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DeepSeek V4 Flash 0423 vs Kimi K2.5

Updated October 21, 2026. 45 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace DeepSeek V4 Flash 0423 Replace Kimi K2.5
DeepSeek V4 Flash 0423DeepSeek
Coding
54.6
Overall
24.4
Output $/M
$0.182
9
Kimi K2.5Moonshot AI
Coding
58.5
Overall
23.5
Output $/M
$2.50
36
vs boards won of 45 shared

Decision reading

Pick Kimi K2.5 for coding: it scores 58.5 on the Vibe Coding Index against 54.6 for DeepSeek V4 Flash 0423.

Pick DeepSeek V4 Flash 0423 when output tokens cost 13.7x less, or when the context window is larger, 1.05M against 262K tokens.

Model ADeepSeek V4 Flash 0423DeepSeek54.6/1001 independent benchmarkNo cost per solved taskModel BKimi K2.5Moonshot AI58.5/1002 independent benchmarks$0.24 per solved task
Shared results
45
DeepSeek V4 Flash 0423 only
3
Kimi K2.5 only
53
Like-for-like categories
7 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
DeepSeek V4 Flash 0423 54.6 from 1 benchmark, Kimi K2.5 58.5 from 2 benchmarks.
Widest category
Coding, 10.8 points apart on average over 8 shared benchmarks.
Widest single gap
LMArena WebDev: React: DeepSeek V4 Flash 0423 1585 against Kimi K2.5 1429, 26.0 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash 0423 $0.182 against Kimi K2.5 $2.50 per million output tokens, 13.7x apart.
Context window
DeepSeek V4 Flash 0423 takes 1.05M tokens, Kimi K2.5 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
CategoryDeepSeek V4 Flash 0423BarsKimi K2.5Ties
Coding53
Intelligence11
Reasoning04
Math02
Knowledge13
Web design17
General116
All shared boards936
CodingLike-for-likeFour of these boards feed the Vibe Coding Index53
Coding benchmarks for DeepSeek V4 Flash 0423 and Kimi K2.5
BenchmarkDeepSeek V4 Flash 0423Kimi K2.5Leader
SWE-bench VerifiedNot measured70.8%Only Kimi K2.5 measured
SWE-bench MultilingualNot measured67.3%Only Kimi K2.5 measured
LMArena WebDev15821437DeepSeek V4 Flash 0423
AA Coding Index52.046.8DeepSeek V4 Flash 0423
LiveCodeBench (Vals AI)Not measured83.9%Only Kimi K2.5 measured
SWE-bench Verified (Vals AI)Not measured70.0%Only Kimi K2.5 measured
Vibe Code Bench (Vals AI)Not measured17.5%Only Kimi K2.5 measured
Code migration (Vals AI)Not measured7.0%Only Kimi K2.5 measured
Terminal-Bench 2.1 (Vals AI)Not measured42.0%Only Kimi K2.5 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured34.8%Only Kimi K2.5 measured
Terminal-BenchNot measured43.2%Only Kimi K2.5 measured
WeirdML45.6%45.6%DeepSeek V4 Flash 0423
ALE-Bench678.2821.6Kimi K2.5
LMArena Text: coding14571483Kimi K2.5
LMArena Text: software and IT14531471Kimi K2.5
LMArena WebDev: React15851429DeepSeek V4 Flash 0423
LMArena WebDev: HTML15581426DeepSeek V4 Flash 0423
LMArena WebDev: from an imageNot measured1439Only Kimi K2.5 measured
Neither model has a result on the other 20 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
Intelligence benchmarks for DeepSeek V4 Flash 0423 and Kimi K2.5
BenchmarkDeepSeek V4 Flash 0423Kimi K2.5Leader
AA Intelligence Index24.423.5DeepSeek V4 Flash 0423
Epoch Capabilities Index146.1148.1Kimi K2.5
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
Agentic work benchmarks for DeepSeek V4 Flash 0423 and Kimi K2.5
BenchmarkDeepSeek V4 Flash 0423Kimi K2.5Leader
AA Agentic Index26.3Not measuredOnly DeepSeek V4 Flash 0423 measured
Design Arena: agents building web appsNot measured1136Only Kimi K2.5 measured
Design Arena: agents building full-stack appsNot measured1114Only Kimi K2.5 measured
Design Arena: agents building mobile appsNot measured1147Only Kimi K2.5 measured
Design Arena: agents building Android appsNot measured1124Only Kimi K2.5 measured
Design Arena: agents building Godot gamesNot measured1219Only Kimi K2.5 measured
Finance Agent (Vals AI)Not measured35.8%Only Kimi K2.5 measured
Legal Research Bench (Vals AI)Not measured15.9%Only Kimi K2.5 measured
Excel Modeling Benchmark (Vals AI)Not measured28.5%Only Kimi K2.5 measured
τ²-Bench TelecomNot measured95.9%Only Kimi K2.5 measured
OSWorldNot measured63.3%Only Kimi K2.5 measured
Vending-Bench 2Not measured$1,198Only Kimi K2.5 measured
Neither model has a result on the other 27 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
Reasoning benchmarks for DeepSeek V4 Flash 0423 and Kimi K2.5
BenchmarkDeepSeek V4 Flash 0423Kimi K2.5Leader
GPQA DiamondNot measured84.1%Only Kimi K2.5 measured
MMMU Pro (Vals AI)Not measured84.3%Only Kimi K2.5 measured
GPQA Diamond (Artificial Analysis run)Not measured87.9%Only Kimi K2.5 measured
Humanity's Last Exam (Artificial Analysis run)Not measured30.7%Only Kimi K2.5 measured
ARC-AGINot measured65.3%Only Kimi K2.5 measured
ARC-AGI-2Not measured11.8%Only Kimi K2.5 measured
SimpleBench46.3%46.8%Kimi K2.5
LMArena Text: hard prompts14441453Kimi K2.5
LMArena Text: expert14411466Kimi K2.5
LMArena Text: hard prompts in English14491460Kimi K2.5
LMArena Vision: diagramsNot measured1282Only Kimi K2.5 measured
LMArena Vision: homeworkNot measured1297Only Kimi K2.5 measured
Neither model has a result on the other 9 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for DeepSeek V4 Flash 0423 and Kimi K2.5
BenchmarkDeepSeek V4 Flash 0423Kimi K2.5Leader
AIMENot measured95.6%Only Kimi K2.5 measured
LMArena Text: math14261470Kimi K2.5
LMArena Text: mathematical work14321473Kimi K2.5
Neither model has a result on the other 10 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index13
Knowledge benchmarks for DeepSeek V4 Flash 0423 and Kimi K2.5
BenchmarkDeepSeek V4 Flash 0423Kimi K2.5Leader
MMLU ProNot measured85.9%Only Kimi K2.5 measured
CaseLaw (Vals AI)Not measured58.7%Only Kimi K2.5 measured
CorpFin (Vals AI)Not measured68.3%Only Kimi K2.5 measured
TaxEval (Vals AI)Not measured74.2%Only Kimi K2.5 measured
MortgageTax (Vals AI)Not measured66.5%Only Kimi K2.5 measured
MedQA (Vals AI)Not measured94.4%Only Kimi K2.5 measured
MedCode (Vals AI)Not measured39.3%Only Kimi K2.5 measured
SimpleQA VerifiedNot measured34.3%Only Kimi K2.5 measured
LMArena Text: science14461459Kimi K2.5
LMArena Text: medicine and healthcare14481448DeepSeek V4 Flash 0423
LMArena Text: legal and government14391441Kimi K2.5
LMArena Text: business and finance14251427Kimi K2.5
Neither model has a result on the other 5 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index17
Web design benchmarks for DeepSeek V4 Flash 0423 and Kimi K2.5
BenchmarkDeepSeek V4 Flash 0423Kimi K2.5Leader
Design Arena: websites12081249Kimi K2.5
Design Arena: UI components11641236Kimi K2.5
Design Arena: game dev11971207Kimi K2.5
Design Arena: data viz11271219Kimi K2.5
Design Arena: 3D11891205Kimi K2.5
Design Arena: all code categories12051236Kimi K2.5
Design Arena: SVG11551149DeepSeek V4 Flash 0423
Design Arena: ASCII art11091165Kimi K2.5
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index116
General benchmarks for DeepSeek V4 Flash 0423 and Kimi K2.5
BenchmarkDeepSeek V4 Flash 0423Kimi K2.5Leader
SAGE (Vals AI)Not measured49.9%Only Kimi K2.5 measured
MedScribe (Vals AI)Not measured76.4%Only Kimi K2.5 measured
IFBenchNot measured70.2%Only Kimi K2.5 measured
Long context reasoning (AA-LCR)Not measured78.0%Only Kimi K2.5 measured
DTBench86.4%Not measuredOnly DeepSeek V4 Flash 0423 measured
LMCA35.9%Not measuredOnly DeepSeek V4 Flash 0423 measured
Fiction.LiveBenchNot measured86.1%Only Kimi K2.5 measured
CL-benchNot measured19.3%Only Kimi K2.5 measured
CL-bench LifeNot measured13.2%Only Kimi K2.5 measured
LMArena Text14321445Kimi K2.5
LMArena Text: instruction following14211431Kimi K2.5
LMArena Text: creative writing14031422Kimi K2.5
LMArena VisionNot measured1269Only Kimi K2.5 measured
LMArena Text: English14411453Kimi K2.5
LMArena Text: non-English14191433Kimi K2.5
LMArena Text: Chinese14631494Kimi K2.5
LMArena Text: German14191441Kimi K2.5
LMArena Text: Japanese13891423Kimi K2.5
LMArena Text: Korean13831412Kimi K2.5
LMArena Text: French14391454Kimi K2.5
LMArena Text: Spanish14361450Kimi K2.5
LMArena Text: Russian14271435Kimi K2.5
LMArena Text: Polish14361445Kimi K2.5
LMArena Text: multi-turn14491444DeepSeek V4 Flash 0423
LMArena Text: longer queries14341445Kimi K2.5
LMArena Text: writing and language14101425Kimi K2.5
LMArena Text: entertainment and media14001417Kimi K2.5
LMArena Vision: EnglishNot measured1274Only Kimi K2.5 measured
LMArena Vision: ChineseNot measured1328Only Kimi K2.5 measured
LMArena Vision: reading textNot measured1276Only Kimi K2.5 measured
LMArena Vision: humorNot measured1284Only Kimi K2.5 measured
LMArena Vision: captioningNot measured1257Only Kimi K2.5 measured
LMArena Vision: recognizing thingsNot measured1285Only Kimi K2.5 measured
LMArena Vision: creative writingNot measured1269Only Kimi K2.5 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 DeepSeek V4 Flash 0423 and Kimi K2.5
BenchmarkDeepSeek V4 Flash 0423Kimi K2.5Leader
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

DeepSeek V4 Flash 0423$0.0002Fits in one request
Kimi K2.5$0.0018Fits in one request

DeepSeek V4 Flash 0423 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Flash 0423$0.0051Fits in one request
Kimi K2.5$0.033Fits in one request

DeepSeek V4 Flash 0423 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Flash 0423$0.020Fits in one request
Kimi K2.5$0.125Fits in one request

DeepSeek V4 Flash 0423 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 DeepSeek V4 Flash 0423 and Kimi K2.5
SpecificationDeepSeek V4 Flash 0423MoonshotAI Kimi K2.5
MakerDeepSeekMoonshot AI
WeightsOpen weightsOpen weights
ReleasedApril 24, 2026January 27, 2026
Context window1.05M262K
Input $/Mtok$0.091$0.50
Output $/Mtok$0.182$2.50
Coding index54.658.5
Independent measurements behind it12
Cost per solved taskNot computable$0.24
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Flash 0423 better than Kimi K2.5 for coding?

Pick Kimi K2.5 for coding: it scores 58.5 on the Vibe Coding Index against 54.6 for DeepSeek V4 Flash 0423. Pick DeepSeek V4 Flash 0423 when output tokens cost 13.7x less, or when the context window is larger, 1.05M against 262K tokens.

Which is cheaper, DeepSeek V4 Flash 0423 or Kimi K2.5?

DeepSeek V4 Flash 0423 costs $0.091 per million input tokens and $0.182 per million output tokens; Kimi K2.5 costs $0.50 and $2.50. Cost per solved task is known for Kimi K2.5 only.

Which has the bigger context window, DeepSeek V4 Flash 0423 or Kimi K2.5?

DeepSeek V4 Flash 0423, with 1.05M tokens against 262K.

How many benchmarks is the DeepSeek V4 Flash 0423 vs Kimi K2.5 comparison based on?

45 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4 Flash 0423's coding index rests on 1 independent benchmark and Kimi K2.5's on 2. Where only one model has a result, the page says so instead of naming a winner.

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