GPT-5.2-Codex vs Kimi K2.5
GPT-5.2-Codex leads Kimi K2.5 on coding, 45.4 to 38.6 on the Vibe Coding Index, and Kimi K2.5 costs 4.9x less per output token ($2.85 vs $14.00 per million). Updated October 21, 2026; 22 benchmarks have a result for both.
GPT-5.2-Codex or Kimi K2.5: which to pick
Pick GPT-5.2-Codex for coding: it scores 45.4 on the Vibe Coding Index against 38.6 for Kimi K2.5.
Pick Kimi K2.5 for output tokens 4.9x cheaper ($2.85 vs $14.00 per million) and a lower cost per solved task ($0.24 against $0.43).
- Shared results
- 22
- GPT-5.2-Codex only
- 0
- Kimi K2.5 only
- 77
- 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
GPT-5.2-Codex
GPT-5.2-Codex scores 45.4 against 38.6.
3 benchmarks behind each score
Intelligence
AA Intelligence Index
GPT-5.2-Codex
GPT-5.2-Codex leads, 28.5 against 23.5.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Kimi K2.5 has a GPQA Diamond result, 84.1%.
Directional only
Math
AIME
No call
Only Kimi K2.5 has a AIME result, 95.6%.
Directional only
Knowledge
MMLU Pro
No call
Only Kimi K2.5 has a MMLU Pro result, 85.9%.
Directional only
Web design
Design Arena: websites
No call
Only Kimi K2.5 has a Design Arena: websites result, 1248.
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 K2.5
GPT-5.2-Codex $0.0088, Kimi K2.5 $0.0020 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Kimi K2.5
GPT-5.2-Codex $0.43, Kimi K2.5 $0.24.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5.2-Codex 45.4 from 3 benchmarks, Kimi K2.5 38.6 from 3 benchmarks.
- Widest category
- Coding, 10.5 points apart on average over 11 shared benchmarks.
- Widest single gap
- Terminal-Bench: GPT-5.2-Codex 66.5% against Kimi K2.5 43.2%, 23.3 points apart on a 0 to 100 scale.
- Output price
- GPT-5.2-Codex $14.00 against Kimi K2.5 $2.85 per million output tokens, 4.9x apart.
- Context window
- GPT-5.2-Codex 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.
| Category | GPT-5.2-Codex | Bars | Kimi K2.5 | Ties |
|---|---|---|---|---|
| Coding | 7 | 4 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 5 | ||
| Reasoning | 2 | 0 | ||
| General | 2 | 0 | ||
| All shared boards | 13 | 9 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index74
| Benchmark | GPT-5.2-Codex | Kimi K2.5 | Leader |
|---|---|---|---|
| SWE-bench Verified | 72.8% | 70.8% | GPT-5.2-Codex |
| SWE-bench Multilingual | 66.3% | 67.3% | Kimi K2.5 |
| LMArena WebDev | 1339 | 1437 | Kimi K2.5 |
| AA Coding Index | Not measured | 46.8 | Only Kimi K2.5 measured |
| LiveCodeBench (Vals AI) | 88.0% | 83.9% | GPT-5.2-Codex |
| SWE-bench Verified (Vals AI) | 72.4% | 70.0% | GPT-5.2-Codex |
| Vibe Code Bench (Vals AI) | 37.9% | 17.5% | GPT-5.2-Codex |
| Code migration (Vals AI) | Not measured | 7.0% | Only Kimi K2.5 measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 42.0% | Only Kimi K2.5 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 37.1% | 34.8% | GPT-5.2-Codex |
| Terminal-Bench | 66.5% | 43.2% | GPT-5.2-Codex |
| WeirdML | Not measured | 45.6% | Only Kimi K2.5 measured |
| ALE-Bench | 1299.9 | 821.6 | GPT-5.2-Codex |
| LMArena Text: coding | Not measured | 1483 | Only Kimi K2.5 measured |
| LMArena Text: software and IT | Not measured | 1471 | Only Kimi K2.5 measured |
| LMArena WebDev: React | 1329 | 1429 | Kimi K2.5 |
| LMArena WebDev: HTML | 1348 | 1426 | Kimi K2.5 |
| LMArena WebDev: from an image | Not measured | 1439 | Only Kimi K2.5 measured |
| Neither model has a result on the other 21 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | GPT-5.2-Codex | Kimi K2.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 28.5 | 23.5 | GPT-5.2-Codex |
| Epoch Capabilities Index | Not measured | 148.1 | Only Kimi K2.5 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index15
| Benchmark | GPT-5.2-Codex | Kimi K2.5 | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1051 | 1136 | Kimi K2.5 |
| Design Arena: agents building full-stack apps | 993 | 1114 | Kimi K2.5 |
| Design Arena: agents building mobile apps | 1090 | 1147 | Kimi K2.5 |
| Design Arena: agents building Android apps | 1176 | 1118 | GPT-5.2-Codex |
| Design Arena: agents building Godot games | 1142 | 1219 | Kimi K2.5 |
| Finance Agent (Vals AI) | Not measured | 35.8% | Only Kimi K2.5 measured |
| Legal Research Bench (Vals AI) | Not measured | 15.9% | Only Kimi K2.5 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 28.5% | Only Kimi K2.5 measured |
| τ²-Bench Telecom | 92.1% | 95.9% | Kimi K2.5 |
| OSWorld | Not measured | 63.3% | Only Kimi K2.5 measured |
| Vending-Bench 2 | Not measured | $1,198 | Only Kimi K2.5 measured |
| Neither model has a result on the other 30 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.2-Codex | Kimi K2.5 | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 84.1% | Only Kimi K2.5 measured |
| MMMU Pro (Vals AI) | Not measured | 84.3% | Only Kimi K2.5 measured |
| GPQA Diamond (Artificial Analysis run) | 89.9% | 87.9% | GPT-5.2-Codex |
| Humanity's Last Exam (Artificial Analysis run) | 35.7% | 30.7% | GPT-5.2-Codex |
| ARC-AGI | Not measured | 65.3% | Only Kimi K2.5 measured |
| ARC-AGI-2 | Not measured | 11.8% | Only Kimi K2.5 measured |
| SimpleBench | Not measured | 46.8% | Only Kimi K2.5 measured |
| LMArena Text: hard prompts | Not measured | 1453 | Only Kimi K2.5 measured |
| LMArena Text: expert | Not measured | 1466 | Only Kimi K2.5 measured |
| LMArena Text: hard prompts in English | Not measured | 1460 | Only Kimi K2.5 measured |
| LMArena Vision: diagrams | Not measured | 1282 | Only Kimi K2.5 measured |
| LMArena Vision: homework | Not measured | 1297 | Only Kimi K2.5 measured |
| Kagi LLM Benchmark | Not measured | 78.5% | Only Kimi K2.5 measured |
| Neither model has a result on the other 9 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | GPT-5.2-Codex | Kimi K2.5 | Leader |
|---|---|---|---|
| AIME | Not measured | 95.6% | Only Kimi K2.5 measured |
| LMArena Text: math | Not measured | 1470 | Only Kimi K2.5 measured |
| LMArena Text: mathematical work | Not measured | 1473 | Only Kimi K2.5 measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
| Benchmark | GPT-5.2-Codex | Kimi K2.5 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 85.9% | Only Kimi K2.5 measured |
| CaseLaw (Vals AI) | Not measured | 58.7% | Only Kimi K2.5 measured |
| CorpFin (Vals AI) | Not measured | 68.3% | Only Kimi K2.5 measured |
| TaxEval (Vals AI) | Not measured | 74.2% | Only Kimi K2.5 measured |
| MortgageTax (Vals AI) | Not measured | 66.5% | Only Kimi K2.5 measured |
| MedQA (Vals AI) | Not measured | 94.4% | Only Kimi K2.5 measured |
| MedCode (Vals AI) | Not measured | 39.3% | Only Kimi K2.5 measured |
| SimpleQA Verified | Not measured | 34.3% | Only Kimi K2.5 measured |
| LMArena Text: science | Not measured | 1459 | Only Kimi K2.5 measured |
| LMArena Text: medicine and healthcare | Not measured | 1448 | Only Kimi K2.5 measured |
| LMArena Text: legal and government | Not measured | 1441 | Only Kimi K2.5 measured |
| LMArena Text: business and finance | Not measured | 1427 | Only Kimi K2.5 measured |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-5.2-Codex | Kimi K2.5 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1248 | Only Kimi K2.5 measured |
| Design Arena: UI components | Not measured | 1236 | Only Kimi K2.5 measured |
| Design Arena: game dev | Not measured | 1207 | Only Kimi K2.5 measured |
| Design Arena: data viz | Not measured | 1219 | Only Kimi K2.5 measured |
| Design Arena: 3D | Not measured | 1205 | Only Kimi K2.5 measured |
| Design Arena: all code categories | Not measured | 1236 | Only Kimi K2.5 measured |
| Design Arena: SVG | Not measured | 1149 | Only Kimi K2.5 measured |
| Design Arena: ASCII art | Not measured | 1166 | Only Kimi K2.5 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 K2.5 | Leader |
|---|---|---|---|
| SAGE (Vals AI) | Not measured | 49.9% | Only Kimi K2.5 measured |
| MedScribe (Vals AI) | Not measured | 76.4% | Only Kimi K2.5 measured |
| IFBench | 77.6% | 70.2% | GPT-5.2-Codex |
| Long context reasoning (AA-LCR) | 82.3% | 78.0% | GPT-5.2-Codex |
| Fiction.LiveBench | Not measured | 86.1% | Only Kimi K2.5 measured |
| CL-bench | Not measured | 19.3% | Only Kimi K2.5 measured |
| CL-bench Life | Not measured | 13.2% | Only Kimi K2.5 measured |
| LMArena Text | Not measured | 1445 | Only Kimi K2.5 measured |
| LMArena Text: instruction following | Not measured | 1431 | Only Kimi K2.5 measured |
| LMArena Text: creative writing | Not measured | 1422 | Only Kimi K2.5 measured |
| LMArena Vision | Not measured | 1269 | Only Kimi K2.5 measured |
| LMArena Text: English | Not measured | 1453 | Only Kimi K2.5 measured |
| LMArena Text: non-English | Not measured | 1433 | Only Kimi K2.5 measured |
| LMArena Text: Chinese | Not measured | 1494 | Only Kimi K2.5 measured |
| LMArena Text: German | Not measured | 1441 | Only Kimi K2.5 measured |
| LMArena Text: Japanese | Not measured | 1423 | Only Kimi K2.5 measured |
| LMArena Text: Korean | Not measured | 1412 | Only Kimi K2.5 measured |
| LMArena Text: French | Not measured | 1454 | Only Kimi K2.5 measured |
| LMArena Text: Spanish | Not measured | 1450 | Only Kimi K2.5 measured |
| LMArena Text: Russian | Not measured | 1435 | Only Kimi K2.5 measured |
| LMArena Text: Polish | Not measured | 1445 | Only Kimi K2.5 measured |
| LMArena Text: multi-turn | Not measured | 1444 | Only Kimi K2.5 measured |
| LMArena Text: longer queries | Not measured | 1445 | Only Kimi K2.5 measured |
| LMArena Text: writing and language | Not measured | 1425 | Only Kimi K2.5 measured |
| LMArena Text: entertainment and media | Not measured | 1417 | Only Kimi K2.5 measured |
| LMArena Vision: English | Not measured | 1274 | Only Kimi K2.5 measured |
| LMArena Vision: Chinese | Not measured | 1328 | Only Kimi K2.5 measured |
| LMArena Vision: reading text | Not measured | 1276 | Only Kimi K2.5 measured |
| LMArena Vision: humor | Not measured | 1284 | Only Kimi K2.5 measured |
| LMArena Vision: captioning | Not measured | 1257 | Only Kimi K2.5 measured |
| LMArena Vision: recognizing things | Not measured | 1285 | Only Kimi K2.5 measured |
| LMArena Vision: creative writing | Not measured | 1269 | Only 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
| Benchmark | GPT-5.2-Codex | Kimi K2.5 | 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 K2.5 costs less
Repository review
50K input + 3K output tokens
Kimi K2.5 costs less
Agent loop
200K input + 10K output tokens
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.
| Specification | OpenAI GPT-5.2-Codex | MoonshotAI Kimi K2.5 |
|---|---|---|
| Maker | OpenAI | Moonshot AI |
| Weights | No public weights listed | Open weights |
| Released | January 14, 2026 | January 27, 2026 |
| Context window | 400K | 262K |
| Input $/Mtok | $1.75 | $0.532 |
| Output $/Mtok | $14.00 | $2.85 |
| Coding index | 45.4 | 38.6 |
| Independent measurements behind it | 3 | 3 |
| Cost per solved task | $0.43 | $0.24 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.2-Codex better than Kimi K2.5 for coding?
Pick GPT-5.2-Codex for coding: it scores 45.4 on the Vibe Coding Index against 38.6 for Kimi K2.5. Pick Kimi K2.5 for output tokens 4.9x cheaper ($2.85 vs $14.00 per million) and a lower cost per solved task ($0.24 against $0.43).
Which is cheaper, GPT-5.2-Codex or Kimi K2.5?
GPT-5.2-Codex costs $1.75 per million input tokens and $14.00 per million output tokens; Kimi K2.5 costs $0.532 and $2.85. Per solved SWE-bench Verified task, GPT-5.2-Codex costs $0.43 and Kimi K2.5 $0.24.
Which has the bigger context window, GPT-5.2-Codex or Kimi K2.5?
GPT-5.2-Codex, with 400K tokens against 262K.
How many benchmarks is the GPT-5.2-Codex vs Kimi K2.5 comparison based on?
22 benchmarks have a result for both models as of October 21, 2026. GPT-5.2-Codex's coding index rests on 3 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.