Model comparison
GPT-4.1 vs GPT-5.2 Codex
GPT-5.2 Codex is the stronger model overall, scoring 42.6 to 35.9 on the Noometry Index.
Last verified . 2 shared benchmarks.
Summary
- They share 2 benchmarks with published results for both. GPT-4.1 scores higher in 0 categories and GPT-5.2 Codex in 2 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in coding, where GPT-5.2 Codex leads 45.5 to 34.4.
- The biggest single-benchmark swing is SWE-bench Verified (bash only): 39.6% for GPT-4.1 and 72.8% for GPT-5.2 Codex.
- GPT-4.1 is cheaper at $2 / $8 per million input/output tokens, against $1.75 / $14 for GPT-5.2 Codex.
- GPT-4.1 accepts more context: 1.05M tokens versus 400K.
Side by side
| GPT-4.1 | GPT-5.2 Codex | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 35.9 | 42.6 |
| Released | 2025-04-14 | 2025-12-18 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 400K |
| Max output | 33K | 128K |
| Input $ / M tokens | $2 | $1.75 |
| Output $ / M tokens | $8 | $14 |
| Results tracked | 52 | 5 |
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Category by category
Coding GPT-5.2 Codex leads
GPT-4.1: 34.4 (#238), GPT-5.2 Codex: 45.5 (#71)
| Benchmark | GPT-4.1 | GPT-5.2 Codex |
|---|---|---|
| SWE-bench Verified (bash only) | 39.6% | 72.8% |
| ALE-Bench | 558.1 | 1,300 |
| SWE-bench Verified | 48.5% | — |
| Aider Polyglot | 52.4% | — |
| LMArena WebDev | — | 1339 |
| SWE-bench Multilingual | — | 66.3% |
| WeirdML | 39% | — |
| LMArena Coding | 1391 | — |
| CadEval | 42% | — |
Agentic & Tool Use GPT-5.2 Codex leads
GPT-4.1: 34.7 (#43), GPT-5.2 Codex: 41.0 (#22)
| Benchmark | GPT-4.1 | GPT-5.2 Codex |
|---|---|---|
| Terminal-Bench | — | 66.5% |
| Berkeley Function Calling Leaderboard | 54% | — |
Reasoning Not comparable
GPT-4.1: 11.7 (#339), GPT-5.2 Codex: —
| Benchmark | GPT-4.1 | GPT-5.2 Codex |
|---|---|---|
| ARC-AGI-2 | 0.4% | — |
| SimpleBench | 27% | — |
| Kagi LLM Benchmark | 52.3% | — |
| ARC-AGI-1 | 5.5% | — |
| Chess Puzzles | 6% | — |
| EnigmaEval | 2.2% | — |
| LMArena Hard Prompts | 1384 | — |
| DTBench | 68.3% | — |
| LMCA | 25.6% | — |
| Epoch Capabilities Index | 136.78 | — |
| ForecastBench | 61.5 | — |
Math Not comparable
GPT-4.1: 22.3 (#280), GPT-5.2 Codex: —
| Benchmark | GPT-4.1 | GPT-5.2 Codex |
|---|---|---|
| FrontierMath (Tiers 1-3) | 6% | — |
| OTIS Mock AIME 2024-2025 | 38.3% | — |
| Omni-MATH | 47.1% | — |
| LMArena Math | 1370 | — |
| MATH Level 5 | 83% | — |
| FrontierMath (Feb 2025 set) | 5.5% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge Not comparable
GPT-4.1: 37.1 (#160), GPT-5.2 Codex: —
| Benchmark | GPT-4.1 | GPT-5.2 Codex |
|---|---|---|
| GPQA Diamond | 66.9% | — |
| Humanity's Last Exam | 5.4% | — |
| SimpleQA Verified | 31.1% | — |
| MMLU-Pro | 81.1% | — |
| Vectara Hallucination Rate | 5.6% | — |
| GPQA (HELM) | 65.9% | — |
| LMArena Expert | 1364 | — |
Multimodal Not comparable
GPT-4.1: 38.2 (#67), GPT-5.2 Codex: —
| Benchmark | GPT-4.1 | GPT-5.2 Codex |
|---|---|---|
| LMArena Vision | 1211 | — |
| GeoBench | 72% | — |
Multilingual Not comparable
GPT-4.1: 49.4 (#133), GPT-5.2 Codex: —
| Benchmark | GPT-4.1 | GPT-5.2 Codex |
|---|---|---|
| LMArena Non-English | 1370 | — |
| LMArena Chinese | 1382 | — |
| LMArena French | 1382 | — |
| LMArena German | 1381 | — |
| LMArena Japanese | 1319 | — |
| LMArena Korean | 1339 | — |
| LMArena Russian | 1377 | — |
| LMArena Spanish | 1376 | — |
Instruction Following Not comparable
GPT-4.1: 71.3 (#153), GPT-5.2 Codex: —
| Benchmark | GPT-4.1 | GPT-5.2 Codex |
|---|---|---|
| IFEval | 83.8% | — |
| LMArena Instruction Following | 1367 | — |
Long Context Not comparable
GPT-4.1: 40.0 (#163), GPT-5.2 Codex: —
| Benchmark | GPT-4.1 | GPT-5.2 Codex |
|---|---|---|
| Fiction.LiveBench | 63.9% | — |
| LMArena Longer Query | 1385 | — |
Writing & Preference Not comparable
GPT-4.1: 57.6 (#125), GPT-5.2 Codex: —
| Benchmark | GPT-4.1 | GPT-5.2 Codex |
|---|---|---|
| LMArena Text | 1383 | — |
| LMArena Creative Writing | 1363 | — |
| EQ-Bench Creative Writing | 1420 | — |
| WildBench | 85.4% | — |
| LMArena Multi-Turn | 1398 | — |
Frequently asked questions
Is GPT-4.1 better than GPT-5.2 Codex?
GPT-5.2 Codex is the stronger model overall, scoring 42.6 to 35.9 on the Noometry Index.
Which is cheaper, GPT-4.1 or GPT-5.2 Codex?
GPT-4.1 is cheaper. It lists at $2 per million input tokens and $8 per million output tokens; GPT-5.2 Codex lists at $1.75 and $14.
Is GPT-4.1 or GPT-5.2 Codex better for coding?
GPT-5.2 Codex scores higher on coding benchmarks: 45.5 versus 34.4 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 does, with 1.05M tokens against 400K.
How many benchmarks do GPT-4.1 and GPT-5.2 Codex share?
2 benchmarks have published results for both models. GPT-4.1 has 52 scored results on Noometry and GPT-5.2 Codex has 5.