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o3 vs Qwen3.6 Max

Full profiles: o3 (OpenAI) and Qwen3.6 Max (Alibaba): every benchmark, price and rank.

Updated · Data from 14 sources

As of 29 Oct 2026, o3 and Qwen3.6 Max are neck and neck on quality (61.0 vs 62.4 on the BenchLeader Index, inside the ±4.4 margin), and Qwen3.6 Max is 1.2× cheaper at $2.92 vs $3.50 per 1M tokens blended. Choose o3 for maths (71 vs 65) and coding (62 vs 56); choose Qwen3.6 Max for instruction following (75 vs 65), knowledge (60 vs 56), and human preference (65 vs 61).

Key facts (as of 29 Oct 2026)

  • o3 scores 61.0 on the BenchLeader Index and Qwen3.6 Max scores 62.4 (BenchLeader, 29 Oct 2026).
  • o3 costs $3.50 per 1M tokens blended (list price, 29 Oct 2026).
  • Qwen3.6 Max costs $2.92 per 1M tokens blended (list price, 29 Oct 2026).
  • Of the 16 benchmarks both models have, Qwen3.6 Max leads 16 (BenchLeader, 29 Oct 2026).
o3 benchmarks OpenAI Qwen3.6 Max benchmarks max AlibabaOpen in the comparison tool

Which to pick for…

The pick's numbers come first. Category scores on the BenchLeader scale (50 is the average model, 15 points one standard deviation). High confidence means a lead of half a standard deviation or more; under one point is called either.

Use casePickWhyConfidence
Codingo362 vs 56 category score; Arena Coding 1460 vs 1511Medium
Agents & tool useQwen3.6 Max72 vs 70 category score; Terminal-Bench Hard 43.9% vs 37.1%Medium
Mathso371 vs 65 category score; Arena Maths 1448 vs 1476Medium
ReasoningQwen3.6 Max63 vs 61 category score; Arena Hard Prompts 1482 vs 1441Medium
KnowledgeQwen3.6 Max60 vs 56 category scoreMedium
Long documentsQwen3.6 Max65 vs 62 category score; AA-LCR v1.1 80.7% vs 74.7%Medium
Following instructionsQwen3.6 Max75 vs 65 category score; IFBench 76.6% vs 71.4%High
Chat quality (human preference)Qwen3.6 Max65 vs 61 on Arena votesMedium
Lowest costQwen3.6 Max$2.92 vs $3.50 per 1M blended; agentic coding session $0.109 vs $0.152–
High volume on a budgetNeither flagshipA smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs–

Key differences

  • o3 and Qwen3.6 Max (max) are neck and neck on quality (61.0 vs 62.4, within the ±4.4 margin).
  • o3 is stronger in coding, maths, multimodal.
  • Qwen3.6 Max (max) is stronger in agents & tools, human preference, instruction following, knowledge, long context, reasoning.
  • Qwen3.6 Max (max) is 1.2× cheaper ($2.92 vs $3.50 per 1M blended).

At a glance

Speco3Qwen3.6 Max
DeveloperOpenAIAlibaba
Released16 Apr 202520 Apr 2026
Context window (tokens)200,000262,144
Compared ato3Qwen3.6 Max (max)
Open weightsNoNo
Price in / out / cached input per 1M$2.00 / $8.00 / $0.500$1.30 / $7.80 / $0.130

Category by category

Category scores on the BenchLeader scale: 50 is the average evaluated model, 15 points is one standard deviation. A gap under one point is called level.

Categoryo3Qwen3.6 Max (max)Leader
Reasoning60.962.7Qwen3.6 Max
Coding61.856.3o3
Agents & tools70.372.1Qwen3.6 Max
Maths70.564.7o3
Knowledge56.160.0Qwen3.6 Max
Instruction following65.174.6Qwen3.6 Max
Human preference61.164.6Qwen3.6 Max
Multimodal56.7–not comparable
Long context62.165.2Qwen3.6 Max

Where sources disagree

Across the 16 benchmarks both have, o3 leads 0, Qwen3.6 Max leads 16. Every overall index that rates both puts Qwen3.6 Max ahead.

Overall indexo3Qwen3.6 Max (max)Leader
BenchLeader Index61.062.4neck and neck
Arena Text14321460Qwen3.6 Max

Each publisher runs its own tasks, harnesses and effort settings, so their overall verdicts can differ; BenchLeader reconciles them on one scale. † measured at another effort setting of the same model (the publisher did not test the one compared here).

Price, speed and latency

List prices blended at three input tokens per output token. Per-task prices use the token counts on the methodology page; suite cost is what Artificial Analysis paid to run its whole Intelligence Index.

Measureo3Qwen3.6 Max (max)
Blended price per 1M tokens$3.50$2.92
Input / output per 1M$2.00 / $8.00$1.30 / $7.80
Cached input per 1M$0.500$0.130
Price per task: chat reply$0.0032$0.0029
Price per task: summarize a 30-page report$0.029$0.020
Price per task: code edit$0.024$0.019
Price per task: agentic coding session$0.152$0.109
Price per task: structured extraction$0.0056$0.0042
Output speed151 tok/s–
Time to first answer5.6 s–
Time to a complete answer8.9 s–

Each model is compared at its best-ranked reasoning-effort setting. o3 scores 61.0 and takes 6 s to its first answer token; o3 (high) scores 53.8 in 6 s, o3 (medium) scores 53.3 in 6 s. Qwen3.6 Max (max) scores 62.4. Higher effort means more thinking before the answer: better scores, longer waits and more tokens billed. How reasoning effort changes scores and cost.

Every benchmark

94 benchmarks, grouped by category; each name links to the board and its leaders. † measured at another effort setting of the same model, shown for reference and not counted as a win.

MetricPublishero3Qwen3.6 Max (max)
BenchLeader IndexBenchLeader61.062.4
Agents & tools scoreBenchLeader70.372.1
Coding scoreBenchLeader61.856.3
Human preference scoreBenchLeader61.164.6
Instruction following scoreBenchLeader65.174.6
Knowledge scoreBenchLeader56.160.0
Long context scoreBenchLeader62.165.2
Maths scoreBenchLeader70.564.7
Multimodal scoreBenchLeader56.7–
Reasoning scoreBenchLeader60.962.7
Blended price $/MBenchLeader$3.50$2.92
Output speedBenchLeader151 tok/s–
Time to first answerBenchLeader5.6 s–
Context windowBenchLeader200,000 tokens262,144 tokens
Reasoning
GPQA DiamondEpoch AI Benchmarking Hub81.8%†87.4%
Humanity's Last ExamScale AI / CAIS20.3%†–
SimpleBenchSimpleBench53.1%†63.0%
Arena Hard PromptsArena (LMArena)14411482
GPQA Diamond (AA)Artificial Analysis82.7%88.8%
Humanity's Last Exam (AA)Artificial Analysis20.1%30.8%
GPQA Diamond (Vals)Vals AI84.1%†–
Kagi LLM BenchmarkKagi LLM Benchmark67.6%–
GPQA Diamond (HELM)HELM Capabilities75.3%–
ARC-AGI-1ARC Prize60.8%†–
ARC-AGI-2ARC Prize6.5%†–
CritPtArtificial Analysis1.1%3.7%
SciPredictScale AI SEAL17.9%–
Chess PuzzlesEpoch AI Benchmarking Hub36.0%†–
Mystery Game PuzzlesEpoch AI Benchmarking Hub29.0%†19.0%†
CL-benchEpoch AI Benchmarking Hub17.8%†–
LMCAEpoch AI Benchmarking Hub39.7%†42.5%
DTBenchEpoch AI Benchmarking Hub84.8%†87.2%
ForecastBenchForecastBench64.6%–
Coding
SWE-bench Verified (Epoch)Epoch AI Benchmarking Hub62.3%†76.7%
WeirdMLWeirdML52.4%†–
GSO-BenchGSO-Bench8.8%†–
Arena CodingArena (LMArena)14601511
Arena WebDevArena (LMArena)–1482
LiveCodeBenchVals AI83.9%†–
Show all 94 benchmarks
MetricPublishero3Qwen3.6 Max (max)
Coding
SWE-bench (Vals)Vals AI–72.8%
Aider PolyglotAider polyglot leaderboard81.3%–
SWE-bench Verified (bash only)SWE-bench58.4%–
SWE-bench Verified (any scaffold)SWE-bench58.4%–
CadEvalEpoch AI Benchmarking Hub74.0%†–
ALE-BenchEpoch AI Benchmarking Hub933.5†–
LiveCodeBench (AA)Artificial Analysis80.8%–
Agents & tools
GDPvalOpenAI30.8%†–
Terminal-Bench HardArtificial Analysis37.1%43.9%
τ²-Bench Telecom (AA)Artificial Analysis80.7%95.9%
BFCL OverallBerkeley Function Calling Leaderboard63.0%–
Terminal-Bench 2.0 (Vals)Vals AI–51.7%
DeepResearch BenchDeepResearch Bench45.2%†–
METR Time HorizonsMETR63.6%–
Vending-Bench 2Andon Labs–4254.2
BrowseComp-PlusBrowseComp-Plus50.5%–
Maths
FrontierMath Tiers 1–3Epoch AI Benchmarking Hub33.3%†–
OTIS Mock AIMEEpoch AI Benchmarking Hub83.9%†91.1%
MATH Level 5Epoch AI Benchmarking Hub97.8%†–
AIME (Vals)Vals AI85.3%†–
MGSMVals AI91.8%†–
IMO 2025MathArena16.7%†–
Omni-MATH (HELM)HELM Capabilities71.4%–
MATH 500Vals AI94.6%†–
Arena MathsArena (LMArena)14481476
AIME 2025 (AA)Artificial Analysis88.3%–
Knowledge
SimpleQA VerifiedEpoch AI Benchmarking Hub49.4%†52.0%
MMLU-ProVals AI85.6%†–
LegalBenchVals AI83.8%†–
CorpFinVals AI59.7%†66.5%
TaxEvalVals AI74.6%†–
MedQAVals AI96.1%†–
PRBench FinanceScale AI SEAL47.7%–
PRBench LegalScale AI SEAL48.6%–
MultiNRCScale AI SEAL45.5%†–
MMLU-Pro (HELM)HELM Capabilities85.9%–
CaseLaw v2Vals AI–47.9%
MedCodeVals AI47.3%†–
MedScribeVals AI76.7%†–
Instruction following
IFBenchArtificial Analysis71.4%76.6%
MultiChallengeScale AI SEAL56.6%†–
TutorBenchScale AI SEAL52.1%†–
IFEval (HELM)HELM Capabilities86.9%–
WildBench (HELM)HELM Capabilities86.1%–
Arena Instruction FollowingArena (LMArena)14031451
Human preference
Arena TextArena (LMArena)14321460
Arena Creative WritingArena (LMArena)13831437
Arena Multi-turnArena (LMArena)14201467
Arena Longer QueriesArena (LMArena)14111473
Lech Mazur Creative WritingLech Mazur83.9%†–
Multimodal
Arena VisionArena (LMArena)1214–
MMMU-ProArtificial Analysis70.1%–
VISTAScale AI SEAL50.1%†–
MMMU (validation)MMMU82.9%–
MMMU-Pro (official)MMMU76.4%–
MMMU-Pro (Vals)Vals AI80.4%†–
MortgageTaxVals AI65.7%†–
VTBScale AI SEAL13.7%–
GeoBenchGeoBench60.0%†–
VPCTEpoch AI Benchmarking Hub52.0%†–
Long context
Fiction.LiveBench 120kFiction.live100.0%†–
AA-LCR v1.1Artificial Analysis74.7%80.7%
Composite
Epoch Capabilities IndexEpoch AI Benchmarking Hub146.8149.4
AA Intelligence Index v4.3.2Artificial Analysis20.228.4
AA Progress Index v1Artificial Analysis258.3297.1
HELM Capabilities meanHELM Capabilities81.1%–
Safety & honesty
FORTRESSScale AI SEAL16.0%–
MASKScale AI SEAL84.5%†–
PropensityBenchScale AI SEAL10.5%–

Data as of 2026-10-29. Best configuration of each model; every score links to its source on the model pages.

What changed

  • o3: 1 new result (AA Progress Index v1).
  • Qwen3.6 Max (max): 1 new result (AA Progress Index v1).
  • Qwen3.6 Max (max): BenchLeader Index 63.3 → 62.8.
  • o3: 1 score revision.
  • o3: 1 new result (PRBench Legal).
  • o3: 1 new result (VTB).
  • o3: 1 new result (PRBench Legal).
  • o3: 1 new result (PRBench Finance).
  • o3: 1 new result (SciPredict).
  • o3: 1 new result (PRBench Finance).

Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs

o3 vs Qwen3.6 Max: questions

Is o3 better than Qwen3.6 Max?
o3 and Qwen3.6 Max (max) are neck and neck on quality (61.0 vs 62.4, within the ±4.4 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 29 Oct 2026, so check the category scores for your use.
o3 vs Qwen3.6 Max: which is cheaper, and will that change?
Qwen3.6 Max is cheaper today: $2.92 against $3.50 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
Is o3 or Qwen3.6 Max better for coding?
o3 scores higher in coding (62 vs 56 on the category index, where 50 is average). On Arena Coding, the top shared coding benchmark, it is 1460 for o3 against 1511 for Qwen3.6 Max.
Is o3 or Qwen3.6 Max better for agents and tool use?
Qwen3.6 Max scores higher in agentic tasks (72 vs 70 on the category index, where 50 is average). On Terminal-Bench Hard, the top shared agents & tools benchmark, it is 37.1% for o3 against 43.9% for Qwen3.6 Max.
Which is better for long documents?
Qwen3.6 Max scores higher on long-context benchmarks (65 vs 62). Qwen3.6 Max accepts more context: 262,144 against 200,000 tokens for o3.
More questions (2)
Do independent benchmarks agree on o3 vs Qwen3.6 Max?
Across the 16 benchmarks both have, o3 leads 0, Qwen3.6 Max leads 16. Every overall index that rates both puts Qwen3.6 Max ahead.
When was Qwen3.6 Max released?
Qwen3.6 Max was released on 20 Apr 2026.