Model comparison
GPT-5.2 Codex vs Kimi K2.6
Kimi K2.6 is the stronger model overall, scoring 47.5 to 42.2 on the Noometry Index.
Last verified . 2 shared benchmarks.
Summary
- They share 2 benchmarks with published results for both. GPT-5.2 Codex scores higher in 1 category and Kimi K2.6 in 1 category; 2 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where GPT-5.2 Codex leads 40.7 to 21.8.
- Kimi K2.6 is cheaper at $0.95 / $4 per million input/output tokens, against $1.75 / $14 for GPT-5.2 Codex.
- GPT-5.2 Codex accepts more context: 400K tokens versus 262K.
- Kimi K2.6 has downloadable open weights; the other is API-only.
Side by side
| GPT-5.2 Codex | Kimi K2.6 | |
|---|---|---|
| Provider | OpenAI | Moonshot AI |
| Noometry Index | 42.2 | 47.5 |
| Released | 2025-12-18 | 2026-04-20 |
| Weights | Proprietary | Open |
| Context window | 400K | 262K |
| Max output | 128K | 262K |
| Input $ / M tokens | $1.75 | $0.95 |
| Output $ / M tokens | $14 | $4 |
| Results tracked | 5 | 51 |
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Category by category
Coding Kimi K2.6 leads
GPT-5.2 Codex: 45.4 (#66), Kimi K2.6: 50.5 (#41)
| Benchmark | GPT-5.2 Codex | Kimi K2.6 |
|---|---|---|
| LMArena WebDev | 1339 | 1509 |
| ALE-Bench | 1,300 | 1,093 |
| SWE-bench Verified | — | 76.7% |
| SWE-bench Verified (bash only) | 72.8% | — |
| SWE-bench Multilingual | 66.3% | — |
| SciCode | — | 53.5% |
| WeirdML | — | 55.9% |
| LMArena Coding | — | 1488 |
Agentic & Tool Use GPT-5.2 Codex leads
GPT-5.2 Codex: 40.7 (#20), Kimi K2.6: 21.8 (#128)
| Benchmark | GPT-5.2 Codex | Kimi K2.6 |
|---|---|---|
| Terminal-Bench | 66.5% | — |
| OSWorld 2.0 | — | 4.6% |
| ExploitBench | — | 18.4% |
| GBAEval | — | 0.9% |
| GDP.pdf | — | 12% |
| Vending-Bench 2 | — | 6,205 |
Reasoning Not comparable
GPT-5.2 Codex: —, Kimi K2.6: 39.6 (#51)
| Benchmark | GPT-5.2 Codex | Kimi K2.6 |
|---|---|---|
| NYT Connections (extended) | — | 87.2% |
| CritPt | — | 8% |
| Chess Puzzles | — | 26% |
| EBR-Bench | — | 2.4% |
| LMArena Hard Prompts | — | 1470 |
| Mystery Game Puzzles | — | 18% |
| DTBench | — | 90.9% |
| LMCA | — | 37.3% |
| Epoch Capabilities Index | — | 151.03 |
Math Not comparable
GPT-5.2 Codex: —, Kimi K2.6: 56.8 (#34)
| Benchmark | GPT-5.2 Codex | Kimi K2.6 |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 57.2% |
| FrontierMath Tier 4 | — | 25.6% |
| MathArena Final-Answer Competitions | — | 72.9% |
| OTIS Mock AIME 2024-2025 | — | 96.1% |
| ProofBench | — | 16% |
| LMArena Math | — | 1475 |
| FrontierMath (Feb 2025 set) | — | 39% |
| FrontierMath Tier 4 (v1) | — | 14.6% |
Knowledge Not comparable
GPT-5.2 Codex: —, Kimi K2.6: 53.9 (#48)
| Benchmark | GPT-5.2 Codex | Kimi K2.6 |
|---|---|---|
| GPQA Diamond | — | 90.8% |
| SimpleQA Verified | — | 34.9% |
| Vectara Hallucination Rate | — | 10.8% |
| LMArena Expert | — | 1491 |
Multimodal Not comparable
GPT-5.2 Codex: —, Kimi K2.6: 31.8 (#95)
| Benchmark | GPT-5.2 Codex | Kimi K2.6 |
|---|---|---|
| LMArena Vision | — | 1282 |
| Blueprint-Bench 2 | — | 3.9% |
| Furniture Assembly | — | 21.7% |
| LMArena Document | — | 1451 |
Multilingual Not comparable
GPT-5.2 Codex: —, Kimi K2.6: 55.1 (#35)
| Benchmark | GPT-5.2 Codex | Kimi K2.6 |
|---|---|---|
| LMArena Non-English | — | 1446 |
| LMArena Chinese | — | 1521 |
| LMArena French | — | 1471 |
| LMArena German | — | 1449 |
| LMArena Japanese | — | 1442 |
| LMArena Korean | — | 1428 |
| LMArena Russian | — | 1446 |
| LMArena Spanish | — | 1463 |
Instruction Following Not comparable
GPT-5.2 Codex: —, Kimi K2.6: 76.5 (#40)
| Benchmark | GPT-5.2 Codex | Kimi K2.6 |
|---|---|---|
| LMArena Instruction Following | — | 1451 |
Long Context Not comparable
GPT-5.2 Codex: —, Kimi K2.6: 44.9 (#50)
| Benchmark | GPT-5.2 Codex | Kimi K2.6 |
|---|---|---|
| LMArena Longer Query | — | 1468 |
Writing & Preference Not comparable
GPT-5.2 Codex: —, Kimi K2.6: 68.7 (#25)
| Benchmark | GPT-5.2 Codex | Kimi K2.6 |
|---|---|---|
| LMArena Text | — | 1455 |
| LMArena Creative Writing | — | 1434 |
| EQ-Bench Creative Writing | — | 1725 |
| EQ-Bench 4 | — | 1202 |
| LMArena Multi-Turn | — | 1453 |
Frequently asked questions
Is GPT-5.2 Codex better than Kimi K2.6?
Kimi K2.6 is the stronger model overall, scoring 47.5 to 42.2 on the Noometry Index.
Which is cheaper, GPT-5.2 Codex or Kimi K2.6?
Kimi K2.6 is cheaper. It lists at $0.95 per million input tokens and $4 per million output tokens; GPT-5.2 Codex lists at $1.75 and $14.
Is GPT-5.2 Codex or Kimi K2.6 better for coding?
Kimi K2.6 scores higher on coding benchmarks: 50.5 versus 45.4 in the Noometry coding category.
Which has the bigger context window?
GPT-5.2 Codex does, with 400K tokens against 262K.
How many benchmarks do GPT-5.2 Codex and Kimi K2.6 share?
2 benchmarks have published results for both models. GPT-5.2 Codex has 5 scored results on Noometry and Kimi K2.6 has 51.