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Gemini 3.7 Flash vs Kimi K3.1 Pro

Full profiles: Gemini 3.7 Flash (Google) and Kimi K3.1 Pro (Moonshot AI): every benchmark, price and rank.

Updated · Data from 9 sources

As of 24 Oct 2026, Gemini 3.7 Flash (high) and Kimi K3.1 Pro are neck and neck on quality (63.5 vs 66.8 on the BenchLeader Index, inside the ±7.1 margin of error), and Gemini 3.7 Flash (high) costs 2.7× less, which makes it the better buy for most workloads. Kimi K3.1 Pro leads in every category we measure both in.

Gemini 3.7 Flash benchmarks high Google Kimi K3.1 Pro benchmarks Moonshot AIOpen 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
Agents & tool useKimi K3.1 Pro67 vs 48 category score; AutomationBench 73.3% vs 62.0%High
ReasoningKimi K3.1 Pro81 vs 67 category score; CritPt 24.6% vs 14.3%High
KnowledgeKimi K3.1 Pro75 vs 68 category score; AA-Omniscience 29.5 vs 26.5Medium
Long documentsKimi K3.1 Pro68 vs 66 category score; AA-LCR 86.3% vs 81.7%Medium
Images and other mediaEither68 vs 67 category score; MMMU-Pro 85.5% vs 83.9%Either
Chat quality (human preference)–Only Gemini 3.7 Flash has an Arena rating (68 category score)Not comparable
Lowest costGemini 3.7 Flash$1.50 vs $4.00 per 1M blended; agentic coding session $0.060 vs $0.160–
Fastest first answerGemini 3.7 Flash2.5 s (Gemini 3.7 Flash (high)) vs 27.7 s (Kimi K3.1 Pro) to the first answer token–
High volume on a budgetNeither flagshipA smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs–

Key differences

  • Gemini 3.7 Flash (high) and Kimi K3.1 Pro are neck and neck on quality (63.5 vs 66.8, within the ±7.1 margin).
  • Gemini 3.7 Flash (high) is stronger in coding, human preference, maths, multimodal.
  • Kimi K3.1 Pro is stronger in agents & tools, composite, knowledge, long context, reasoning.
  • Gemini 3.7 Flash (high) is 2.7× cheaper ($1.50 vs $4.00 per 1M blended).

At a glance

SpecGemini 3.7 FlashKimi K3.1 Pro
DeveloperGoogleMoonshot AI
Released13 Aug 202623 Oct 2026
Context window (tokens)1,048,5761,048,576
Compared atGemini 3.7 Flash (high)Kimi K3.1 Pro
Open weightsNoNo
Price in / out / cached input per 1M$0.750 / $3.75 / $0.075$2.00 / $10.00 / $0.200

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 3.7 Flash (high)Kimi K3.1 ProLeader
Reasoning67.381.3Kimi K3.1 Pro
Coding63.0–not comparable
Agents & tools47.567.3Kimi K3.1 Pro
Maths63.3–not comparable
Knowledge68.074.8Kimi K3.1 Pro
Human preference68.4–not comparable
Multimodal67.667.0level
Long context65.968.3Kimi K3.1 Pro
Composite73.275.8Kimi K3.1 Pro

Where sources disagree

Across the 11 benchmarks both have, Gemini 3.7 Flash leads 2, Kimi K3.1 Pro leads 9. Every overall index that rates both puts Kimi K3.1 Pro ahead.

Overall indexGemini 3.7 Flash (high)Kimi K3.1 ProLeader
BenchLeader Index63.566.8neck and neck
AA Intelligence Index v4.3.239.155.1Kimi K3.1 Pro

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.

MeasureGemini 3.7 Flash (high)Kimi K3.1 Pro
Blended price per 1M tokens$1.50$4.00
Input / output per 1M$0.750 / $3.75$2.00 / $10.00
Cached input per 1M$0.075$0.200
Price per task: chat reply$0.0014$0.0038
Price per task: summarize a 30-page report$0.011$0.030
Price per task: code edit$0.010$0.027
Price per task: agentic coding session$0.060$0.160
Price per task: structured extraction$0.0023$0.0060
Cost to run a full benchmark suite–$2.11
Output speed88 tok/s81 tok/s
Time to first answer2.5 s27.7 s
Time to a complete answer–33.9 s

Each model is compared at its best-ranked reasoning-effort setting. Gemini 3.7 Flash (high) scores 63.5 and takes 2 s to its first answer token; Gemini 3.7 Flash (medium) scores 63.1 in 2 s, Gemini 3.7 Flash (low) scores 60.3 in 2 s. Kimi K3.1 Pro scores 66.8 and takes 28 s to its first answer token. 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

103 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 3.7 Flash (high)Kimi K3.1 Pro
BenchLeader IndexBenchLeader63.566.8
Agents & tools scoreBenchLeader47.567.3
Coding scoreBenchLeader63.0–
Composite scoreBenchLeader73.275.8
Human preference scoreBenchLeader68.4–
Knowledge scoreBenchLeader68.074.8
Long context scoreBenchLeader65.968.3
Maths scoreBenchLeader63.3–
Multimodal scoreBenchLeader67.667.0
Reasoning scoreBenchLeader67.381.3
Blended price $/MBenchLeader$1.50$4.00
Output speedBenchLeader88 tok/s81 tok/s
Time to first answerBenchLeader2.5 s27.7 s
Context windowBenchLeader1,048,576 tokens1,048,576 tokens
Reasoning
GPQA DiamondEpoch AI Benchmarking Hub94.8%–
Arena Hard PromptsArena (LMArena)1509–
LiveBench 2.0 ReasoningLiveBench87.8%†91.1%
LiveBench 1.0 ReasoningLiveBench87.8%–
GPQA Diamond (AA)Artificial Analysis94.5%–
Humanity's Last Exam (AA)Artificial Analysis47.9%52.5%
GPQA Diamond (Vals)Vals AI93.9%–
ARC-AGI-1ARC Prize95.5%–
ARC-AGI-2ARC Prize84.6%–
CritPtArtificial Analysis14.3%24.6%
Chess PuzzlesEpoch AI Benchmarking Hub66.0%–
Mystery Game PuzzlesEpoch AI Benchmarking Hub37.0%–
LMCAEpoch AI Benchmarking Hub50.4%–
DTBenchEpoch AI Benchmarking Hub96.8%–
ForecastBenchForecastBench66.2%–
Coding
SciCodeSciCode57.2%–
FrontierCodeCognition43.6%†–
Arena CodingArena (LMArena)1520–
Arena WebDevArena (LMArena)1591–
LiveBench 2.0 CodingLiveBench80.5%†81.8%
LiveBench 1.0 CodingLiveBench78.9%–
SciCode (AA)Artificial Analysis57.2%60.8%
LiveCodeBenchVals AI88.7%–
IOIVals AI67.8%–
SWE-bench (Vals)Vals AI80.8%–
Show all 103 benchmarks
MetricPublisherGemini 3.7 Flash (high)Kimi K3.1 Pro
Coding
Code MigrationVals AI34.8%–
ProgramBenchVals AI0.0%–
Vibe Code Bench v1.1Vals AI70.4%–
DeepSWE v1.1Epoch AI Benchmarking Hub65.3%–
ALE-BenchEpoch AI Benchmarking Hub904.3–
FrontierSWEEpoch AI Benchmarking Hub20.3%–
Terminal-Bench 4.0 (AA)Artificial Analysis13.6%67.2%
Terminal-Bench 2.1 (AA)Artificial Analysis85.8%–
FrontierCode 1.1 (AA)Artificial Analysis–47.1%
Agents & tools
Terminal-BenchTerminal-Bench11.2%–
Remote Labor IndexScale AI / CAIS5.0%†–
APEX-AgentsMercor67.8%†–
Arena AgentArena (LMArena)-1–
LiveBench Long AgenticLiveBench28.3%†49.5%
LiveBench BrowserLiveBench56.0%†80.0%
LiveBench Agentic CodingLiveBench58.3%–
Terminal-Bench 2.1 (Vals)Vals AI77.5%–
GDPval-AA v2.1Artificial Analysis–67.3%
τ³-Banking (AA)Artificial Analysis32.8%–
Analyst Agent (AA)Artificial Analysis60.0%–
CyberBenchVals AI43.8%–
Finance Agent v2Vals AI59.0%–
Harvey's Legal Agent Benchmark v1Vals AI8.8%–
Legal Research BenchVals AI34.6%–
SkillsBenchVals AI65.9%–
SREBenchVals AI4.6%–
Tax Agent BenchVals AI22.8%–
Terminal-Bench 4.0 (Vals)Vals AI12.1%–
Terminal-Bench ScienceVals AI7.1%–
AutomationBenchArtificial Analysis62.0%73.3%
GDP.pdf (AA)Artificial Analysis23.6%31.4%
EnterpriseOps-GymArtificial Analysis50.4%†–
AA-Briefcase v1.1Artificial Analysis–1678
CWE-Bench (AA)Artificial Analysis–60.8%
DeepSec-Bench (AA)Artificial Analysis–36.7%
CyberGym end-to-end (AA)Artificial Analysis–94.7%
FACTS SearchGoogle80.9%†–
Maths
FrontierMath Tiers 1–3Epoch AI Benchmarking Hub71.6%–
FrontierMath Tier 4Epoch AI Benchmarking Hub36.6%–
OTIS Mock AIMEEpoch AI Benchmarking Hub97.2%–
ProofBenchVals AI58.0%†–
LiveBench MathematicsLiveBench93.5%–
Arena MathsArena (LMArena)1505–
Knowledge
SimpleQA VerifiedEpoch AI Benchmarking Hub69.2%–
LiveBench 2.0 Data AnalysisLiveBench68.0%†79.1%
LiveBench ResearchLiveBench76.5%†77.9%
LiveBench 1.0 Data AnalysisLiveBench68.0%–
AA-OmniscienceArtificial Analysis26.529.5
MMLU-ProVals AI90.1%–
LegalBenchVals AI87.3%–
TaxEvalVals AI74.7%–
Excel Modeling BenchmarkVals AI71.3%–
MedCodeVals AI53.4%–
MedScribeVals AI83.9%–
GDP.pdfEpoch AI Benchmarking Hub23.8%–
AA-Omniscience: accuracyArtificial Analysis55.3%51.0%
AA-Omniscience: non-hallucinationArtificial Analysis35.5%56.1%
Instruction following
LiveBench LanguageLiveBench85.5%–
LiveBench Instruction FollowingLiveBench79.9%–
Arena Instruction FollowingArena (LMArena)1487–
Human preference
Arena TextArena (LMArena)1490–
Arena Creative WritingArena (LMArena)1492–
Arena Multi-turnArena (LMArena)1489–
Arena Longer QueriesArena (LMArena)1501–
Multimodal
Arena VisionArena (LMArena)1314–
LiveBench DesignLiveBench73.2%†77.8%
MMMU-ProArtificial Analysis85.5%83.9%
MMMU-Pro (Vals)Vals AI89.0%–
MortgageTaxVals AI66.7%–
SAGEVals AI49.2%–
Long context
AA-LCRArtificial Analysis81.7%86.3%
MLCRArtificial Analysis12.2%–
Composite
Epoch Capabilities IndexEpoch AI Benchmarking Hub158.0†–
LiveBench 2.0LiveBench67.2%†76.7%
LiveBench 1.0LiveBench78.8%–
AA Intelligence Index v4.3.2Artificial Analysis39.155.1
Vals RSI IndexVals AI18.3%–
AA Cyber IndexArtificial Analysis–64.1

Data as of 2026-10-24. Best configuration of each model; every score links to its source on the model pages.

What changed

  • Kimi K3.1 Pro: BenchLeader Index 65.6 → 66.8.
  • Kimi K3.1 Pro: 5 new results (FrontierCode 1.1 (AA), AA Cyber Index, CWE-Bench (AA)…).
  • Gemini 3.7 Flash (high): 2 new results (Harvey's Legal Agent Benchmark v1, Vals RSI Index).
  • Kimi K3.1 Pro: first results.
  • Gemini 3.7 Flash (high): input price moved from $0.38/M to $0.75/M (97% up); output price moved from $1.88/M to $3.75/M (99% up).
  • Gemini 3.7 Flash (high): 1 score revision; input price moved from $0.75/M to $0.38/M (49% down); output price moved from $3.75/M to $1.88/M (50% down).
  • Gemini 3.7 Flash (high): 1 new result (ForecastBench).
  • Gemini 3.7 Flash (high): BenchLeader Index 62.9 → 63.5.
  • Gemini 3.7 Flash (high): BenchLeader Index 60.8 → 62.9.
  • Gemini 3.7 Flash (high): 18 new results (AA Intelligence Index v4.3.2, GPQA Diamond (AA), Humanity's Last Exam (AA)…).

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

Gemini 3.7 Flash vs Kimi K3.1 Pro: questions

Is Gemini 3.7 Flash better than Kimi K3.1 Pro?
Gemini 3.7 Flash (high) and Kimi K3.1 Pro are neck and neck on quality (63.5 vs 66.8, within the ±7.1 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 2026-10-24, so check the category scores for your use.
Which is cheaper, Gemini 3.7 Flash or Kimi K3.1 Pro, and will that change?
Gemini 3.7 Flash is cheaper today: $1.50 against $4.00 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
Is Gemini 3.7 Flash better than Kimi K3.1 Pro for agents and tool use?
Kimi K3.1 Pro scores higher in agentic tasks (67 vs 48 on the category index, where 50 is average).
Which is better for long documents?
Kimi K3.1 Pro scores higher on long-context benchmarks (68 vs 66). Both accept 1,048,576 tokens of context.
Which has lower latency?
Gemini 3.7 Flash (high) answers first: 2.5 s against 27.7 s to the first answer token, as Artificial Analysis measures it. Reasoning effort drives most of this: a higher setting thinks longer before it answers.
Which is faster, Gemini 3.7 Flash or Kimi K3.1 Pro?
Gemini 3.7 Flash streams faster: 88 against 81 output tokens per second.
Do independent benchmarks agree on Gemini 3.7 Flash vs Kimi K3.1 Pro?
Across the 11 benchmarks both have, Gemini 3.7 Flash leads 2, Kimi K3.1 Pro leads 9. Every overall index that rates both puts Kimi K3.1 Pro ahead.
When was Kimi K3.1 Pro released?
Kimi K3.1 Pro was released on 23 Oct 2026.