MMLU Pro85.6%87.7%Qwen3.6 Plus
LegalBench (Vals AI)83.8%84.2%Qwen3.6 Plus
CaseLaw (Vals AI)Not measured51.5%Only Qwen3.6 Plus measured
CorpFin (Vals AI)59.7%61.9%Qwen3.6 Plus
TaxEval (Vals AI)74.6%74.7%Qwen3.6 Plus
MortgageTax (Vals AI)65.7%68.0%Qwen3.6 Plus
MedQA (Vals AI)96.1%Not measuredOnly o3 measured
MedCode (Vals AI)47.3%36.9%o3
MMLU Pro (Artificial Analysis run)85.3%Not measuredOnly o3 measured
SimpleQA Verified49.4%44.1%o3
GeoBench74.0%Not measuredOnly o3 measured
LMArena Text: science14291439Qwen3.6 Plus
LMArena Text: medicine and healthcare14481442o3
LMArena Text: legal and government14281437Qwen3.6 Plus
LMArena Text: business and finance13931430Qwen3.6 Plus
FACTS Benchmark Suite44.4%Not measuredOnly o3 measured
Neither model has a result on the other 2 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index05
Web design benchmarks for o3 and Qwen3.6 Plus
Benchmarko3Qwen3.6 PlusLeader
Design Arena: websites10361243Qwen3.6 Plus
Design Arena: UI components10171230Qwen3.6 Plus
Design Arena: game dev10341211Qwen3.6 Plus
Design Arena: data viz12001228Qwen3.6 Plus
Design Arena: 3DNot measured1202Only Qwen3.6 Plus measured
Design Arena: all code categories10201236Qwen3.6 Plus
Design Arena: SVGNot measured1161Only Qwen3.6 Plus measured
Design Arena: ASCII artNot measured1113Only Qwen3.6 Plus measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index420
General benchmarks for o3 and Qwen3.6 Plus
Benchmarko3Qwen3.6 PlusLeader
SAGE (Vals AI)41.8%44.9%Qwen3.6 Plus
MedScribe (Vals AI)76.7%77.0%Qwen3.6 Plus
Vals Multimodal IndexNot measured51.5%Only Qwen3.6 Plus measured
IFBench71.4%75.2%Qwen3.6 Plus
Long context reasoning (AA-LCR)74.7%78.3%Qwen3.6 Plus
DTBench84.8%81.9%o3
LMCA39.7%33.1%o3
Fiction.LiveBench88.9%Not measuredOnly o3 measured
Creative writing (Lech Mazur)83.9%Not measuredOnly o3 measured
CL-bench17.8%20.3%Qwen3.6 Plus
LMArena Text14101436Qwen3.6 Plus
LMArena Text: instruction following13681424Qwen3.6 Plus
LMArena Text: creative writing13591404Qwen3.6 Plus
LMArena Vision1214Not measuredOnly o3 measured
LMArena Text: English14171445Qwen3.6 Plus
LMArena Text: non-English14011424Qwen3.6 Plus
LMArena Text: Chinese14371477Qwen3.6 Plus
LMArena Text: German14201451Qwen3.6 Plus
LMArena Text: Japanese14031390o3
LMArena Text: Korean13701379Qwen3.6 Plus
LMArena Text: French14301455Qwen3.6 Plus
LMArena Text: Spanish13951432Qwen3.6 Plus
LMArena Text: Russian14061434Qwen3.6 Plus
LMArena Text: Polish14381433o3
LMArena Text: multi-turn14051438Qwen3.6 Plus
LMArena Text: longer queries13721439Qwen3.6 Plus
LMArena Text: writing and language13721418Qwen3.6 Plus
LMArena Text: entertainment and media13731402Qwen3.6 Plus
LMArena Vision: English1221Not measuredOnly o3 measured
LMArena Vision: Chinese1237Not measuredOnly o3 measured
LMArena Vision: reading text1218Not measuredOnly o3 measured
LMArena Vision: humor1222Not measuredOnly o3 measured
LMArena Vision: captioning1210Not measuredOnly o3 measured
LMArena Vision: recognizing things1234Not measuredOnly o3 measured
LMArena Vision: creative writing1201Not measuredOnly o3 measured
Neither model has a result on the other 11 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for o3 and Qwen3.6 Plus
Benchmarko3Qwen3.6 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

o3$0.0060Fits in one request
Qwen3.6 Plus$0.0013Fits in one request

Qwen3.6 Plus costs less

Repository review

50K input + 3K output tokens

o3$0.124Fits in one request
Qwen3.6 Plus$0.022Fits in one request

Qwen3.6 Plus costs less

Agent loop

200K input + 10K output tokens

o3$0.480Exceeds the context window
Qwen3.6 Plus$0.085Fits in one request

Qwen3.6 Plus 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 o3 and Qwen3.6 Plus
SpecificationOpenAI o3Qwen3.6 Plus
MakerOpenAIQwen
WeightsNo public weights listedNo public weights listed
ReleasedApril 16, 2025April 2, 2026
Context window200K1M
Input $/Mtok$2.00$0.325
Output $/Mtok$8.00$1.95
Coding indexNot benchmarked44.1
Independent measurements behind it03
Cost per solved task$0.571$1.19
SourceOpenRouter listingOpenRouter listing

Questions

Is o3 better than Qwen3.6 Plus for coding?

Only Qwen3.6 Plus has a coding score, 44.1 on the Vibe Coding Index; o3 has none, so the two cannot be ranked on coding. Pick o3 for a lower cost per solved task ($0.571 against $1.19) and work measured by ALE-Bench or Chess puzzles, where it leads.

Which is cheaper, o3 or Qwen3.6 Plus?

o3 costs $2.00 per million input tokens and $8.00 per million output tokens; Qwen3.6 Plus costs $0.325 and $1.95. Per solved SWE-bench Verified task, o3 costs $0.571 and Qwen3.6 Plus $1.19.

Which has the bigger context window, o3 or Qwen3.6 Plus?

Qwen3.6 Plus, with 1M tokens against 200K.

How many benchmarks is the o3 vs Qwen3.6 Plus comparison based on?

63 benchmarks have a result for both models as of October 22, 2026. o3's coding index rests on 0 independent benchmarks and Qwen3.6 Plus's on 3. Where only one model has a result, the page says so instead of naming a winner.

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