Enter opens the highlighted result. Esc closes.

GPT-5 Pro vs Kimi K2.5

Updated October 21, 2026. 5 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

GPT-5 ProOpenAI
Coding
No data
Overall
No data
Output $/M
$120.00
5
Kimi K2.5Moonshot AI
Coding
38.6
Overall
23.5
Output $/M
$2.85
0
vs boards won of 5 shared

Decision reading

Only Kimi K2.5 has a coding score, 38.6 on the Vibe Coding Index; GPT-5 Pro has none, so the two cannot be ranked on coding.

GPT-5 Pro has the edge where the context window is larger, 400K against 262K tokens, and where what matters is WeirdML or Epoch Capabilities Index, where it leads.

Shared results
5
GPT-5 Pro only
3
Kimi K2.5 only
93
Like-for-like categories
3 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
GPT-5 Pro not benchmarked, Kimi K2.5 38.6 from 3 benchmarks.
Widest category
Coding, 14.8 points apart on average over 1 shared benchmark.
Widest single gap
SimpleBench: GPT-5 Pro 61.6% against Kimi K2.5 46.8%, 14.8 points apart on a 0 to 100 scale.
Output price
GPT-5 Pro $120.00 against Kimi K2.5 $2.85 per million output tokens, 42.1x apart.
Context window
GPT-5 Pro takes 400K 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
CategoryGPT-5 ProBarsKimi K2.5Ties
Coding10
Intelligence10
Reasoning30
All shared boards50
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
Coding benchmarks for GPT-5 Pro and Kimi K2.5
BenchmarkGPT-5 ProKimi K2.5Leader
SWE-bench VerifiedNot measured70.8%Only Kimi K2.5 measured
SWE-bench MultilingualNot measured67.3%Only Kimi K2.5 measured
LMArena WebDevNot measured1437Only Kimi K2.5 measured
AA Coding IndexNot measured46.8Only Kimi K2.5 measured
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
WeirdML60.4%45.6%GPT-5 Pro
ALE-BenchNot measured821.6Only Kimi K2.5 measured
LMArena Text: codingNot measured1483Only Kimi K2.5 measured
LMArena Text: software and ITNot measured1471Only Kimi K2.5 measured
LMArena WebDev: ReactNot measured1429Only Kimi K2.5 measured
LMArena WebDev: HTMLNot measured1426Only Kimi K2.5 measured
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 index10
Intelligence benchmarks for GPT-5 Pro and Kimi K2.5
BenchmarkGPT-5 ProKimi K2.5Leader
AA Intelligence IndexNot measured23.5Only Kimi K2.5 measured
Epoch Capabilities Index150.6148.1GPT-5 Pro
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
Agentic work benchmarks for GPT-5 Pro and Kimi K2.5
BenchmarkGPT-5 ProKimi K2.5Leader
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 measured1125Only 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 28 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
Reasoning benchmarks for GPT-5 Pro and Kimi K2.5
BenchmarkGPT-5 ProKimi 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-AGI70.2%65.3%GPT-5 Pro
ARC-AGI-218.3%11.8%GPT-5 Pro
SimpleBench61.6%46.8%GPT-5 Pro
Chess puzzles48.0%Not measuredOnly GPT-5 Pro measured
LMArena Text: hard promptsNot measured1453Only Kimi K2.5 measured
LMArena Text: expertNot measured1466Only Kimi K2.5 measured
LMArena Text: hard prompts in EnglishNot measured1460Only Kimi K2.5 measured
LMArena Vision: diagramsNot measured1282Only Kimi K2.5 measured
LMArena Vision: homeworkNot measured1297Only Kimi K2.5 measured
Neither model has a result on the other 8 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Math benchmarks for GPT-5 Pro and Kimi K2.5
BenchmarkGPT-5 ProKimi K2.5Leader
AIMENot measured95.6%Only Kimi K2.5 measured
FrontierMath, tiers 1 to 355.8%Not measuredOnly GPT-5 Pro measured
FrontierMath, tier 419.5%Not measuredOnly GPT-5 Pro measured
LMArena Text: mathNot measured1470Only Kimi K2.5 measured
LMArena Text: mathematical workNot measured1473Only Kimi K2.5 measured
Neither model has a result on the other 8 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
Knowledge benchmarks for GPT-5 Pro and Kimi K2.5
BenchmarkGPT-5 ProKimi 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: scienceNot measured1459Only Kimi K2.5 measured
LMArena Text: medicine and healthcareNot measured1448Only Kimi K2.5 measured
LMArena Text: legal and governmentNot measured1441Only Kimi K2.5 measured
LMArena Text: business and financeNot measured1427Only Kimi K2.5 measured
Neither model has a result on the other 5 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for GPT-5 Pro and Kimi K2.5
BenchmarkGPT-5 ProKimi K2.5Leader
Design Arena: websitesNot measured1249Only Kimi K2.5 measured
Design Arena: UI componentsNot measured1236Only Kimi K2.5 measured
Design Arena: game devNot measured1207Only Kimi K2.5 measured
Design Arena: data vizNot measured1218Only Kimi K2.5 measured
Design Arena: 3DNot measured1205Only Kimi K2.5 measured
Design Arena: all code categoriesNot measured1236Only Kimi K2.5 measured
Design Arena: SVGNot measured1149Only Kimi K2.5 measured
Design Arena: ASCII artNot measured1165Only Kimi K2.5 measured
Neither model has a result on the other 1 board here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index32 boards, none shared
General benchmarks for GPT-5 Pro and Kimi K2.5
BenchmarkGPT-5 ProKimi 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
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 TextNot measured1445Only Kimi K2.5 measured
LMArena Text: instruction followingNot measured1431Only Kimi K2.5 measured
LMArena Text: creative writingNot measured1422Only Kimi K2.5 measured
LMArena VisionNot measured1269Only Kimi K2.5 measured
LMArena Text: EnglishNot measured1453Only Kimi K2.5 measured
LMArena Text: non-EnglishNot measured1433Only Kimi K2.5 measured
LMArena Text: ChineseNot measured1494Only Kimi K2.5 measured
LMArena Text: GermanNot measured1441Only Kimi K2.5 measured
LMArena Text: JapaneseNot measured1423Only Kimi K2.5 measured
LMArena Text: KoreanNot measured1412Only Kimi K2.5 measured
LMArena Text: FrenchNot measured1454Only Kimi K2.5 measured
LMArena Text: SpanishNot measured1450Only Kimi K2.5 measured
LMArena Text: RussianNot measured1435Only Kimi K2.5 measured
LMArena Text: PolishNot measured1445Only Kimi K2.5 measured
LMArena Text: multi-turnNot measured1444Only Kimi K2.5 measured
LMArena Text: longer queriesNot measured1445Only Kimi K2.5 measured
LMArena Text: writing and languageNot measured1425Only Kimi K2.5 measured
LMArena Text: entertainment and mediaNot measured1417Only Kimi K2.5 measured
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 14 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-5 Pro and Kimi K2.5
BenchmarkGPT-5 ProKimi 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

GPT-5 Pro$0.075Fits in one request
Kimi K2.5$0.0020Fits in one request

Kimi K2.5 costs less

Repository review

50K input + 3K output tokens

GPT-5 Pro$1.11Fits in one request
Kimi K2.5$0.035Fits in one request

Kimi K2.5 costs less

Agent loop

200K input + 10K output tokens

GPT-5 Pro$4.20Fits in one request
Kimi K2.5$0.135Fits in one request

Kimi K2.5 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 GPT-5 Pro and Kimi K2.5
SpecificationOpenAI GPT-5 ProMoonshotAI Kimi K2.5
MakerOpenAIMoonshot AI
WeightsNo public weights listedOpen weights
ReleasedOctober 6, 2025January 27, 2026
Context window400K262K
Input $/Mtok$15.00$0.532
Output $/Mtok$120.00$2.85
Coding indexNot benchmarked38.6
Independent measurements behind it03
Cost per solved taskNot computable$0.24
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-5 Pro better than Kimi K2.5 for coding?

Only Kimi K2.5 has a coding score, 38.6 on the Vibe Coding Index; GPT-5 Pro has none, so the two cannot be ranked on coding. GPT-5 Pro has the edge where the context window is larger, 400K against 262K tokens, and where what matters is WeirdML or Epoch Capabilities Index, where it leads.

Which is cheaper, GPT-5 Pro or Kimi K2.5?

GPT-5 Pro costs $15.00 per million input tokens and $120.00 per million output tokens; Kimi K2.5 costs $0.532 and $2.85. Cost per solved task is known for Kimi K2.5 only.

Which has the bigger context window, GPT-5 Pro or Kimi K2.5?

GPT-5 Pro, with 400K tokens against 262K.

How many benchmarks is the GPT-5 Pro vs Kimi K2.5 comparison based on?

5 benchmarks have a result for both models as of October 21, 2026. GPT-5 Pro's coding index rests on 0 independent benchmarks and Kimi K2.5's on 3. Where only one model has a result, the page says so instead of naming a winner.

Compare next