Model comparison
GPT-4.1 vs GPT-5.6 Terra
GPT-5.6 Terra is the stronger model overall, scoring 59.2 to 35.9 on the Noometry Index.
Last verified . 33 shared benchmarks.
Summary
- They share 33 benchmarks with published results for both. GPT-4.1 scores higher in 0 categories and GPT-5.6 Terra in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.6 Terra leads 81.6 to 22.3.
- The biggest single-benchmark swing is ARC-AGI-1: 5.5% for GPT-4.1 and 96.5% for GPT-5.6 Terra.
- GPT-4.1 is cheaper at $2 / $8 per million input/output tokens, against $2 / $12 for GPT-5.6 Terra.
- GPT-5.6 Terra accepts more context: 1.05M tokens versus 1.05M.
Side by side
| GPT-4.1 | GPT-5.6 Terra | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 35.9 | 59.2 |
| Released | 2025-04-14 | 2026-07-09 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 1.05M |
| Max output | 33K | 128K |
| Input $ / M tokens | $2 | $2 |
| Output $ / M tokens | $8 | $12 |
| Results tracked | 52 | 52 |
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Category by category
Coding GPT-5.6 Terra leads
GPT-4.1: 34.4 (#238), GPT-5.6 Terra: 57.7 (#19)
| Benchmark | GPT-4.1 | GPT-5.6 Terra |
|---|---|---|
| WeirdML | 39% | 78.3% |
| LMArena Coding | 1391 | 1484 |
| ALE-Bench | 558.1 | 1,951 |
| SWE-bench Verified | 48.5% | — |
| DeepSWE | — | 69.6% |
| FrontierCode | — | 41.3% |
| SWE-bench Verified (bash only) | 39.6% | — |
| Aider Polyglot | 52.4% | — |
| CursorBench | — | 41.3% |
| LMArena WebDev | — | 1522 |
| SciCode | — | 55% |
| CadEval | 42% | — |
Agentic & Tool Use GPT-5.6 Terra leads
GPT-4.1: 34.7 (#43), GPT-5.6 Terra: 40.1 (#25)
| Benchmark | GPT-4.1 | GPT-5.6 Terra |
|---|---|---|
| APEX-Agents | — | 58.2% |
| Berkeley Function Calling Leaderboard | 54% | — |
| BALROG | — | 53.2% |
| GDP.pdf | — | 24.7% |
| Vending-Bench 2 | — | 7,343 |
Reasoning GPT-5.6 Terra leads
GPT-4.1: 11.7 (#339), GPT-5.6 Terra: 60.7 (#21)
| Benchmark | GPT-4.1 | GPT-5.6 Terra |
|---|---|---|
| ARC-AGI-2 | 0.4% | 83.9% |
| SimpleBench | 27% | 48.9% |
| Kagi LLM Benchmark | 52.3% | 51.3% |
| ARC-AGI-1 | 5.5% | 96.5% |
| Chess Puzzles | 6% | 54% |
| LMArena Hard Prompts | 1384 | 1468 |
| DTBench | 68.3% | 93.3% |
| LMCA | 25.6% | 55% |
| Epoch Capabilities Index | 136.78 | 159.62 |
| NYT Connections (extended) | — | 78.4% |
| CritPt | — | 30% |
| EnigmaEval | 2.2% | — |
| Mystery Game Puzzles | — | 35% |
| Surface Evolver Bench | — | 83.8% |
| ForecastBench | 61.5 | — |
Math GPT-5.6 Terra leads
GPT-4.1: 22.3 (#280), GPT-5.6 Terra: 81.6 (#12)
| Benchmark | GPT-4.1 | GPT-5.6 Terra |
|---|---|---|
| FrontierMath (Tiers 1-3) | 6% | 86% |
| OTIS Mock AIME 2024-2025 | 38.3% | 99.7% |
| LMArena Math | 1370 | 1466 |
| FrontierMath Tier 4 | — | 70.7% |
| ProofBench | — | 74% |
| Omni-MATH | 47.1% | — |
| MATH Level 5 | 83% | — |
| FrontierMath (Feb 2025 set) | 5.5% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge GPT-5.6 Terra leads
GPT-4.1: 37.1 (#160), GPT-5.6 Terra: 61.2 (#30)
| Benchmark | GPT-4.1 | GPT-5.6 Terra |
|---|---|---|
| GPQA Diamond | 66.9% | 93.3% |
| SimpleQA Verified | 31.1% | 43.2% |
| LMArena Expert | 1364 | 1492 |
| Humanity's Last Exam | 5.4% | — |
| MMLU-Pro | 81.1% | — |
| Vectara Hallucination Rate | 5.6% | — |
| GPQA (HELM) | 65.9% | — |
Multimodal GPT-5.6 Terra leads
GPT-4.1: 38.2 (#67), GPT-5.6 Terra: 47.3 (#11)
| Benchmark | GPT-4.1 | GPT-5.6 Terra |
|---|---|---|
| LMArena Vision | 1211 | 1271 |
| GeoBench | 72% | — |
| Blueprint-Bench 2 | — | 30.8% |
| Furniture Assembly | — | 54.2% |
| LMArena Document | — | 1472 |
Multilingual GPT-5.6 Terra leads
GPT-4.1: 49.4 (#133), GPT-5.6 Terra: 54.4 (#44)
| Benchmark | GPT-4.1 | GPT-5.6 Terra |
|---|---|---|
| LMArena Non-English | 1370 | 1439 |
| LMArena Chinese | 1382 | 1513 |
| LMArena French | 1382 | 1471 |
| LMArena German | 1381 | 1460 |
| LMArena Japanese | 1319 | 1457 |
| LMArena Korean | 1339 | 1425 |
| LMArena Russian | 1377 | 1450 |
| LMArena Spanish | 1376 | 1448 |
Instruction Following GPT-5.6 Terra leads
GPT-4.1: 71.3 (#153), GPT-5.6 Terra: 76.4 (#40)
| Benchmark | GPT-4.1 | GPT-5.6 Terra |
|---|---|---|
| LMArena Instruction Following | 1367 | 1454 |
| IFEval | 83.8% | — |
Long Context GPT-5.6 Terra leads
GPT-4.1: 40.0 (#163), GPT-5.6 Terra: 44.4 (#68)
| Benchmark | GPT-4.1 | GPT-5.6 Terra |
|---|---|---|
| LMArena Longer Query | 1385 | 1451 |
| Fiction.LiveBench | 63.9% | — |
Writing & Preference GPT-5.6 Terra leads
GPT-4.1: 57.6 (#125), GPT-5.6 Terra: 70.2 (#23)
| Benchmark | GPT-4.1 | GPT-5.6 Terra |
|---|---|---|
| LMArena Text | 1383 | 1447 |
| LMArena Creative Writing | 1363 | 1410 |
| EQ-Bench Creative Writing | 1420 | 1855 |
| LMArena Multi-Turn | 1398 | 1449 |
| WildBench | 85.4% | — |
| EQ-Bench 4 | — | 1234 |
Frequently asked questions
Is GPT-4.1 better than GPT-5.6 Terra?
GPT-5.6 Terra is the stronger model overall, scoring 59.2 to 35.9 on the Noometry Index.
Which is cheaper, GPT-4.1 or GPT-5.6 Terra?
GPT-4.1 is cheaper. It lists at $2 per million input tokens and $8 per million output tokens; GPT-5.6 Terra lists at $2 and $12.
Is GPT-4.1 or GPT-5.6 Terra better for coding?
GPT-5.6 Terra scores higher on coding benchmarks: 57.7 versus 34.4 in the Noometry coding category.
Which has the bigger context window?
GPT-5.6 Terra does, with 1.05M tokens against 1.05M.
How many benchmarks do GPT-4.1 and GPT-5.6 Terra share?
33 benchmarks have published results for both models. GPT-4.1 has 52 scored results on Noometry and GPT-5.6 Terra has 52.