GPT-5.2 vs Kimi K2.7 Code
Updated October 21, 2026. 36 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick GPT-5.2 for coding: it scores 58.9 on the Vibe Coding Index against 39.1 for Kimi K2.7 Code.
Pick Kimi K2.7 Code when output tokens cost 4.2x less, or when a solved task costs $0.35 against $1.91.
- Shared results
- 36
- GPT-5.2 only
- 75
- Kimi K2.7 Code only
- 15
- 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.
Coding
Vibe Coding Index, four public coding benchmarks
GPT-5.2
GPT-5.2 scores 58.9 against 39.1.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.2
GPT-5.2 leads, 30.4 against 25.8.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Kimi K2.7 Code has a AA Agentic Index result, 21.0.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5.2 has a GPQA Diamond result, 91.7%.
Directional only
Math
AIME
No call
Only GPT-5.2 has a AIME result, 96.9%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.2 has a MMLU Pro result, 86.2%.
Directional only
Web design
Design Arena: websites
Kimi K2.7 Code
Kimi K2.7 Code leads, 1264 against 1196.
Same board, both measured
Long documents
Listed context window
GPT-5.2
GPT-5.2 takes 400K tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Kimi K2.7 Code
GPT-5.2 $0.0088, Kimi K2.7 Code $0.0023 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Kimi K2.7 Code
GPT-5.2 $1.91, Kimi K2.7 Code $0.35.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5.2 58.9 from 2 benchmarks, Kimi K2.7 Code 39.1 from 1 benchmark.
- Widest category
- Math, 11.1 points apart on average over 3 shared benchmarks.
- Widest single gap
- Chess puzzles: GPT-5.2 48.0% against Kimi K2.7 Code 14.0%, 34.0 points apart on a 0 to 100 scale.
- Output price
- GPT-5.2 $14.00 against Kimi K2.7 Code $3.35 per million output tokens, 4.2x apart.
- Context window
- GPT-5.2 takes 400K tokens, Kimi K2.7 Code 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.
| Category | GPT-5.2 | Bars | Kimi K2.7 Code | Ties |
|---|---|---|---|---|
| Coding | 5 | 3 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 0 | 7 | ||
| Reasoning | 4 | 1 | ||
| Math | 3 | 0 | ||
| Knowledge | 1 | 0 | ||
| Web design | 0 | 8 | ||
| General | 2 | 0 | ||
| All shared boards | 17 | 19 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index53
| Benchmark | GPT-5.2 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| SWE-bench Verified | 72.8% | Not measured | Only GPT-5.2 measured |
| SWE-bench Multilingual | 66.7% | Not measured | Only GPT-5.2 measured |
| LMArena WebDev | 1417 | 1474 | Kimi K2.7 Code |
| AA Coding Index | Not measured | 60.8 | Only Kimi K2.7 Code measured |
| LiveCodeBench (Vals AI) | 85.4% | 82.0% | GPT-5.2 |
| SWE-bench Verified (Vals AI) | 75.8% | 78.2% | Kimi K2.7 Code |
| Vibe Code Bench (Vals AI) | 53.5% | 47.2% | GPT-5.2 |
| Code migration (Vals AI) | Not measured | 25.4% | Only Kimi K2.7 Code measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Kimi K2.7 Code measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 67.0% | Only Kimi K2.7 Code measured |
| SkillsBench (Vals AI) | Not measured | 50.0% | Only Kimi K2.7 Code measured |
| LiveCodeBench (Artificial Analysis run) | 89.4% | Not measured | Only GPT-5.2 measured |
| SciCode | Not measured | 47.8% | Only Kimi K2.7 Code measured |
| Terminal-Bench Hard (Artificial Analysis run) | 47.0% | 44.7% | GPT-5.2 |
| Terminal-Bench | 64.9% | Not measured | Only GPT-5.2 measured |
| FrontierCode | Not measured | 30.1% | Only Kimi K2.7 Code measured |
| GSO-Bench | 27.5% | Not measured | Only GPT-5.2 measured |
| WeirdML | 72.2% | 54.1% | GPT-5.2 |
| ALE-Bench | 1293.5 | 886.2 | GPT-5.2 |
| LMArena Text: coding | 1442 | Not measured | Only GPT-5.2 measured |
| LMArena Text: software and IT | 1434 | Not measured | Only GPT-5.2 measured |
| LMArena WebDev: React | Not measured | 1475 | Only Kimi K2.7 Code measured |
| LMArena WebDev: HTML | 1427 | 1451 | Kimi K2.7 Code |
| LMArena WebDev: from an image | Not measured | 1513 | Only Kimi K2.7 Code measured |
| Neither model has a result on the other 14 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.2 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| AA Intelligence Index | 30.4 | 25.8 | GPT-5.2 |
| Epoch Capabilities Index | 153.7 | 150.1 | GPT-5.2 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index07
| Benchmark | GPT-5.2 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 21.0 | Only Kimi K2.7 Code measured |
| Design Arena: agents building web apps | 1086 | 1176 | Kimi K2.7 Code |
| Design Arena: agents building full-stack apps | 1043 | 1175 | Kimi K2.7 Code |
| Design Arena: agents building mobile apps | 1094 | 1143 | Kimi K2.7 Code |
| Design Arena: agents building Android apps | 1064 | 1143 | Kimi K2.7 Code |
| Design Arena: agents building Godot games | 1142 | 1147 | Kimi K2.7 Code |
| Design Arena: agents building games | Not measured | 1130 | Only Kimi K2.7 Code measured |
| Design Arena: HTML slides | Not measured | 1201 | Only Kimi K2.7 Code measured |
| Design Arena: PowerPoint slides | Not measured | 1154 | Only Kimi K2.7 Code measured |
| τ²-Bench Telecom | 84.8% | 90.1% | Kimi K2.7 Code |
| APEX-Agents | Not measured | 37.6% | Only Kimi K2.7 Code measured |
| METR time horizons | 75.3% | Not measured | Only GPT-5.2 measured |
| Remote Labor Index | 2.5% | Not measured | Only GPT-5.2 measured |
| GDPval | 49.7% | Not measured | Only GPT-5.2 measured |
| DeepResearch Bench | 41.1% | Not measured | Only GPT-5.2 measured |
| Vending-Bench 2 | $3,591 | $5,083 | Kimi K2.7 Code |
| Neither model has a result on the other 23 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index41
| Benchmark | GPT-5.2 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| GPQA Diamond | 91.7% | Not measured | Only GPT-5.2 measured |
| MMMU Pro (Vals AI) | 86.7% | Not measured | Only GPT-5.2 measured |
| GPQA Diamond (Artificial Analysis run) | 90.3% | 89.6% | GPT-5.2 |
| Humanity's Last Exam (Artificial Analysis run) | 37.7% | 35.0% | GPT-5.2 |
| GPQA Diamond (Epoch AI run) | 91.4% | 87.9% | GPT-5.2 |
| ARC-AGI | 86.2% | Not measured | Only GPT-5.2 measured |
| ARC-AGI-2 | 52.9% | Not measured | Only GPT-5.2 measured |
| SimpleBench | 45.8% | 57.9% | Kimi K2.7 Code |
| Chess puzzles | 48.0% | 14.0% | GPT-5.2 |
| Mystery game puzzles | 23.0% | Not measured | Only GPT-5.2 measured |
| EBR-bench | 23.0% | Not measured | Only GPT-5.2 measured |
| VPCT | 84.0% | Not measured | Only GPT-5.2 measured |
| LMArena Text: hard prompts | 1428 | Not measured | Only GPT-5.2 measured |
| LMArena Text: expert | 1445 | Not measured | Only GPT-5.2 measured |
| LMArena Text: hard prompts in English | 1431 | Not measured | Only GPT-5.2 measured |
| LMArena Vision: diagrams | 1265 | Not measured | Only GPT-5.2 measured |
| LMArena Vision: homework | 1276 | Not measured | Only GPT-5.2 measured |
| Neither model has a result on the other 4 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | GPT-5.2 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| AIME | 96.9% | Not measured | Only GPT-5.2 measured |
| MGSM (Vals AI) | 94.0% | Not measured | Only GPT-5.2 measured |
| AA Math Index | 99.0 | Not measured | Only GPT-5.2 measured |
| AIME 2025 (Artificial Analysis run) | 99.0% | Not measured | Only GPT-5.2 measured |
| OTIS Mock AIME | 96.1% | 95.6% | GPT-5.2 |
| FrontierMath, tiers 1 to 3 | 67.4% | 54.0% | GPT-5.2 |
| FrontierMath, tier 4 | 31.7% | 12.2% | GPT-5.2 |
| ProofBench | 15.0% | Not measured | Only GPT-5.2 measured |
| LMArena Text: math | 1440 | Not measured | Only GPT-5.2 measured |
| LMArena Text: mathematical work | 1442 | Not measured | Only GPT-5.2 measured |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.2 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| MMLU Pro | 86.2% | Not measured | Only GPT-5.2 measured |
| LegalBench (Vals AI) | 82.8% | Not measured | Only GPT-5.2 measured |
| CaseLaw (Vals AI) | 66.0% | Not measured | Only GPT-5.2 measured |
| CorpFin (Vals AI) | 65.9% | Not measured | Only GPT-5.2 measured |
| TaxEval (Vals AI) | 75.8% | Not measured | Only GPT-5.2 measured |
| MortgageTax (Vals AI) | 67.1% | Not measured | Only GPT-5.2 measured |
| MedQA (Vals AI) | 94.1% | Not measured | Only GPT-5.2 measured |
| MedCode (Vals AI) | 49.8% | Not measured | Only GPT-5.2 measured |
| MMLU Pro (Artificial Analysis run) | 87.4% | Not measured | Only GPT-5.2 measured |
| SimpleQA Verified | 37.1% | 36.5% | GPT-5.2 |
| LMArena Text: science | 1425 | Not measured | Only GPT-5.2 measured |
| LMArena Text: medicine and healthcare | 1425 | Not measured | Only GPT-5.2 measured |
| LMArena Text: legal and government | 1427 | Not measured | Only GPT-5.2 measured |
| LMArena Text: business and finance | 1414 | Not measured | Only GPT-5.2 measured |
| Neither model has a result on the other 3 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index08
| Benchmark | GPT-5.2 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| Design Arena: websites | 1196 | 1264 | Kimi K2.7 Code |
| Design Arena: UI components | 1190 | 1259 | Kimi K2.7 Code |
| Design Arena: game dev | 1196 | 1220 | Kimi K2.7 Code |
| Design Arena: data viz | 1202 | 1226 | Kimi K2.7 Code |
| Design Arena: 3D | 1079 | 1241 | Kimi K2.7 Code |
| Design Arena: all code categories | 1171 | 1253 | Kimi K2.7 Code |
| Design Arena: SVG | 1137 | 1176 | Kimi K2.7 Code |
| Design Arena: ASCII art | 1153 | 1196 | Kimi K2.7 Code |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.2 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 49.3% | Not measured | Only GPT-5.2 measured |
| MedScribe (Vals AI) | 84.4% | Not measured | Only GPT-5.2 measured |
| IFBench | 75.4% | 63.1% | GPT-5.2 |
| Long context reasoning (AA-LCR) | 82.7% | 79.3% | GPT-5.2 |
| DTBench | 90.9% | Not measured | Only GPT-5.2 measured |
| LMCA | 43.9% | Not measured | Only GPT-5.2 measured |
| CL-bench | 18.2% | Not measured | Only GPT-5.2 measured |
| Surface Evolver Bench | Not measured | 48.8% | Only Kimi K2.7 Code measured |
| Furniture assembly | 38.3% | Not measured | Only GPT-5.2 measured |
| LMArena Text | 1416 | Not measured | Only GPT-5.2 measured |
| LMArena Text: instruction following | 1409 | Not measured | Only GPT-5.2 measured |
| LMArena Text: creative writing | 1376 | Not measured | Only GPT-5.2 measured |
| LMArena Vision | 1246 | Not measured | Only GPT-5.2 measured |
| LMArena Text: English | 1422 | Not measured | Only GPT-5.2 measured |
| LMArena Text: non-English | 1405 | Not measured | Only GPT-5.2 measured |
| LMArena Text: Chinese | 1447 | Not measured | Only GPT-5.2 measured |
| LMArena Text: German | 1444 | Not measured | Only GPT-5.2 measured |
| LMArena Text: Japanese | 1420 | Not measured | Only GPT-5.2 measured |
| LMArena Text: Korean | 1374 | Not measured | Only GPT-5.2 measured |
| LMArena Text: French | 1454 | Not measured | Only GPT-5.2 measured |
| LMArena Text: Spanish | 1413 | Not measured | Only GPT-5.2 measured |
| LMArena Text: Russian | 1415 | Not measured | Only GPT-5.2 measured |
| LMArena Text: Polish | 1426 | Not measured | Only GPT-5.2 measured |
| LMArena Text: multi-turn | 1419 | Not measured | Only GPT-5.2 measured |
| LMArena Text: longer queries | 1413 | Not measured | Only GPT-5.2 measured |
| LMArena Text: writing and language | 1392 | Not measured | Only GPT-5.2 measured |
| LMArena Text: entertainment and media | 1378 | Not measured | Only GPT-5.2 measured |
| LMArena Vision: English | 1243 | Not measured | Only GPT-5.2 measured |
| LMArena Vision: Chinese | 1305 | Not measured | Only GPT-5.2 measured |
| LMArena Vision: reading text | 1257 | Not measured | Only GPT-5.2 measured |
| LMArena Vision: humor | 1227 | Not measured | Only GPT-5.2 measured |
| LMArena Vision: captioning | 1267 | Not measured | Only GPT-5.2 measured |
| LMArena Vision: recognizing things | 1232 | Not measured | Only GPT-5.2 measured |
| LMArena Vision: creative writing | 1225 | Not measured | Only GPT-5.2 measured |
| LMArena Document | 1405 | Not measured | Only GPT-5.2 measured |
| 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
| Benchmark | GPT-5.2 | Kimi K2.7 Code | Leader |
|---|---|---|---|
| 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
Kimi K2.7 Code costs less
Repository review
50K input + 3K output tokens
Kimi K2.7 Code costs less
Agent loop
200K input + 10K output tokens
Kimi K2.7 Code 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.
| Specification | OpenAI GPT-5.2 | MoonshotAI Kimi K2.7 Code |
|---|---|---|
| Maker | OpenAI | Moonshot AI |
| Weights | No public weights listed | Open weights |
| Released | December 10, 2025 | June 12, 2026 |
| Context window | 400K | 262K |
| Input $/Mtok | $1.75 | $0.6712 |
| Output $/Mtok | $14.00 | $3.35 |
| Coding index | 58.9 | 39.1 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | $1.91 | $0.35 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.2 better than Kimi K2.7 Code for coding?
Pick GPT-5.2 for coding: it scores 58.9 on the Vibe Coding Index against 39.1 for Kimi K2.7 Code. Pick Kimi K2.7 Code when output tokens cost 4.2x less, or when a solved task costs $0.35 against $1.91.
Which is cheaper, GPT-5.2 or Kimi K2.7 Code?
GPT-5.2 costs $1.75 per million input tokens and $14.00 per million output tokens; Kimi K2.7 Code costs $0.6712 and $3.35. Per solved SWE-bench Verified task, GPT-5.2 costs $1.91 and Kimi K2.7 Code $0.35.
Which has the bigger context window, GPT-5.2 or Kimi K2.7 Code?
GPT-5.2, with 400K tokens against 262K.
How many benchmarks is the GPT-5.2 vs Kimi K2.7 Code comparison based on?
36 benchmarks have a result for both models as of October 21, 2026. GPT-5.2's coding index rests on 2 independent benchmarks and Kimi K2.7 Code's on 1. Where only one model has a result, the page says so instead of naming a winner.