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Gemini 3.5 Flash vs Kimi K2.6

Updated October 21, 2026. 102 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace Gemini 3.5 Flash Replace Kimi K2.6
Gemini 3.5 FlashGoogle
Coding
42.8
Overall
33.6
Output $/M
$9.00
80
Kimi K2.6Moonshot AI
Coding
44.2
Overall
27.0
Output $/M
$3.41
21
vs boards won of 102 shared, 1 tied

Decision reading

Gemini 3.5 Flash and Kimi K2.6 are level for coding, 42.8 against 44.2 on the Vibe Coding Index, so price and context decide.

Pick Gemini 3.5 Flash when the context window is larger, 1.05M against 262K tokens, or when what matters is LiveCodeBench (Vals AI) or SWE-bench Verified (Vals AI), where it leads. Pick Kimi K2.6 when output tokens cost 2.6x less, or when a solved task costs $0.35 against $1.21.

Model AGemini 3.5 FlashGoogle42.8/1001 independent benchmark$1.21 per solved taskModel BKimi K2.6Moonshot AI44.2/1001 independent benchmark$0.35 per solved task
Shared results
102
Gemini 3.5 Flash only
8
Kimi K2.6 only
7
Like-for-like categories
8 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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
Gemini 3.5 Flash 42.8 from 1 benchmark, Kimi K2.6 44.2 from 1 benchmark.
Widest category
Knowledge, 6.5 points apart on average over 11 shared benchmarks.
Widest single gap
SimpleQA Verified: Gemini 3.5 Flash 66.2% against Kimi K2.6 34.9%, 31.3 points apart on a 0 to 100 scale.
Output price
Gemini 3.5 Flash $9.00 against Kimi K2.6 $3.41 per million output tokens, 2.6x apart.
Context window
Gemini 3.5 Flash takes 1.05M tokens, Kimi K2.6 262K.

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
CategoryGemini 3.5 FlashBarsKimi K2.6Ties
Coding1051 tie
Intelligence20
Agentic work95
Reasoning130
Math51
Knowledge83
Web design44
General293
All shared boards80211 tie
CodingLike-for-likeFour of these boards feed the Vibe Coding Index105
Coding benchmarks for Gemini 3.5 Flash and Kimi K2.6
BenchmarkGemini 3.5 FlashKimi K2.6Leader
LMArena WebDev14991509Kimi K2.6
AA Coding IndexNot measured61.8Only Kimi K2.6 measured
LiveCodeBench (Vals AI)87.6%86.8%Gemini 3.5 Flash
SWE-bench Verified (Vals AI)78.8%76.2%Gemini 3.5 Flash
Terminal-Bench 4 (Vals AI)6.1%Not measuredOnly Gemini 3.5 Flash measured
Vibe Code Bench (Vals AI)48.7%37.9%Gemini 3.5 Flash
Code migration (Vals AI)26.8%27.8%Kimi K2.6
ProgramBench (Vals AI)0.0%0.0%Tie
Terminal-Bench 2.1 (Vals AI)74.2%53.6%Gemini 3.5 Flash
SkillsBench (Vals AI)52.7%Not measuredOnly Gemini 3.5 Flash measured
SciCode53.9%51.5%Gemini 3.5 Flash
Terminal-Bench Hard (Artificial Analysis run)46.2%43.9%Gemini 3.5 Flash
WeirdML62.6%55.9%Gemini 3.5 Flash
ALE-Bench911.01092.7Kimi K2.6
LMArena Text: coding14931489Gemini 3.5 Flash
LMArena Text: software and IT14941484Gemini 3.5 Flash
LMArena WebDev: React14951505Kimi K2.6
LMArena WebDev: HTML15221485Gemini 3.5 Flash
LMArena WebDev: from an image15041521Kimi K2.6
Neither model has a result on the other 19 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Gemini 3.5 Flash and Kimi K2.6
BenchmarkGemini 3.5 FlashKimi K2.6Leader
AA Intelligence Index33.627.0Gemini 3.5 Flash
Epoch Capabilities Index154.9150.9Gemini 3.5 Flash
Agentic workLike-for-likePublic boards, shown as published, kept out of the index95
Agentic work benchmarks for Gemini 3.5 Flash and Kimi K2.6
BenchmarkGemini 3.5 FlashKimi K2.6Leader
AA Agentic IndexNot measured20.5Only Kimi K2.6 measured
Design Arena: agents building web apps12021268Kimi K2.6
Design Arena: agents building full-stack apps11971155Gemini 3.5 Flash
Design Arena: agents building mobile apps11751156Gemini 3.5 Flash
Design Arena: agents building Android apps11901166Gemini 3.5 Flash
Design Arena: agents building Godot games10981120Kimi K2.6
Design Arena: agents building games11801141Gemini 3.5 Flash
Design Arena: HTML slides11421184Kimi K2.6
Design Arena: PowerPoint slides11781128Gemini 3.5 Flash
Design Arena: spreadsheetsNot measured1276Only Kimi K2.6 measured
Finance Agent (Vals AI)57.9%44.9%Gemini 3.5 Flash
Tax Agent Bench (Vals AI)21.6%12.4%Gemini 3.5 Flash
Legal Research Bench (Vals AI)30.8%15.9%Gemini 3.5 Flash
Excel Modeling Benchmark (Vals AI)63.5%57.9%Gemini 3.5 Flash
Terminal-Bench-Science (Vals AI)5.7%Not measuredOnly Gemini 3.5 Flash measured
τ²-Bench Telecom95.6%95.9%Kimi K2.6
APEX-Agents27.5%Not measuredOnly Gemini 3.5 Flash measured
OSWorld 2.0Not measured4.6%Only Kimi K2.6 measured
Vending-Bench 2$5,396$6,205Kimi K2.6
Neither model has a result on the other 20 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index130
Reasoning benchmarks for Gemini 3.5 Flash and Kimi K2.6
BenchmarkGemini 3.5 FlashKimi K2.6Leader
GPQA Diamond92.7%89.1%Gemini 3.5 Flash
MMMU Pro (Vals AI)88.3%86.3%Gemini 3.5 Flash
GPQA Diamond (Artificial Analysis run)92.2%91.1%Gemini 3.5 Flash
Humanity's Last Exam (Artificial Analysis run)42.7%37.5%Gemini 3.5 Flash
GPQA Diamond (Epoch AI run)92.8%90.8%Gemini 3.5 Flash
ARC-AGI92.5%Not measuredOnly Gemini 3.5 Flash measured
ARC-AGI-272.1%Not measuredOnly Gemini 3.5 Flash measured
SimpleBench76.7%Not measuredOnly Gemini 3.5 Flash measured
Chess puzzles45.0%20.0%Gemini 3.5 Flash
Mystery game puzzles32.0%18.0%Gemini 3.5 Flash
EBR-bench4.8%2.4%Gemini 3.5 Flash
LMArena Text: hard prompts14881470Gemini 3.5 Flash
LMArena Text: expert14951491Gemini 3.5 Flash
LMArena Text: hard prompts in English14831471Gemini 3.5 Flash
LMArena Vision: diagrams13231298Gemini 3.5 Flash
LMArena Vision: homework13301310Gemini 3.5 Flash
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index51
Math benchmarks for Gemini 3.5 Flash and Kimi K2.6
BenchmarkGemini 3.5 FlashKimi K2.6Leader
OTIS Mock AIME95.6%96.1%Kimi K2.6
FrontierMath, tiers 1 to 362.8%57.2%Gemini 3.5 Flash
FrontierMath, tier 426.8%25.6%Gemini 3.5 Flash
ProofBench31.0%16.0%Gemini 3.5 Flash
LMArena Text: math15041474Gemini 3.5 Flash
LMArena Text: mathematical work14951480Gemini 3.5 Flash
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index83
Knowledge benchmarks for Gemini 3.5 Flash and Kimi K2.6
BenchmarkGemini 3.5 FlashKimi K2.6Leader
MMLU Pro89.5%87.6%Gemini 3.5 Flash
LegalBench (Vals AI)83.6%84.7%Kimi K2.6
CaseLaw (Vals AI)Not measured61.2%Only Kimi K2.6 measured
CorpFin (Vals AI)64.7%66.7%Kimi K2.6
TaxEval (Vals AI)74.4%74.7%Kimi K2.6
MortgageTax (Vals AI)68.1%65.8%Gemini 3.5 Flash
MedCode (Vals AI)55.8%40.1%Gemini 3.5 Flash
SimpleQA Verified66.2%34.9%Gemini 3.5 Flash
LMArena Text: science14951468Gemini 3.5 Flash
LMArena Text: medicine and healthcare14831457Gemini 3.5 Flash
LMArena Text: legal and government14881462Gemini 3.5 Flash
LMArena Text: business and finance14671445Gemini 3.5 Flash
Neither model has a result on the other 5 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index44
Web design benchmarks for Gemini 3.5 Flash and Kimi K2.6
BenchmarkGemini 3.5 FlashKimi K2.6Leader
Design Arena: websites12681269Kimi K2.6
Design Arena: UI components12721266Gemini 3.5 Flash
Design Arena: game dev12631251Gemini 3.5 Flash
Design Arena: data viz12361249Kimi K2.6
Design Arena: 3D12441268Kimi K2.6
Design Arena: all code categories12661272Kimi K2.6
Design Arena: SVG12541181Gemini 3.5 Flash
Design Arena: ASCII art12531164Gemini 3.5 Flash
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index293
General benchmarks for Gemini 3.5 Flash and Kimi K2.6
BenchmarkGemini 3.5 FlashKimi K2.6Leader
Public Benefits Bench (Vals AI)59.5%56.6%Gemini 3.5 Flash
SAGE (Vals AI)49.9%50.2%Kimi K2.6
MedScribe (Vals AI)76.6%78.2%Kimi K2.6
Vals Multimodal Index62.9%56.4%Gemini 3.5 Flash
IFBench76.3%76.0%Gemini 3.5 Flash
Long context reasoning (AA-LCR)74.3%81.0%Kimi K2.6
DTBench94.7%90.9%Gemini 3.5 Flash
LMCA47.1%37.3%Gemini 3.5 Flash
Surface Evolver Bench58.1%Not measuredOnly Gemini 3.5 Flash measured
Furniture assemblyNot measured21.7%Only Kimi K2.6 measured
ExploitBenchNot measured18.4%Only Kimi K2.6 measured
LMArena Text14821455Gemini 3.5 Flash
LMArena Text: instruction following14671451Gemini 3.5 Flash
LMArena Text: creative writing14701434Gemini 3.5 Flash
LMArena Vision13081282Gemini 3.5 Flash
LMArena Text: English14811460Gemini 3.5 Flash
LMArena Text: non-English14751446Gemini 3.5 Flash
LMArena Text: Chinese15271520Gemini 3.5 Flash
LMArena Text: German14941451Gemini 3.5 Flash
LMArena Text: Japanese14861443Gemini 3.5 Flash
LMArena Text: Korean14481427Gemini 3.5 Flash
LMArena Text: French14901471Gemini 3.5 Flash
LMArena Text: Spanish14801464Gemini 3.5 Flash
LMArena Text: Russian14931446Gemini 3.5 Flash
LMArena Text: Polish15161438Gemini 3.5 Flash
LMArena Text: multi-turn14811453Gemini 3.5 Flash
LMArena Text: longer queries14831468Gemini 3.5 Flash
LMArena Text: writing and language14781439Gemini 3.5 Flash
LMArena Text: entertainment and media14591428Gemini 3.5 Flash
LMArena Vision: English13051287Gemini 3.5 Flash
LMArena Vision: Chinese13771346Gemini 3.5 Flash
LMArena Vision: reading text13171291Gemini 3.5 Flash
LMArena Vision: humor13211280Gemini 3.5 Flash
LMArena Vision: creative writing13011273Gemini 3.5 Flash
LMArena Document14631451Gemini 3.5 Flash
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 Gemini 3.5 Flash and Kimi K2.6
BenchmarkGemini 3.5 FlashKimi K2.6Leader
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

Gemini 3.5 Flash$0.0060Fits in one request
Kimi K2.6$0.0024Fits in one request

Kimi K2.6 costs less

Repository review

50K input + 3K output tokens

Gemini 3.5 Flash$0.102Fits in one request
Kimi K2.6$0.043Fits in one request

Kimi K2.6 costs less

Agent loop

200K input + 10K output tokens

Gemini 3.5 Flash$0.390Fits in one request
Kimi K2.6$0.164Fits in one request

Kimi K2.6 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 Gemini 3.5 Flash and Kimi K2.6
SpecificationGoogle Gemini 3.5 FlashMoonshotAI Kimi K2.6
MakerGoogleMoonshot AI
WeightsNo public weights listedOpen weights
ReleasedMay 19, 2026April 20, 2026
Context window1.05M262K
Input $/Mtok$1.50$0.65
Output $/Mtok$9.00$3.41
Coding index42.844.2
Independent measurements behind it11
Cost per solved task$1.21$0.35
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 3.5 Flash better than Kimi K2.6 for coding?

Gemini 3.5 Flash and Kimi K2.6 are level for coding, 42.8 against 44.2 on the Vibe Coding Index, so price and context decide. Pick Gemini 3.5 Flash when the context window is larger, 1.05M against 262K tokens, or when what matters is LiveCodeBench (Vals AI) or SWE-bench Verified (Vals AI), where it leads. Pick Kimi K2.6 when output tokens cost 2.6x less, or when a solved task costs $0.35 against $1.21.

Which is cheaper, Gemini 3.5 Flash or Kimi K2.6?

Gemini 3.5 Flash costs $1.50 per million input tokens and $9.00 per million output tokens; Kimi K2.6 costs $0.65 and $3.41. Per solved SWE-bench Verified task, Gemini 3.5 Flash costs $1.21 and Kimi K2.6 $0.35.

Which has the bigger context window, Gemini 3.5 Flash or Kimi K2.6?

Gemini 3.5 Flash, with 1.05M tokens against 262K.

How many benchmarks is the Gemini 3.5 Flash vs Kimi K2.6 comparison based on?

102 benchmarks have a result for both models as of October 21, 2026. Gemini 3.5 Flash's coding index rests on 1 independent benchmark and Kimi K2.6's on 1. Where only one model has a result, the page says so instead of naming a winner.

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