Model comparison
GPT-5.2 Codex vs GPT-5.6 Terra
GPT-5.6 Terra is the stronger model overall, scoring 59.2 to 42.6 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 GPT-5.6 Terra in 1 category; one gap is clear of the uncertainty.
- The widest gap is in coding, where GPT-5.6 Terra leads 57.7 to 45.5.
- GPT-5.6 Terra is cheaper at $2 / $12 per million input/output tokens, against $1.75 / $14 for GPT-5.2 Codex.
- GPT-5.6 Terra accepts more context: 1.05M tokens versus 400K.
Side by side
| GPT-5.2 Codex | GPT-5.6 Terra | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 42.6 | 59.2 |
| Released | 2025-12-18 | 2026-07-09 |
| Weights | Proprietary | Proprietary |
| Context window | 400K | 1.05M |
| Max output | 128K | 128K |
| Input $ / M tokens | $1.75 | $2 |
| Output $ / M tokens | $14 | $12 |
| Results tracked | 5 | 52 |
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Category by category
Coding GPT-5.6 Terra leads
GPT-5.2 Codex: 45.5 (#71), GPT-5.6 Terra: 57.7 (#19)
| Benchmark | GPT-5.2 Codex | GPT-5.6 Terra |
|---|---|---|
| LMArena WebDev | 1339 | 1522 |
| ALE-Bench | 1,300 | 1,951 |
| DeepSWE | — | 69.6% |
| FrontierCode | — | 41.3% |
| SWE-bench Verified (bash only) | 72.8% | — |
| CursorBench | — | 41.3% |
| SWE-bench Multilingual | 66.3% | — |
| SciCode | — | 55% |
| WeirdML | — | 78.3% |
| LMArena Coding | — | 1484 |
Agentic & Tool Use Too close to call
GPT-5.2 Codex: 41.0 (#22), GPT-5.6 Terra: 40.1 (#25)
| Benchmark | GPT-5.2 Codex | GPT-5.6 Terra |
|---|---|---|
| Terminal-Bench | 66.5% | — |
| APEX-Agents | — | 58.2% |
| BALROG | — | 53.2% |
| GDP.pdf | — | 24.7% |
| Vending-Bench 2 | — | 7,343 |
Reasoning Not comparable
GPT-5.2 Codex: —, GPT-5.6 Terra: 60.7 (#21)
| Benchmark | GPT-5.2 Codex | GPT-5.6 Terra |
|---|---|---|
| ARC-AGI-2 | — | 83.9% |
| SimpleBench | — | 48.9% |
| Kagi LLM Benchmark | — | 51.3% |
| NYT Connections (extended) | — | 78.4% |
| ARC-AGI-1 | — | 96.5% |
| CritPt | — | 30% |
| Chess Puzzles | — | 54% |
| LMArena Hard Prompts | — | 1468 |
| Mystery Game Puzzles | — | 35% |
| DTBench | — | 93.3% |
| LMCA | — | 55% |
| Surface Evolver Bench | — | 83.8% |
| Epoch Capabilities Index | — | 159.62 |
Math Not comparable
GPT-5.2 Codex: —, GPT-5.6 Terra: 81.6 (#12)
| Benchmark | GPT-5.2 Codex | GPT-5.6 Terra |
|---|---|---|
| FrontierMath (Tiers 1-3) | — | 86% |
| FrontierMath Tier 4 | — | 70.7% |
| OTIS Mock AIME 2024-2025 | — | 99.7% |
| ProofBench | — | 74% |
| LMArena Math | — | 1466 |
Knowledge Not comparable
GPT-5.2 Codex: —, GPT-5.6 Terra: 61.2 (#30)
| Benchmark | GPT-5.2 Codex | GPT-5.6 Terra |
|---|---|---|
| GPQA Diamond | — | 93.3% |
| SimpleQA Verified | — | 43.2% |
| LMArena Expert | — | 1492 |
Multimodal Not comparable
GPT-5.2 Codex: —, GPT-5.6 Terra: 47.3 (#11)
| Benchmark | GPT-5.2 Codex | GPT-5.6 Terra |
|---|---|---|
| LMArena Vision | — | 1271 |
| Blueprint-Bench 2 | — | 30.8% |
| Furniture Assembly | — | 54.2% |
| LMArena Document | — | 1472 |
Multilingual Not comparable
GPT-5.2 Codex: —, GPT-5.6 Terra: 54.4 (#44)
| Benchmark | GPT-5.2 Codex | GPT-5.6 Terra |
|---|---|---|
| LMArena Non-English | — | 1439 |
| LMArena Chinese | — | 1513 |
| LMArena French | — | 1471 |
| LMArena German | — | 1460 |
| LMArena Japanese | — | 1457 |
| LMArena Korean | — | 1425 |
| LMArena Russian | — | 1450 |
| LMArena Spanish | — | 1448 |
Instruction Following Not comparable
GPT-5.2 Codex: —, GPT-5.6 Terra: 76.4 (#40)
| Benchmark | GPT-5.2 Codex | GPT-5.6 Terra |
|---|---|---|
| LMArena Instruction Following | — | 1454 |
Long Context Not comparable
GPT-5.2 Codex: —, GPT-5.6 Terra: 44.4 (#68)
| Benchmark | GPT-5.2 Codex | GPT-5.6 Terra |
|---|---|---|
| LMArena Longer Query | — | 1451 |
Writing & Preference Not comparable
GPT-5.2 Codex: —, GPT-5.6 Terra: 70.2 (#23)
| Benchmark | GPT-5.2 Codex | GPT-5.6 Terra |
|---|---|---|
| LMArena Text | — | 1447 |
| LMArena Creative Writing | — | 1410 |
| EQ-Bench Creative Writing | — | 1855 |
| EQ-Bench 4 | — | 1234 |
| LMArena Multi-Turn | — | 1449 |
Frequently asked questions
Is GPT-5.2 Codex better than GPT-5.6 Terra?
GPT-5.6 Terra is the stronger model overall, scoring 59.2 to 42.6 on the Noometry Index.
Which is cheaper, GPT-5.2 Codex or GPT-5.6 Terra?
GPT-5.6 Terra is cheaper. It lists at $2 per million input tokens and $12 per million output tokens; GPT-5.2 Codex lists at $1.75 and $14.
Is GPT-5.2 Codex or GPT-5.6 Terra better for coding?
GPT-5.6 Terra scores higher on coding benchmarks: 57.7 versus 45.5 in the Noometry coding category.
Which has the bigger context window?
GPT-5.6 Terra does, with 1.05M tokens against 400K.
How many benchmarks do GPT-5.2 Codex and GPT-5.6 Terra share?
2 benchmarks have published results for both models. GPT-5.2 Codex has 5 scored results on Noometry and GPT-5.6 Terra has 52.