Model comparison
GPT-5.3 Codex vs GPT-5.6 Terra
GPT-5.6 Terra is the stronger model overall, scoring 59.1 to 45.5 on the Noometry Index.
Last verified . 5 shared benchmarks.
Summary
- They share 5 benchmarks with published results for both. GPT-5.3 Codex scores higher in 1 category and GPT-5.6 Terra in 1 category; 2 gaps are clear of the uncertainty.
- The widest gap is in coding, where GPT-5.6 Terra leads 57.1 to 48.5.
- GPT-5.6 Terra is cheaper at $2 / $12 per million input/output tokens, against $1.75 / $14 for GPT-5.3 Codex.
- GPT-5.6 Terra accepts more context: 1.05M tokens versus 400K.
Side by side
| GPT-5.3 Codex | GPT-5.6 Terra | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 45.5 | 59.1 |
| Released | 2026-02-05 | 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 | 8 | 52 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GPT-5.6 Terra leads
GPT-5.3 Codex: 48.5 (#51), GPT-5.6 Terra: 57.1 (#16)
| Benchmark | GPT-5.3 Codex | GPT-5.6 Terra |
|---|---|---|
| LMArena WebDev | 1408 | 1520 |
| WeirdML | 79.3% | 78.3% |
| ALE-Bench | 1,655 | 1,951 |
| SWE-bench Verified | 74.8% | — |
| DeepSWE | — | 69.6% |
| FrontierCode | — | 41.3% |
| CursorBench | — | 41.3% |
| SciCode | — | 55% |
| LMArena Coding | — | 1484 |
Agentic & Tool Use GPT-5.3 Codex leads
GPT-5.3 Codex: 47.8 (#9), GPT-5.6 Terra: 40.2 (#23)
| Benchmark | GPT-5.3 Codex | GPT-5.6 Terra |
|---|---|---|
| Vending-Bench 2 | 5,940 | 7,343 |
| Terminal-Bench | 78.4% | — |
| APEX-Agents | — | 58.2% |
| BALROG | — | 53.2% |
| GDP.pdf | — | 24.7% |
| METR Time Horizons | 74.5% | — |
Reasoning Not comparable
GPT-5.3 Codex: —, GPT-5.6 Terra: 60.6 (#19)
| Benchmark | GPT-5.3 Codex | GPT-5.6 Terra |
|---|---|---|
| Epoch Capabilities Index | 156.84 | 159.31 |
| 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 | — | 1467 |
| Mystery Game Puzzles | — | 35% |
| DTBench | — | 93.3% |
| LMCA | — | 55% |
| Surface Evolver Bench | — | 83.8% |
Math Not comparable
GPT-5.3 Codex: —, GPT-5.6 Terra: 81.5 (#10)
| Benchmark | GPT-5.3 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 | — | 1463 |
Knowledge Not comparable
GPT-5.3 Codex: —, GPT-5.6 Terra: 61.3 (#27)
| Benchmark | GPT-5.3 Codex | GPT-5.6 Terra |
|---|---|---|
| GPQA Diamond | — | 93.3% |
| SimpleQA Verified | — | 43.2% |
| LMArena Expert | — | 1492 |
Multimodal Not comparable
GPT-5.3 Codex: —, GPT-5.6 Terra: 47.5 (#10)
| Benchmark | GPT-5.3 Codex | GPT-5.6 Terra |
|---|---|---|
| LMArena Vision | — | 1271 |
| Blueprint-Bench 2 | — | 30.8% |
| Furniture Assembly | — | 54.2% |
| LMArena Document | — | 1472 |
Multilingual Not comparable
GPT-5.3 Codex: —, GPT-5.6 Terra: 54.5 (#42)
| Benchmark | GPT-5.3 Codex | GPT-5.6 Terra |
|---|---|---|
| LMArena Non-English | — | 1439 |
| LMArena Chinese | — | 1514 |
| LMArena French | — | 1476 |
| LMArena German | — | 1462 |
| LMArena Japanese | — | 1446 |
| LMArena Korean | — | 1420 |
| LMArena Russian | — | 1450 |
| LMArena Spanish | — | 1455 |
Instruction Following Not comparable
GPT-5.3 Codex: —, GPT-5.6 Terra: 76.6 (#38)
| Benchmark | GPT-5.3 Codex | GPT-5.6 Terra |
|---|---|---|
| LMArena Instruction Following | — | 1453 |
Long Context Not comparable
GPT-5.3 Codex: —, GPT-5.6 Terra: 44.4 (#64)
| Benchmark | GPT-5.3 Codex | GPT-5.6 Terra |
|---|---|---|
| LMArena Longer Query | — | 1452 |
Writing & Preference Not comparable
GPT-5.3 Codex: —, GPT-5.6 Terra: 70.4 (#21)
| Benchmark | GPT-5.3 Codex | GPT-5.6 Terra |
|---|---|---|
| LMArena Text | — | 1446 |
| LMArena Creative Writing | — | 1411 |
| EQ-Bench Creative Writing | — | 1855 |
| EQ-Bench 4 | — | 1234 |
| LMArena Multi-Turn | — | 1451 |
Frequently asked questions
Is GPT-5.3 Codex better than GPT-5.6 Terra?
GPT-5.6 Terra is the stronger model overall, scoring 59.1 to 45.5 on the Noometry Index.
Which is cheaper, GPT-5.3 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-5.3 Codex lists at $1.75 and $14.
Is GPT-5.3 Codex or GPT-5.6 Terra better for coding?
GPT-5.6 Terra scores higher on coding benchmarks: 57.1 versus 48.5 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-5.3 Codex and GPT-5.6 Terra share?
5 benchmarks have published results for both models. GPT-5.3 Codex has 8 scored results on Noometry and GPT-5.6 Terra has 52.