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Gemini 3.5 Flash vs Kimi K3.1 Pro Together

Full profiles: Gemini 3.5 Flash (Google) and Kimi K3.1 Pro Together (Moonshot AI): every benchmark, price and rank.

Updated · Data from 10 sources

As of 9 Nov 2026, Gemini 3.5 Flash and Kimi K3.1 Pro Together are neck and neck on quality (62.5 vs 60.5 on the BenchLeader Index, inside the ±3.6 margin). Kimi K3.1 Pro Together leads in every category we measure both in.

Key facts (as of 9 Nov 2026)

  • Gemini 3.5 Flash scores 62.5 on the BenchLeader Index and Kimi K3.1 Pro Together scores 60.5 (BenchLeader, 9 Nov 2026).
  • Gemini 3.5 Flash costs $3.38 per 1M tokens blended (list price, 9 Nov 2026).
  • Of the 7 benchmarks both models have, Kimi K3.1 Pro Together leads 5 (BenchLeader, 9 Nov 2026).
Gemini 3.5 Flash benchmarks high Google Kimi K3.1 Pro Together benchmarks max Moonshot AIAdd 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
MathsKimi K3.1 Pro Together66 vs 58 category score; FrontierMath Tiers 1–3 78.3% vs 62.8%High
ReasoningKimi K3.1 Pro Together67 vs 61 category score; GPQA Diamond 94.2% vs 92.8%Medium
KnowledgeKimi K3.1 Pro Together68 vs 64 category score; SimpleQA Verified 62.2% vs 66.2%Medium
Chat quality (human preference)–Only Gemini 3.5 Flash has an Arena rating (67 category score)Not comparable
High volume on a budgetNeither flagshipA smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs–

Key differences

  • Gemini 3.5 Flash (high) and Kimi K3.1 Pro Together (max) are neck and neck on quality (62.5 vs 60.5, within the ±3.6 margin).
  • Gemini 3.5 Flash (high) is stronger in agents & tools, coding, human preference, instruction following, long context, multimodal.
  • Kimi K3.1 Pro Together (max) is stronger in knowledge, maths, reasoning.

At a glance

SpecGemini 3.5 FlashKimi K3.1 Pro Together
DeveloperGoogleMoonshot AI
Released19 May 202623 Oct 2026
Context window (tokens)1,048,576–
Compared atGemini 3.5 Flash (high)Kimi K3.1 Pro Together (max)
Open weightsNoNo
Price in / out / cached input per 1M$1.50 / $9.00 / $0.150–

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 3.5 Flash (high)Kimi K3.1 Pro Together (max)Leader
Reasoning60.767.1Kimi K3.1 Pro Together
Coding59.7–not comparable
Agents & tools62.9–not comparable
Maths58.165.8Kimi K3.1 Pro Together
Knowledge63.867.6Kimi K3.1 Pro Together
Instruction following74.4–not comparable
Human preference66.9–not comparable
Multimodal66.2–not comparable
Long context61.2–not comparable

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 avg75ReasoningMathsKnowledgeGemini 3.5 Flash, Reasoning: 60.7Gemini 3.5 Flash, Maths: 58.1Gemini 3.5 Flash, Knowledge: 63.8Kimi K3.1 Pro Together, Reasoning: 67.1Kimi K3.1 Pro Together, Maths: 65.8Kimi K3.1 Pro Together, Knowledge: 67.6

Not drawn, measured for fewer than two of these models: Coding, Agents & tools, Instruction following, Long context, Multimodal, Human preference.

ModelIndex

Where sources disagree

Across the 7 benchmarks both have, Gemini 3.5 Flash leads 1, Kimi K3.1 Pro Together leads 5 and 1 is a tie.

Overall indexGemini 3.5 Flash (high)Kimi K3.1 Pro Together (max)Leader
BenchLeader Index62.560.5neck and neck

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 3.5 Flash (high)Kimi K3.1 Pro Together (max)
Blended price per 1M tokens$3.38–
Input / output per 1M$1.50 / $9.00– / –
Cached input per 1M$0.150–
Price per task: chat reply$0.0033–
Price per task: summarize a 30-page report$0.023–
Price per task: code edit$0.022–
Price per task: agentic coding session$0.126–
Price per task: structured extraction$0.0048–
Agentic coding session, input mostly cached$0.065–
Output speed181 tok/s–
Time to first answer12.4 s–
Time to a complete answer27.4 s–

Each model is compared at its best-ranked reasoning-effort setting. Gemini 3.5 Flash (high) scores 62.5 and takes 12 s to its first answer token; Gemini 3.5 Flash (medium) scores 61.9 in 10 s, Gemini 3.5 Flash (minimal) scores 55.6 in 3 s. Kimi K3.1 Pro Together (max) scores 60.5. 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

106 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 3.5 Flash (high)Kimi K3.1 Pro Together (max)
BenchLeader IndexBenchLeader62.560.5
Agents & tools scoreBenchLeader62.9–
Coding scoreBenchLeader59.7–
Human preference scoreBenchLeader66.9–
Instruction following scoreBenchLeader74.4–
Knowledge scoreBenchLeader63.867.6
Long context scoreBenchLeader61.2–
Maths scoreBenchLeader58.165.8
Multimodal scoreBenchLeader66.2–
Reasoning scoreBenchLeader60.767.1
Blended price $/MBenchLeader$3.38–
Output speedBenchLeader181 tok/s–
Time to first answerBenchLeader12.4 s–
Context windowBenchLeader1,048,576 tokens–
Reasoning
GPQA DiamondEpoch AI Benchmarking Hub92.8%94.2%
SimpleBenchSimpleBench76.7%†–
Arena Hard PromptsArena (LMArena)1496–
LiveBench 1.0 ReasoningLiveBench82.0%–
GPQA Diamond (AA)Artificial Analysis92.2%–
Humanity's Last Exam (AA)Artificial Analysis42.7%–
GPQA Diamond (Vals)Vals AI92.7%–
EnigmaEvalScale AI SEAL25.4%–
ARC-AGI-1ARC Prize92.5%–
ARC-AGI-2ARC Prize72.1%–
CritPtArtificial Analysis13.1%–
Chess PuzzlesEpoch AI Benchmarking Hub45.0%45.0%
Mystery Game PuzzlesEpoch AI Benchmarking Hub32.0%42.0%
LMCAEpoch AI Benchmarking Hub47.1%–
DTBenchEpoch AI Benchmarking Hub94.7%–
ForecastBenchForecastBench64.4%†–
Coding
SWE-bench Verified (Epoch)Epoch AI Benchmarking Hub79.3%–
SciCodeSciCode53.9%–
WeirdMLWeirdML62.6%–
Arena CodingArena (LMArena)1508–
Arena WebDevArena (LMArena)1500–
LiveBench 1.0 CodingLiveBench78.2%–
LiveCodeBenchVals AI87.6%–
SWE-bench (Vals)Vals AI78.8%–
Code MigrationVals AI26.8%–
Show all 106 benchmarks
MetricPublisherGemini 3.5 Flash (high)Kimi K3.1 Pro Together (max)
Coding
ProgramBenchVals AI0.0%–
Vibe Code Bench v1.1Vals AI48.7%–
Surface Evolver BenchEpoch AI Benchmarking Hub58.1%†–
DeepSWE v1.1Epoch AI Benchmarking Hub36.1%–
ALE-BenchEpoch AI Benchmarking Hub911.0–
Terminal-Bench 4.0 (AA)Artificial Analysis6.6%–
Terminal-Bench 2.1 (AA)Artificial Analysis78.7%–
GameBench 2 OverallDuelLab GameBench 249.4†–
GameBench 2 by reasoning settingDuelLab GameBench 262.6–
Design Arena WebsiteDesign Arena1266†–
Agents & tools
APEX-AgentsMercor27.5%†–
LiveBench Agentic CodingLiveBench49.0%–
Terminal-Bench HardArtificial Analysis40.9%–
τ²-Bench Telecom (AA)Artificial Analysis95.3%–
Terminal-Bench 2.1 (Vals)Vals AI74.2%–
MCP AtlasScale AI SEAL83.6%–
HiL-BenchScale AI SEAL27.7%†–
τ³-Banking (AA)Artificial Analysis32.2%–
ITBench SRE (AA)Artificial Analysis40.4%–
Analyst Agent (AA)Artificial Analysis45.0%–
APEX-Agents (AA)Artificial Analysis47.0%–
Finance Agent v2Vals AI57.9%–
Harvey's Legal Agent Benchmark v1Vals AI2.5%–
Legal Research BenchVals AI30.8%–
SkillsBenchVals AI52.7%–
Tax Agent BenchVals AI21.6%–
Terminal-Bench 2.0 (Vals)Vals AI67.4%–
Terminal-Bench 4.0 (Vals)Vals AI6.1%–
Terminal-Bench ScienceVals AI5.7%–
Web Search IndexVals AI37.0%–
GBAEvalEpoch AI Benchmarking Hub6.7%†–
Vending-Bench 2Andon Labs5396.4†–
AutomationBenchArtificial Analysis42.1%–
GDP.pdf (AA)Artificial Analysis19.8%–
EnterpriseOps-GymArtificial Analysis50.1%–
AA-Briefcase v1.1Artificial Analysis876–
Design Arena AgenticDesign Arena1168†–
Maths
FrontierMath Tiers 1–3Epoch AI Benchmarking Hub62.8%78.3%
FrontierMath Tier 4Epoch AI Benchmarking Hub26.8%65.8%
OTIS Mock AIMEEpoch AI Benchmarking Hub95.6%100.0%
ProofBenchVals AI31.0%–
LiveBench MathematicsLiveBench88.2%–
AIME 2026MathArena95.0%†–
HMMT February 2026MathArena95.5%†–
MathArena ApexMathArena32.3%†–
Arena MathsArena (LMArena)1497–
Knowledge
SimpleQA VerifiedEpoch AI Benchmarking Hub66.2%62.2%
LiveBench 1.0 Data AnalysisLiveBench64.9%–
MMLU-ProVals AI89.5%–
LegalBenchVals AI83.6%–
CorpFinVals AI64.7%–
TaxEvalVals AI74.4%–
Excel Modeling BenchmarkVals AI63.5%–
MedCodeVals AI55.8%–
MedScribeVals AI76.6%–
Public Benefits Bench v1.1Vals AI59.5%–
DrugDiscoveryBenchScale AI SEAL50.0%–
EBR-benchEpoch AI Benchmarking Hub4.8%–
GDP.pdfEpoch AI Benchmarking Hub14.0%†–
Instruction following
LiveBench LanguageLiveBench84.6%–
LiveBench Instruction FollowingLiveBench75.6%–
IFBenchArtificial Analysis76.3%–
Arena Instruction FollowingArena (LMArena)1465–
Human preference
Arena TextArena (LMArena)1478–
EQ-Bench 4EQ-Bench1077†–
Arena Creative WritingArena (LMArena)1465–
Arena Multi-turnArena (LMArena)1480–
Arena Longer QueriesArena (LMArena)1483–
Multimodal
Arena VisionArena (LMArena)1308–
MMMU-ProArtificial Analysis84.3%–
MMMU-Pro (Vals)Vals AI88.3%–
MortgageTaxVals AI68.1%–
Blueprint-Bench 2Epoch AI Benchmarking Hub33.6%†–
Long context
AA-LCR v1.1Artificial Analysis73.3%–
Arena DocumentArena (LMArena)1455–
MLCRArtificial Analysis10.0%–
Composite
Epoch Capabilities IndexEpoch AI Benchmarking Hub155.2†–
LiveBench 1.0LiveBench74.6%–
AA Intelligence Index v4.3.2Artificial Analysis32.6–
AA Progress Index v1Artificial Analysis305.1–
Vals Multimodal IndexVals AI62.9%–

Data as of 2026-11-09. Best configuration of each model; every score links to its source on the model pages.

DuelLab GameBench 2, release gb2-20261103-eaea31df94e6 (https://benchmarks.duellab.org/releases/gb2-20261103-eaea31df94e6/), CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Scores mapped to BenchLeader model names; not endorsed by DuelLab.

What changed

  • Kimi K3.1 Pro Together (max): first results.
  • Gemini 3.5 Flash (high): 1 score revision.
  • Gemini 3.5 Flash (high): BenchLeader Index 63.2 → 62.6.
  • Gemini 3.5 Flash (high): 1 new result (AA Progress Index v1).
  • Gemini 3.5 Flash (high): cost per task moved from $3.69/M to $2.98/M (19% down).
  • Gemini 3.5 Flash (high): 1 new result (Harvey's Legal Agent Benchmark v1).
  • Gemini 3.5 Flash (high): 1 score revision.
  • Gemini 3.5 Flash (high): 3 new results (GDPval-AA v2.1, normalised score, AA-Omniscience v1.1: accuracy, AA-Omniscience v1.1: non-hallucination).
  • Gemini 3.5 Flash (high): 1 score revision.
  • Gemini 3.5 Flash (high): 2 score revisions.

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

Gemini 3.5 Flash vs Kimi K3.1 Pro Together: questions

Is Gemini 3.5 Flash better than Kimi K3.1 Pro Together?
Gemini 3.5 Flash (high) and Kimi K3.1 Pro Together (max) are neck and neck on quality (62.5 vs 60.5, within the ±3.6 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 9 Nov 2026, so check the category scores for your use.
Do independent benchmarks agree on Gemini 3.5 Flash vs Kimi K3.1 Pro Together?
Across the 7 benchmarks both have, Gemini 3.5 Flash leads 1, Kimi K3.1 Pro Together leads 5 and 1 is a tie.
When was Kimi K3.1 Pro Together released?
Kimi K3.1 Pro Together was released on 23 Oct 2026.