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Gemini 3.8 Flash vs Qwen3.6 Max

Full profiles: Gemini 3.8 Flash (Google) and Qwen3.6 Max (Alibaba): every benchmark, price and rank.

Updated · Data from 12 sources

As of 2 Nov 2026, Gemini 3.8 Flash and Qwen3.6 Max are neck and neck on quality (61.9 vs 62.4 on the BenchLeader Index, inside the ±4.7 margin), and Gemini 3.8 Flash is 1.9× cheaper at $1.50 vs $2.92 per 1M tokens blended. Choose Gemini 3.8 Flash for knowledge (64 vs 60), human preference (69 vs 65), and coding (60 vs 56); choose Qwen3.6 Max for agents & tools (72 vs 51) and maths (65 vs 62). Gemini 3.8 Flash's current price runs until 31 Dec 2026, then $3.00.

Key facts (as of 2 Nov 2026)

  • Gemini 3.8 Flash scores 61.9 on the BenchLeader Index and Qwen3.6 Max scores 62.4 (BenchLeader, 2 Nov 2026).
  • Gemini 3.8 Flash costs $1.50 per 1M tokens blended until 31 Dec 2026, then $3.00 (https://ai.google.dev/gemini-api/docs/pricing, checked 20 Oct 2026).
  • Qwen3.6 Max costs $2.92 per 1M tokens blended (list price, 2 Nov 2026).
  • Of the 17 benchmarks both models have, Gemini 3.8 Flash leads 17 (BenchLeader, 2 Nov 2026).
  • On Arena WebDev, Gemini 3.8 Flash is rated 1583 and Qwen3.6 Max 1482 (LMArena, as published by 2 Nov 2026).
Gemini 3.8 Flash benchmarks high Google Qwen3.6 Max benchmarks max AlibabaAdd a third model

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
CodingGemini 3.8 Flash60 vs 56 category score; Arena WebDev 1583 vs 1482Medium
Agents & tool useQwen3.6 Max72 vs 51 category scoreHigh
MathsQwen3.6 Max65 vs 62 category score; Arena Maths 1476 vs 1524Medium
ReasoningGemini 3.8 Flash64 vs 63 category score; GPQA Diamond 95.4% vs 87.4%Medium
KnowledgeGemini 3.8 Flash64 vs 60 category score; SimpleQA Verified 69.7% vs 52.0%Medium
Long documentsEither66 vs 65 category score; AA-LCR v1.1 81.3% vs 80.7%Either
Chat quality (human preference)Gemini 3.8 Flash69 vs 65 on Arena votesMedium
Lowest costGemini 3.8 Flash (until 31 Dec 2026)$1.50 vs $2.96 per 1M blended; agentic coding session $0.060 vs $0.111; from 1 Jan 2027: $3.00 vs $2.96–
High volume on a budgetNeither flagshipA smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs–

Key differences

  • Gemini 3.8 Flash (high) and Qwen3.6 Max (max) are neck and neck on quality (61.9 vs 62.4, within the ±4.7 margin).
  • Gemini 3.8 Flash (high) is stronger in coding, human preference, knowledge, long context, multimodal, reasoning.
  • Qwen3.6 Max (max) is stronger in agents & tools, maths, instruction following.
  • Gemini 3.8 Flash (high) is 2.0× cheaper ($1.50 vs $2.96 per 1M blended) until 31 Dec 2026, then $3.00 vs $2.96 from 1 Jan 2027.

At a glance

SpecGemini 3.8 FlashQwen3.6 Max
DeveloperGoogleAlibaba
Released2 Sep 202620 Apr 2026
Context window (tokens)1,048,576245,800
Compared atGemini 3.8 Flash (high)Qwen3.6 Max (max)
Open weightsNoNo
Price in / out / cached input per 1M$0.750 / $3.75 / $0.075$1.32 / $7.90 / $0.132
Announced price change$1.50 / $7.50 from 1 Jan 2027None announced

Limits, availability and announced prices from the vendors' own pages: ai.google.dev pricing (checked 20 Oct 2026). Everything else is from the day's data.

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.

CategoryGemini 3.8 Flash (high)Qwen3.6 Max (max)Leader
Reasoning63.862.7Gemini 3.8 Flash
Coding60.256.3Gemini 3.8 Flash
Agents & tools51.172.1Qwen3.6 Max
Maths62.264.7Qwen3.6 Max
Knowledge64.460.0Gemini 3.8 Flash
Instruction following–74.6not comparable
Human preference69.064.6Gemini 3.8 Flash
Multimodal67.5–not comparable
Long context65.565.2level

On one chart

Each domain on the index's own scale, where 50 is an average model. Click a domain to see the benchmarks behind it. Pick up to 5 models from the list.

2550 avg75ReasoningCodingAgents & toolsMathsKnowledgeLong contextHumanpreferenceGemini 3.8 Flash, Reasoning: 63.8Gemini 3.8 Flash, Coding: 60.2Gemini 3.8 Flash, Agents & tools: 51.1Gemini 3.8 Flash, Maths: 62.2Gemini 3.8 Flash, Knowledge: 64.4Gemini 3.8 Flash, Long context: 65.5Gemini 3.8 Flash, Human preference: 69.0Qwen3.6 Max, Reasoning: 62.7Qwen3.6 Max, Coding: 56.3Qwen3.6 Max, Agents & tools: 72.1Qwen3.6 Max, Maths: 64.7Qwen3.6 Max, Knowledge: 60.0Qwen3.6 Max, Long context: 65.2Qwen3.6 Max, Human preference: 64.6

Not drawn, measured for fewer than two of these models: Instruction following, Multimodal.

ModelIndex

Where sources disagree

Across the 17 benchmarks both have, Gemini 3.8 Flash leads 17, Qwen3.6 Max leads 0. Every overall index that rates both puts Gemini 3.8 Flash ahead.

Overall indexGemini 3.8 Flash (high)Qwen3.6 Max (max)Leader
BenchLeader Index61.962.4neck and neck
Arena Text14961460Gemini 3.8 Flash

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. Cost, tokens and time per benchmark task are measured: Artificial Analysis’ averages over its whole Intelligence Index run.

MeasureGemini 3.8 Flash (high)Qwen3.6 Max (max)
Blended price per 1M tokens, until 31 Dec 2026$1.50$2.96
Input / output per 1M$0.750 / $3.75$1.32 / $7.90
Blended price per 1M from 1 Jan 2027$3.00$2.96
Input / output per 1M from 1 Jan 2027$1.50 / $7.50$1.32 / $7.90
Cached input per 1M$0.075$0.132
Price per task: chat reply$0.0014$0.0029
Price per task: summarize a 30-page report$0.011$0.021
Price per task: code edit$0.010$0.020
Price per task: agentic coding session$0.060$0.111
Price per task: structured extraction$0.0023$0.0042
Agentic coding session, input mostly cached$0.030$0.057
Cost per benchmark task (AA Index)$7.77–
Output tokens per task (AA Index)99k–
Of which reasoning60k–
Time per task (AA Index)12 min–
Output speed131 tok/s–
Time to first answer24.9 s–
Time to a complete answer28.7 s–

Each model is compared at its best-ranked reasoning-effort setting. Gemini 3.8 Flash (high) scores 61.9 and takes 25 s to its first answer token; Gemini 3.8 Flash (medium) scores 60.6 in 3 s, Gemini 3.8 Flash (low) scores 56.1 in 3 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

153 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.

MetricPublisherGemini 3.8 Flash (high)Qwen3.6 Max (max)
BenchLeader IndexBenchLeader61.962.4
Agents & tools scoreBenchLeader51.172.1
Coding scoreBenchLeader60.256.3
Human preference scoreBenchLeader69.064.6
Knowledge scoreBenchLeader64.460.0
Long context scoreBenchLeader65.565.2
Maths scoreBenchLeader62.264.7
Multimodal scoreBenchLeader67.5–
Reasoning scoreBenchLeader63.862.7
Instruction following scoreBenchLeader–74.6
Blended price $/MBenchLeader$1.50$2.96
Output speedBenchLeader131 tok/s–
Time to first answerBenchLeader24.9 s–
Context windowBenchLeader1,048,576 tokens245,800 tokens
Reasoning
GPQA DiamondEpoch AI Benchmarking Hub95.4%87.4%
Humanity's Last ExamScale AI / CAIS44.5%†–
SimpleBenchSimpleBench–63.0%
Arena Hard PromptsArena (LMArena)15171482
LiveBench 2.0 ReasoningLiveBench89.3%†–
LiveBench 1.0 ReasoningLiveBench89.3%–
GPQA Diamond (AA)Artificial Analysis95.3%88.8%
Humanity's Last Exam (AA)Artificial Analysis47.8%30.8%
HLE-Diamond (AA)Artificial Analysis33.1%–
GPQA Diamond (Vals)Vals AI94.4%–
ARC-AGI-1ARC Prize98.5%–
ARC-AGI-2ARC Prize89.2%–
ARC-AGI-3ARC Prize35.0%–
CritPtArtificial Analysis18.3%3.7%
CritPt v2 hard subset (AA)Artificial Analysis43.5%–
MysteryMechanismVals AI36.5%–
Chess PuzzlesEpoch AI Benchmarking Hub58.0%–
Mystery Game PuzzlesEpoch AI Benchmarking Hub47.0%19.0%†
LMCAEpoch AI Benchmarking Hub51.5%†42.5%
DTBenchEpoch AI Benchmarking Hub95.7%†87.2%
Coding
SWE-bench Verified (Epoch)Epoch AI Benchmarking Hub–76.7%
SciCodeSciCode56.6%–
WeirdMLWeirdML84.8%–
FrontierCodeCognition41.2%†–
Arena CodingArena (LMArena)15301511
Show all 153 benchmarks
MetricPublisherGemini 3.8 Flash (high)Qwen3.6 Max (max)
Coding
Arena WebDevArena (LMArena)15831482
LiveBench 2.0 CodingLiveBench82.2%†–
LiveBench 1.0 CodingLiveBench72.5%–
LiveCodeBenchVals AI89.5%–
IOIVals AI56.9%–
SWE-bench (Vals)Vals AI80.0%72.8%
Code MigrationVals AI36.5%–
Code Migration v1.1Vals AI38.6%–
ProgramBenchVals AI1.0%–
SWE-bench MultimodalVals AI40.8%–
Vibe Code Bench 1-100Vals AI18.8%–
Vibe Code Bench v1.1Vals AI78.7%–
SWE Atlas: Codebase QnAScale AI SEAL47.0%†–
SWE Atlas: RefactoringScale AI SEAL44.8%†–
SWE Atlas: Test WritingScale AI SEAL53.7%†–
Surface Evolver BenchEpoch AI Benchmarking Hub76.9%–
DeepSWE v1.1Epoch AI Benchmarking Hub73.8%–
CursorBenchCursor39.6%–
ALE-BenchEpoch AI Benchmarking Hub1269.7–
FrontierSWEEpoch AI Benchmarking Hub19.6%–
Terminal-Bench 4.0 (AA)Artificial Analysis19.7%–
Terminal-Bench 2.1 (AA)Artificial Analysis87.6%–
Startrise FrontendStartrise64.6%†–
GameBench 2 OverallDuelLab GameBench 261.0†–
GameBench 2 by reasoning settingDuelLab GameBench 266.2–
FrontierCode 1.1 (AA)Artificial Analysis36.4%–
FrontierCode 2.0 (AA)Artificial Analysis18.7%–
Agents & tools
Terminal-BenchTerminal-Bench19.1%–
Remote Labor IndexScale AI / CAIS5.8%†–
APEX-AgentsMercor64.3%†–
Arena AgentArena (LMArena)2.6–
LiveBench Long AgenticLiveBench16.5%†–
LiveBench BrowserLiveBench45.1%†–
LiveBench Agentic CodingLiveBench54.2%–
Terminal-Bench HardArtificial Analysis–43.9%
τ²-Bench Telecom (AA)Artificial Analysis–95.9%
Terminal-Bench 2.1 (Vals)Vals AI81.3%–
HiL-BenchScale AI SEAL41.5%†–
GDPval-AA v2.1, normalised scoreArtificial Analysis46.8%–
GDPval-AA v2.1Artificial Analysis1445–
τ³-Banking (AA)Artificial Analysis45.0%–
ITBench SRE (AA)Artificial Analysis52.5%–
Analyst Agent (AA)Artificial Analysis46.3%–
CUA-benchVals AI4.2%–
CyberBenchVals AI43.8%–
Finance Agent v2Vals AI61.4%–
Finance Agent v2.1Vals AI65.8%–
Harvey's Legal Agent Benchmark v1.1Vals AI12.1%–
Harvey's Legal Agent Benchmark v1Vals AI10.0%–
Legal Research BenchVals AI38.9%–
SkillsBenchVals AI58.0%–
SREBenchVals AI11.1%–
Tax Agent BenchVals AI32.1%–
Terminal-Bench 2.0 (Vals)Vals AI–51.7%
Terminal-Bench 4.0 (Vals)Vals AI19.7%–
Terminal-Bench ScienceVals AI8.6%–
Time Horizon Index: KSPVals AI18.8%–
Vending-Bench 2Andon Labs5093.8†4254.2
AutomationBenchArtificial Analysis59.9%–
GDP.pdf (AA)Artificial Analysis21.0%–
Harvey LAB-AA v1.1Harvey0.0%–
AA-Briefcase v1.1Artificial Analysis1203–
Terminal-Bench-Science 0.1 (AA)Artificial Analysis10.0%–
CWE-Bench (AA)Artificial Analysis52.5%–
DeepSec-Bench (AA)Artificial Analysis14.5%–
CyberGym end-to-end (AA)Artificial Analysis8.4%–
FACTS SearchGoogle76.3%†–
Maths
FrontierMath Tiers 1–3Epoch AI Benchmarking Hub68.4%–
FrontierMath Tier 4Epoch AI Benchmarking Hub21.9%–
OTIS Mock AIMEEpoch AI Benchmarking Hub98.9%91.1%
ProofBenchVals AI48.0%†–
LiveBench MathematicsLiveBench91.6%–
Arena MathsArena (LMArena)15241476
Knowledge
SimpleQA VerifiedEpoch AI Benchmarking Hub69.7%52.0%
LiveBench 2.0 Data AnalysisLiveBench54.0%†–
LiveBench ResearchLiveBench79.1%†–
LiveBench 1.0 Data AnalysisLiveBench54.0%–
AA-Omniscience v1.1Artificial Analysis23.3–
MMLU-ProVals AI90.2%–
LegalBenchVals AI87.0%–
CorpFinVals AI–66.5%
TaxEvalVals AI74.5%–
PRBench FinanceScale AI SEAL49.5%†–
PRBench LegalScale AI SEAL48.9%†–
BioMysteryBenchVals AI62.2%–
CaseLaw v2Vals AI–47.9%
Excel Modeling BenchmarkVals AI72.2%–
Excel Modeling Benchmark v1.1Vals AI72.9%–
MedCodeVals AI48.1%–
MedScribeVals AI84.5%–
Public Benefits Bench v1.1Vals AI65.3%–
GDP.pdfEpoch AI Benchmarking Hub23.2%–
AA-Omniscience v1.1: accuracyArtificial Analysis50.5%–
AA-Omniscience v1.1: non-hallucinationArtificial Analysis44.9%–
HealthBench Professional (AA)OpenAI51.7%–
Instruction following
LiveBench LanguageLiveBench87.8%–
LiveBench Instruction FollowingLiveBench81.4%–
IFBenchArtificial Analysis–76.6%
Arena Instruction FollowingArena (LMArena)14911451
Human preference
Arena TextArena (LMArena)14961460
Arena Creative WritingArena (LMArena)14871437
Arena Multi-turnArena (LMArena)15051467
Arena Longer QueriesArena (LMArena)15121473
Multimodal
Arena VisionArena (LMArena)1315–
LiveBench DesignLiveBench72.7%†–
MMMU-ProArtificial Analysis85.6%–
MMMU-Pro (Vals)Vals AI89.1%–
MortgageTaxVals AI65.3%–
SAGEVals AI88.2%–
AudioMCScale AI SEAL60.4%–
AudioMC (text output)Scale AI SEAL60.4%–
Blueprint-Bench 2Epoch AI Benchmarking Hub38.6%†–
Code2Video-AAArtificial Analysis899–
AA-3DArtificial Analysis966–
Long context
AA-LCR v1.1Artificial Analysis81.3%80.7%
MLCRArtificial Analysis10.6%–
Composite
Epoch Capabilities IndexEpoch AI Benchmarking Hub157.6†149.4
LiveBench 2.0LiveBench59.2%†–
LiveBench 1.0LiveBench75.8%–
AA Intelligence Index v5.0Artificial Analysis30.6–
AA Intelligence Index v4.3.2Artificial Analysis40.928.4
AA Progress Index v1Artificial Analysis320.3297.1
Vals IndexVals AI56.0–
Vals Finance IndexVals AI60.5%–
Vals RSI IndexVals AI19.9%–
Vals Science IndexVals AI35.8%–
Vals Router IndexVals AI56.0%†–
AA Cyber IndexArtificial Analysis25.1–

Data as of 2026-11-02. Best configuration of each model; every score links to its source on the model pages.

DuelLab GameBench 2, release gb2-20261026-cb69502a12d9 (https://benchmarks.duellab.org/releases/gb2-20261026-cb69502a12d9/), CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Scores mapped to BenchLeader model names; not endorsed by DuelLab.

What changed

  • Gemini 3.8 Flash: list price moves to $1.50 / $7.50 per 1M input / output tokens (announced).
  • Gemini 3.8 Flash (high): 1 new result (MirrorCode).
  • Gemini 3.8 Flash (high): 1 score revision.
  • Gemini 3.8 Flash (high): BenchLeader Index 63.3 → 61.8.
  • Gemini 3.8 Flash (high): 5 new results (AA Intelligence Index v5.0, AA Progress Index v1, HLE-Diamond (AA)…); 3 score revisions; cost per task moved from $3.49/M to $7.77/M (123% up).
  • Qwen3.6 Max (max): 1 new result (AA Progress Index v1).
  • Gemini 3.8 Flash (high): cost per task moved from $1.24/M to $3.49/M (180% up).
  • Gemini 3.8 Flash (high): 8 new results (Code Migration v1.1, Excel Modeling Benchmark v1.1, Finance Agent v2.1…).
  • Qwen3.6 Max (max): BenchLeader Index 63.3 → 62.8.
  • Gemini 3.8 Flash (high): 1 score revision.

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

Gemini 3.8 Flash vs Qwen3.6 Max: questions

Is Gemini 3.8 Flash better than Qwen3.6 Max?
Gemini 3.8 Flash (high) and Qwen3.6 Max (max) are neck and neck on quality (61.9 vs 62.4, within the ±4.7 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 2 Nov 2026, so check the category scores for your use.
Gemini 3.8 Flash vs Qwen3.6 Max: which is cheaper, and will that change?
Gemini 3.8 Flash is cheaper today: $1.50 against $2.92 per million tokens, blended at three input tokens per output token. Gemini 3.8 Flash's current price runs until 31 Dec 2026, then $3.00.
Is Gemini 3.8 Flash or Qwen3.6 Max better for coding?
Gemini 3.8 Flash scores higher in coding (60 vs 56 on the category index, where 50 is average). On Arena WebDev, the top shared coding benchmark, it is 1583 for Gemini 3.8 Flash against 1482 for Qwen3.6 Max.
Is Gemini 3.8 Flash or Qwen3.6 Max better for agents and tool use?
Qwen3.6 Max scores higher in agentic tasks (72 vs 51 on the category index, where 50 is average).
Which is better for long documents?
They are level on long-context benchmarks (66 vs 65). Gemini 3.8 Flash accepts more context: 1,048,576 against 245,800 tokens for Qwen3.6 Max.
More questions (2)
Do independent benchmarks agree on Gemini 3.8 Flash vs Qwen3.6 Max?
Across the 17 benchmarks both have, Gemini 3.8 Flash leads 17, Qwen3.6 Max leads 0. Every overall index that rates both puts Gemini 3.8 Flash ahead.
When was Gemini 3.8 Flash released?
Gemini 3.8 Flash was released on 2 Sep 2026.