GPT-5.2-Codex vs Kimi K2.7 Code
Kimi K2.7 Code leads GPT-5.2-Codex on coding, 53.4 to 45.4 on the Vibe Coding Index, and Kimi K2.7 Code costs 3.5x less per output token ($4.00 vs $14.00 per million). Updated October 22, 2026; 19 benchmarks have a result for both.
GPT-5.2-Codex or Kimi K2.7 Code: which to pick
Pick Kimi K2.7 Code for coding: it scores 53.4 on the Vibe Coding Index against 45.4 for GPT-5.2-Codex.
Pick GPT-5.2-Codex for a larger context window (400K against 262K tokens) and work measured by LiveCodeBench (Vals AI) or ALE-Bench, where it leads.
- Shared results
- 19
- GPT-5.2-Codex only
- 3
- Kimi K2.7 Code only
- 32
- Like-for-like categories
- 5 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
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, six public coding benchmarks
Kimi K2.7 Code
Kimi K2.7 Code scores 53.4 against 45.4.
3 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.2-Codex
GPT-5.2-Codex leads, 28.5 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
Web design
Design Arena: websites
No call
Only Kimi K2.7 Code has a Design Arena: websites result, 1263.
Directional only
Long documents
Listed context window
GPT-5.2-Codex
GPT-5.2-Codex takes 400K tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Kimi K2.7 Code
GPT-5.2-Codex $0.0088, Kimi K2.7 Code $0.0029 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Kimi K2.7 Code
GPT-5.2-Codex $0.43, Kimi K2.7 Code $0.35.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5.2-Codex 45.4 from 3 benchmarks, Kimi K2.7 Code 53.4 from 4 benchmarks.
- Widest category
- Coding, 12.9 points apart on average over 8 shared benchmarks.
- Widest single gap
- LMArena WebDev: React: GPT-5.2-Codex 1329 against Kimi K2.7 Code 1475, 24.3 points apart on a 0 to 100 scale.
- Output price
- GPT-5.2-Codex $14.00 against Kimi K2.7 Code $4.00 per million output tokens, 3.5x apart.
- Context window
- GPT-5.2-Codex 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-Codex | Bars | Kimi K2.7 Code | Ties |
|---|---|---|---|---|
| Coding | 2 | 6 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 2 | 4 | ||
| Reasoning | 2 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 9 | 10 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index26
| Benchmark | GPT-5.2-Codex | Kimi K2.7 Code | Leader |
|---|---|---|---|
| SWE-bench Verified | 72.8% | Not measured | Only GPT-5.2-Codex measured |
| SWE-bench Multilingual | 66.3% | Not measured | Only GPT-5.2-Codex measured |
| LMArena WebDev | 1339 | 1474 | Kimi K2.7 Code |
| AA Coding Index | Not measured | 60.8 | Only Kimi K2.7 Code measured |
| LiveCodeBench (Vals AI) | 88.0% | 82.0% | GPT-5.2-Codex |
| SWE-bench Verified (Vals AI) | 72.4% | 78.2% | Kimi K2.7 Code |
| Vibe Code Bench (Vals AI) | 37.9% | 47.2% | Kimi K2.7 Code |
| 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 |
| SciCode | Not measured | 47.8% | Only Kimi K2.7 Code measured |
| Terminal-Bench Hard (Artificial Analysis run) | 37.1% | 44.7% | Kimi K2.7 Code |
| Terminal-Bench | 66.5% | Not measured | Only GPT-5.2-Codex measured |
| FrontierCode | Not measured | 30.1% | Only Kimi K2.7 Code measured |
| WeirdML | Not measured | 54.1% | Only Kimi K2.7 Code measured |
| ALE-Bench | 1299.9 | 886.2 | GPT-5.2-Codex |
| LMArena WebDev: React | 1329 | 1475 | Kimi K2.7 Code |
| LMArena WebDev: HTML | 1348 | 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 19 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.2-Codex | Kimi K2.7 Code | Leader |
|---|---|---|---|
| AA Intelligence Index | 28.5 | 25.8 | GPT-5.2-Codex |
| Epoch Capabilities Index | Not measured | 150.1 | Only Kimi K2.7 Code measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index24
| Benchmark | GPT-5.2-Codex | Kimi K2.7 Code | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 21.0 | Only Kimi K2.7 Code measured |
| Design Arena: agents building web apps | 1051 | 1176 | Kimi K2.7 Code |
| Design Arena: agents building full-stack apps | 993 | 1175 | Kimi K2.7 Code |
| Design Arena: agents building mobile apps | 1090 | 1143 | Kimi K2.7 Code |
| Design Arena: agents building Android apps | 1176 | 1138 | GPT-5.2-Codex |
| 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 | 1151 | Only Kimi K2.7 Code measured |
| Design Arena: PowerPoint slides | Not measured | 1129 | Only Kimi K2.7 Code measured |
| τ²-Bench Telecom | 92.1% | 90.1% | GPT-5.2-Codex |
| APEX-Agents | Not measured | 37.6% | Only Kimi K2.7 Code measured |
| Vending-Bench 2 | Not measured | $5,083 | Only Kimi K2.7 Code measured |
| Neither model has a result on the other 29 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.2-Codex | Kimi K2.7 Code | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 89.9% | 89.6% | GPT-5.2-Codex |
| Humanity's Last Exam (Artificial Analysis run) | 35.7% | 35.0% | GPT-5.2-Codex |
| GPQA Diamond (Epoch AI run) | Not measured | 87.9% | Only Kimi K2.7 Code measured |
| SimpleBench | Not measured | 57.9% | Only Kimi K2.7 Code measured |
| Chess puzzles | Not measured | 14.0% | Only Kimi K2.7 Code measured |
| Neither model has a result on the other 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | GPT-5.2-Codex | Kimi K2.7 Code | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 95.6% | Only Kimi K2.7 Code measured |
| FrontierMath, tiers 1 to 3 | Not measured | 54.0% | Only Kimi K2.7 Code measured |
| FrontierMath, tier 4 | Not measured | 12.2% | Only Kimi K2.7 Code measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-5.2-Codex | Kimi K2.7 Code | Leader |
|---|---|---|---|
| SimpleQA Verified | Not measured | 36.5% | Only Kimi K2.7 Code measured |
| Neither model has a result on the other 17 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-5.2-Codex | Kimi K2.7 Code | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1263 | Only Kimi K2.7 Code measured |
| Design Arena: UI components | Not measured | 1255 | Only Kimi K2.7 Code measured |
| Design Arena: game dev | Not measured | 1220 | Only Kimi K2.7 Code measured |
| Design Arena: data viz | Not measured | 1227 | Only Kimi K2.7 Code measured |
| Design Arena: 3D | Not measured | 1240 | Only Kimi K2.7 Code measured |
| Design Arena: all code categories | Not measured | 1252 | Only Kimi K2.7 Code measured |
| Design Arena: SVG | Not measured | 1176 | Only Kimi K2.7 Code measured |
| Design Arena: ASCII art | Not measured | 1196 | Only Kimi K2.7 Code measured |
| 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-Codex | Kimi K2.7 Code | Leader |
|---|---|---|---|
| IFBench | 77.6% | 63.1% | GPT-5.2-Codex |
| Long context reasoning (AA-LCR) | 82.3% | 79.3% | GPT-5.2-Codex |
| Surface Evolver Bench | Not measured | 48.8% | Only Kimi K2.7 Code measured |
| Neither model has a result on the other 43 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.2-Codex | 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-Codex | MoonshotAI Kimi K2.7 Code |
|---|---|---|
| Maker | OpenAI | Moonshot AI |
| Weights | No public weights listed | Open weights |
| Released | January 14, 2026 | June 12, 2026 |
| Context window | 400K | 262K |
| Input $/Mtok | $1.75 | $0.95 |
| Output $/Mtok | $14.00 | $4.00 |
| Coding index | 45.4 | 53.4 |
| Independent measurements behind it | 3 | 4 |
| Cost per solved task | $0.43 | $0.35 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.2-Codex better than Kimi K2.7 Code for coding?
Pick Kimi K2.7 Code for coding: it scores 53.4 on the Vibe Coding Index against 45.4 for GPT-5.2-Codex. Pick GPT-5.2-Codex for a larger context window (400K against 262K tokens) and work measured by LiveCodeBench (Vals AI) or ALE-Bench, where it leads.
Which is cheaper, GPT-5.2-Codex or Kimi K2.7 Code?
GPT-5.2-Codex costs $1.75 per million input tokens and $14.00 per million output tokens; Kimi K2.7 Code costs $0.95 and $4.00. Per solved SWE-bench Verified task, GPT-5.2-Codex costs $0.43 and Kimi K2.7 Code $0.35.
Which has the bigger context window, GPT-5.2-Codex or Kimi K2.7 Code?
GPT-5.2-Codex, with 400K tokens against 262K.
How many benchmarks is the GPT-5.2-Codex vs Kimi K2.7 Code comparison based on?
19 benchmarks have a result for both models as of October 22, 2026. GPT-5.2-Codex's coding index rests on 3 independent benchmarks and Kimi K2.7 Code's on 4. Where only one model has a result, the page says so instead of naming a winner.