GPT-5.2-Codex vs Kimi K3.1 Pro
Kimi K3.1 Pro leads GPT-5.2-Codex on coding, 82.2 to 45.4 on the Vibe Coding Index, and Kimi K3.1 Pro costs 1.4x less per output token ($10.00 vs $14.00 per million). Updated October 29, 2026; 7 benchmarks have a result for both.
GPT-5.2-Codex or Kimi K3.1 Pro: which to pick
Pick Kimi K3.1 Pro for coding: it scores 82.2 on the Vibe Coding Index against 45.4 for GPT-5.2-Codex.
GPT-5.2-Codex is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
- Shared results
- 7
- GPT-5.2-Codex only
- 14
- Kimi K3.1 Pro only
- 28
- Like-for-like categories
- 3 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 K3.1 Pro
Kimi K3.1 Pro scores 82.2 against 45.4.
3 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only Kimi K3.1 Pro has a AA Intelligence Index result, 46.0.
Directional only
Web design
Design Arena: websites
No call
Only Kimi K3.1 Pro has a Design Arena: websites result, 1325.
Directional only
General
Vals Index
No call
Only Kimi K3.1 Pro has a Vals Index result, 62.5%.
Directional only
Long documents
Listed context window
Kimi K3.1 Pro
Kimi K3.1 Pro takes 1.05M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Kimi K3.1 Pro
GPT-5.2-Codex $0.0088, Kimi K3.1 Pro $0.0070 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.2-Codex has the number, $0.43.
Directional only
At a glance
- Coding index
- GPT-5.2-Codex 45.4 from 3 benchmarks, Kimi K3.1 Pro 82.2 from 4 benchmarks.
- Widest category
- Coding, 41.2 points apart on average over 5 shared benchmarks.
- Widest single gap
- LMArena WebDev: GPT-5.2-Codex 1339 against Kimi K3.1 Pro 1695, 50.8 points apart on a 0 to 100 scale.
- Output price
- GPT-5.2-Codex $14.00 against Kimi K3.1 Pro $10.00 per million output tokens, 1.4x apart.
- Context window
- GPT-5.2-Codex takes 400K tokens, Kimi K3.1 Pro 1.05M.
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 K3.1 Pro | Ties |
|---|---|---|---|---|
| Coding | 0 | 5 | ||
| Reasoning | 0 | 1 | ||
| General | 0 | 1 | ||
| All shared boards | 0 | 7 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index05
| Benchmark | GPT-5.2-Codex | Kimi K3.1 Pro | 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 |
| LiveBench coding | Not measured | 81.8% | Only Kimi K3.1 Pro measured |
| LMArena WebDev | 1339 | 1695 | Kimi K3.1 Pro |
| LiveCodeBench (Vals AI) | 88.0% | Not measured | Only GPT-5.2-Codex measured |
| SWE-bench Verified (Vals AI) | 72.4% | Not measured | Only GPT-5.2-Codex measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 63.6% | Only Kimi K3.1 Pro measured |
| Vibe Code Bench (Vals AI) | 37.9% | 84.9% | Kimi K3.1 Pro |
| IOI (Vals AI) | Not measured | 81.9% | Only Kimi K3.1 Pro measured |
| SciCode | Not measured | 60.8% | Only Kimi K3.1 Pro measured |
| Terminal-Bench Hard (Artificial Analysis run) | 37.1% | Not measured | Only GPT-5.2-Codex measured |
| Terminal-Bench | 66.5% | Not measured | Only GPT-5.2-Codex measured |
| ALE-Bench | 1299.9 | 1932.8 | Kimi K3.1 Pro |
| LMArena WebDev: React | 1329 | 1701 | Kimi K3.1 Pro |
| LMArena WebDev: HTML | 1349 | 1706 | Kimi K3.1 Pro |
| Neither model has a result on the other 28 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | GPT-5.2-Codex | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 46.0 | Only Kimi K3.1 Pro measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index15 boards, none shared
| Benchmark | GPT-5.2-Codex | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1052 | Not measured | Only GPT-5.2-Codex measured |
| Design Arena: agents building full-stack apps | 993 | Not measured | Only GPT-5.2-Codex measured |
| Design Arena: agents building mobile apps | 1089 | Not measured | Only GPT-5.2-Codex measured |
| Design Arena: agents building Android apps | 1176 | Not measured | Only GPT-5.2-Codex measured |
| Design Arena: agents building Godot games | 1142 | Not measured | Only GPT-5.2-Codex measured |
| LiveBench research | Not measured | 77.9% | Only Kimi K3.1 Pro measured |
| LiveBench browser | Not measured | 75.9% | Only Kimi K3.1 Pro measured |
| LiveBench long agentic | Not measured | 39.1% | Only Kimi K3.1 Pro measured |
| Tax Agent Bench (Vals AI) | Not measured | 24.9% | Only Kimi K3.1 Pro measured |
| Legal Research Bench (Vals AI) | Not measured | 37.5% | Only Kimi K3.1 Pro measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 11.7% | Only Kimi K3.1 Pro measured |
| BioMysteryBench (Vals AI) | Not measured | 75.6% | Only Kimi K3.1 Pro measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 31.4% | Only Kimi K3.1 Pro measured |
| Vals Science Index | Not measured | 44.4% | Only Kimi K3.1 Pro measured |
| τ²-Bench Telecom | 92.1% | Not measured | Only GPT-5.2-Codex measured |
| Neither model has a result on the other 27 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-5.2-Codex | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 91.1% | Only Kimi K3.1 Pro measured |
| MysteryMechanism (Vals AI) | Not measured | 26.1% | Only Kimi K3.1 Pro measured |
| GPQA Diamond (Artificial Analysis run) | 89.9% | Not measured | Only GPT-5.2-Codex measured |
| Humanity's Last Exam (Artificial Analysis run) | 35.7% | 52.5% | Kimi K3.1 Pro |
| Neither model has a result on the other 19 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | GPT-5.2-Codex | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| ProofBench | Not measured | 91.0% | Only Kimi K3.1 Pro measured |
| MathArena | Not measured | 59.6% | Only Kimi K3.1 Pro measured |
| Neither model has a result on the other 12 boards here | |||
KnowledgeNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.2-Codex | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| Neither model has a result on 20 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | GPT-5.2-Codex | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1325 | Only Kimi K3.1 Pro measured |
| Design Arena: UI components | Not measured | 1400 | Only Kimi K3.1 Pro measured |
| Design Arena: game dev | Not measured | 1410 | Only Kimi K3.1 Pro measured |
| Design Arena: data viz | Not measured | 1300 | Only Kimi K3.1 Pro measured |
| Design Arena: 3D | Not measured | 1451 | Only Kimi K3.1 Pro measured |
| Design Arena: all code categories | Not measured | 1354 | Only Kimi K3.1 Pro measured |
| Design Arena: SVG | Not measured | 1328 | Only Kimi K3.1 Pro measured |
| LiveBench design | Not measured | 77.8% | Only Kimi K3.1 Pro measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | GPT-5.2-Codex | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| Vals Index | Not measured | 62.5% | Only Kimi K3.1 Pro measured |
| LiveBench data analysis | Not measured | 79.1% | Only Kimi K3.1 Pro measured |
| IFBench | 77.6% | Not measured | Only GPT-5.2-Codex measured |
| Long context reasoning (AA-LCR) | 82.3% | 86.3% | Kimi K3.1 Pro |
| Neither model has a result on the other 44 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.2-Codex | Kimi K3.1 Pro | 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 K3.1 Pro costs less
Repository review
50K input + 3K output tokens
GPT-5.2-Codex costs less
Agent loop
200K input + 10K output tokens
GPT-5.2-Codex 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 K3.1 Pro |
|---|---|---|
| Maker | OpenAI | Moonshot AI |
| Weights | No public weights listed | No public weights listed |
| Released | January 14, 2026 | October 23, 2026 |
| Context window | 400K | 1.05M |
| Input $/Mtok | $1.75 | $2.00 |
| Output $/Mtok | $14.00 | $10.00 |
| Coding index | 45.4 | 82.2 |
| Independent measurements behind it | 3 | 4 |
| Cost per solved task | $0.43 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.2-Codex better than Kimi K3.1 Pro for coding?
Pick Kimi K3.1 Pro for coding: it scores 82.2 on the Vibe Coding Index against 45.4 for GPT-5.2-Codex. GPT-5.2-Codex is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
Which is cheaper, GPT-5.2-Codex or Kimi K3.1 Pro?
GPT-5.2-Codex costs $1.75 per million input tokens and $14.00 per million output tokens; Kimi K3.1 Pro costs $2.00 and $10.00. Cost per solved task is known for GPT-5.2-Codex only.
Which has the bigger context window, GPT-5.2-Codex or Kimi K3.1 Pro?
Kimi K3.1 Pro, with 1.05M tokens against 400K.
How many benchmarks is the GPT-5.2-Codex vs Kimi K3.1 Pro comparison based on?
7 benchmarks have a result for both models as of October 29, 2026. GPT-5.2-Codex's coding index rests on 3 independent benchmarks and Kimi K3.1 Pro's on 4. Where only one model has a result, the page says so instead of naming a winner.