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Gemini 2.5 Flash vs Kimi K2 0711

Updated October 21, 2026. 20 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Gemini 2.5 FlashGoogle
Coding
28.7
Overall
15.5
Output $/M
$2.50
15
Kimi K2 0711Moonshot AI
Coding
64.7
Overall
12.7
Output $/M
$2.30
5
vs boards won of 20 shared

Decision reading

Pick Kimi K2 0711 for coding: it scores 64.7 on the Vibe Coding Index against 28.7 for Gemini 2.5 Flash.

Pick Gemini 2.5 Flash when the context window is larger, 1.05M against 131K tokens, or when what matters is LiveCodeBench (Artificial Analysis run) or AA Intelligence Index, where it leads.

Shared results
20
Gemini 2.5 Flash only
49
Kimi K2 0711 only
16
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 2.5 Flash 28.7 from 1 benchmark, Kimi K2 0711 64.7 from 2 benchmarks.
Widest category
Agentic work, 29.5 points apart on average over 1 shared benchmark.
Widest single gap
SWE-bench Verified: Gemini 2.5 Flash 28.7% against Kimi K2 0711 71.2%, 42.5 points apart on a 0 to 100 scale.
Output price
Gemini 2.5 Flash $2.50 against Kimi K2 0711 $2.30 per million output tokens, 1.1x apart.
Context window
Gemini 2.5 Flash takes 1.05M tokens, Kimi K2 0711 131K.

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 2.5 FlashBarsKimi K2 0711Ties
Coding13
Intelligence20
Agentic work01
Reasoning30
Math20
Knowledge10
Web design41
General20
All shared boards155
CodingLike-for-likeFour of these boards feed the Vibe Coding Index13
Coding benchmarks for Gemini 2.5 Flash and Kimi K2 0711
BenchmarkGemini 2.5 FlashKimi K2 0711Leader
Aider polyglotNot measured59.1%Only Kimi K2 0711 measured
SWE-bench Verified28.7%71.2%Kimi K2 0711
LiveCodeBench (Vals AI)Not measured70.5%Only Kimi K2 0711 measured
LiveCodeBench (Artificial Analysis run)69.5%55.6%Gemini 2.5 Flash
Terminal-Bench Hard (Artificial Analysis run)13.6%15.9%Kimi K2 0711
Terminal-Bench17.1%27.8%Kimi K2 0711
GSO-BenchNot measured4.9%Only Kimi K2 0711 measured
WeirdMLNot measured39.4%Only Kimi K2 0711 measured
LMArena Text: coding1423Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: software and IT1425Not measuredOnly Gemini 2.5 Flash measured
Neither model has a result on the other 28 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Gemini 2.5 Flash and Kimi K2 0711
BenchmarkGemini 2.5 FlashKimi K2 0711Leader
AA Intelligence Index15.512.7Gemini 2.5 Flash
Epoch Capabilities Index142.9140.0Gemini 2.5 Flash
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Gemini 2.5 Flash and Kimi K2 0711
BenchmarkGemini 2.5 FlashKimi K2 0711Leader
τ²-Bench Telecom31.6%61.1%Kimi K2 0711
BALROG33.5%Not measuredOnly Gemini 2.5 Flash measured
Vending-Bench 2$549Not measuredOnly Gemini 2.5 Flash measured
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
Reasoning benchmarks for Gemini 2.5 Flash and Kimi K2 0711
BenchmarkGemini 2.5 FlashKimi K2 0711Leader
GPQA DiamondNot measured71.5%Only Kimi K2 0711 measured
GPQA Diamond (Artificial Analysis run)79.0%76.6%Gemini 2.5 Flash
Humanity's Last Exam (Artificial Analysis run)12.1%7.4%Gemini 2.5 Flash
ARC-AGI33.3%Not measuredOnly Gemini 2.5 Flash measured
ARC-AGI-22.5%Not measuredOnly Gemini 2.5 Flash measured
SimpleBench41.2%26.3%Gemini 2.5 Flash
LMArena Text: hard prompts1422Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: expert1426Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: hard prompts in English1420Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: diagrams1245Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: homework1244Not measuredOnly Gemini 2.5 Flash measured
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for Gemini 2.5 Flash and Kimi K2 0711
BenchmarkGemini 2.5 FlashKimi K2 0711Leader
AIMENot measured62.7%Only Kimi K2 0711 measured
MATH 500 (Vals AI)Not measured94.2%Only Kimi K2 0711 measured
MGSM (Vals AI)Not measured91.0%Only Kimi K2 0711 measured
AA Math Index73.357.0Gemini 2.5 Flash
AIME 2025 (Artificial Analysis run)73.3%57.0%Gemini 2.5 Flash
LMArena Text: math1411Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: mathematical work1422Not measuredOnly Gemini 2.5 Flash measured
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
Knowledge benchmarks for Gemini 2.5 Flash and Kimi K2 0711
BenchmarkGemini 2.5 FlashKimi K2 0711Leader
MMLU ProNot measured79.4%Only Kimi K2 0711 measured
LegalBench (Vals AI)Not measured81.5%Only Kimi K2 0711 measured
CorpFin (Vals AI)Not measured50.4%Only Kimi K2 0711 measured
TaxEval (Vals AI)Not measured70.2%Only Kimi K2 0711 measured
MedQA (Vals AI)Not measured84.0%Only Kimi K2 0711 measured
MedCode (Vals AI)40.4%Not measuredOnly Gemini 2.5 Flash measured
MMLU Pro (Artificial Analysis run)83.2%82.4%Gemini 2.5 Flash
LMArena Text: science1433Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: medicine and healthcare1428Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: legal and government1430Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: business and finance1404Not measuredOnly Gemini 2.5 Flash measured
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index41
Web design benchmarks for Gemini 2.5 Flash and Kimi K2 0711
BenchmarkGemini 2.5 FlashKimi K2 0711Leader
Design Arena: websites10741050Gemini 2.5 Flash
Design Arena: UI components10051030Kimi K2 0711
Design Arena: game dev1005974Gemini 2.5 Flash
Design Arena: data viz10601018Gemini 2.5 Flash
Design Arena: 3D1021Not measuredOnly Gemini 2.5 Flash measured
Design Arena: all code categories10591034Gemini 2.5 Flash
Design Arena: SVG1018Not measuredOnly Gemini 2.5 Flash measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
General benchmarks for Gemini 2.5 Flash and Kimi K2 0711
BenchmarkGemini 2.5 FlashKimi K2 0711Leader
SAGE (Vals AI)44.8%Not measuredOnly Gemini 2.5 Flash measured
MedScribe (Vals AI)83.0%Not measuredOnly Gemini 2.5 Flash measured
IFBench50.3%41.5%Gemini 2.5 Flash
Long context reasoning (AA-LCR)65.3%53.0%Gemini 2.5 Flash
DTBench76.5%Not measuredOnly Gemini 2.5 Flash measured
LMCA27.5%Not measuredOnly Gemini 2.5 Flash measured
Fiction.LiveBenchNot measured61.1%Only Kimi K2 0711 measured
Creative writing (Lech Mazur)Not measured85.6%Only Kimi K2 0711 measured
CL-benchNot measured11.9%Only Kimi K2 0711 measured
LMArena Text1417Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: instruction following1405Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: creative writing1400Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision1235Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: English1418Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: non-English1409Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: Chinese1449Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: German1417Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: Japanese1396Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: Korean1385Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: French1432Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: Spanish1422Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: Russian1415Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: Polish1413Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: multi-turn1408Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: longer queries1419Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: writing and language1405Not measuredOnly Gemini 2.5 Flash measured
LMArena Text: entertainment and media1393Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: English1239Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: Chinese1284Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: reading text1237Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: humor1225Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: captioning1277Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: recognizing things1252Not measuredOnly Gemini 2.5 Flash measured
LMArena Vision: creative writing1241Not measuredOnly Gemini 2.5 Flash measured
Neither model has a result on the other 12 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemini 2.5 Flash and Kimi K2 0711
BenchmarkGemini 2.5 FlashKimi K2 0711Leader
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 2.5 Flash$0.0015Fits in one request
Kimi K2 0711$0.0017Fits in one request

Gemini 2.5 Flash costs less

Repository review

50K input + 3K output tokens

Gemini 2.5 Flash$0.022Fits in one request
Kimi K2 0711$0.035Fits in one request

Gemini 2.5 Flash costs less

Agent loop

200K input + 10K output tokens

Gemini 2.5 Flash$0.085Fits in one request
Kimi K2 0711$0.137Exceeds the context window

Gemini 2.5 Flash 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 2.5 Flash and Kimi K2 0711
SpecificationGoogle Gemini 2.5 FlashMoonshotAI Kimi K2 0711
MakerGoogleMoonshot AI
WeightsNo public weights listedOpen weights
ReleasedJune 17, 2025July 11, 2025
Context window1.05M131K
Input $/Mtok$0.30$0.57
Output $/Mtok$2.50$2.30
Coding index28.764.7
Independent measurements behind it12
Cost per solved task$0.466Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 2.5 Flash better than Kimi K2 0711 for coding?

Pick Kimi K2 0711 for coding: it scores 64.7 on the Vibe Coding Index against 28.7 for Gemini 2.5 Flash. Pick Gemini 2.5 Flash when the context window is larger, 1.05M against 131K tokens, or when what matters is LiveCodeBench (Artificial Analysis run) or AA Intelligence Index, where it leads.

Which is cheaper, Gemini 2.5 Flash or Kimi K2 0711?

Gemini 2.5 Flash costs $0.30 per million input tokens and $2.50 per million output tokens; Kimi K2 0711 costs $0.57 and $2.30. Cost per solved task is known for Gemini 2.5 Flash only.

Which has the bigger context window, Gemini 2.5 Flash or Kimi K2 0711?

Gemini 2.5 Flash, with 1.05M tokens against 131K.

How many benchmarks is the Gemini 2.5 Flash vs Kimi K2 0711 comparison based on?

20 benchmarks have a result for both models as of October 21, 2026. Gemini 2.5 Flash's coding index rests on 1 independent benchmark and Kimi K2 0711's on 2. Where only one model has a result, the page says so instead of naming a winner.

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