Model comparison
GPT-5.2 Codex vs Trinity Large Thinking
GPT-5.2 Codex is the stronger model overall, scoring 42.6 to 38.6 on the Noometry Index. Trinity Large Thinking costs 12× less per token, which makes it the better buy when GPT-5.2 Codex's lead doesn't matter for your workload.
Last verified . 1 shared benchmarks.
Summary
- They share 1 benchmark with published results for both. GPT-5.2 Codex scores higher in 1 category and Trinity Large Thinking in 0 categories; one gap is clear of the uncertainty.
- The widest gap is in coding, where GPT-5.2 Codex leads 45.5 to 34.1.
- Trinity Large Thinking is cheaper at $0.25 / $0.80 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.
- Trinity Large Thinking has downloadable open weights; the other is API-only.
Side by side
| GPT-5.2 Codex | Trinity Large Thinking | |
|---|---|---|
| Provider | OpenAI | Arcee AI |
| Noometry Index | 42.6 | 38.6 |
| Released | 2025-12-18 | 2026-04-01 |
| Weights | Proprietary | Open |
| Context window | 400K | 262K |
| Max output | 128K | 80K |
| Input $ / M tokens | $1.75 | $0.25 |
| Output $ / M tokens | $14 | $0.80 |
| Results tracked | 5 | 24 |
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Category by category
Coding GPT-5.2 Codex leads
GPT-5.2 Codex: 45.5 (#71), Trinity Large Thinking: 34.1 (#244)
| Benchmark | GPT-5.2 Codex | Trinity Large Thinking |
|---|---|---|
| LMArena WebDev | 1339 | 1238 |
| SWE-bench Verified (bash only) | 72.8% | — |
| SWE-bench Multilingual | 66.3% | — |
| SciCode | — | 36.1% |
| LMArena Coding | — | 1381 |
| ALE-Bench | 1,300 | — |
Agentic & Tool Use Not comparable
GPT-5.2 Codex: 41.0 (#22), Trinity Large Thinking: —
| Benchmark | GPT-5.2 Codex | Trinity Large Thinking |
|---|---|---|
| Terminal-Bench | 66.5% | — |
Reasoning Not comparable
GPT-5.2 Codex: —, Trinity Large Thinking: 16.9 (#298)
| Benchmark | GPT-5.2 Codex | Trinity Large Thinking |
|---|---|---|
| NYT Connections (extended) | — | 16.5% |
| CritPt | — | 0.9% |
| Thematic Generalization | — | 41.6% |
| LMArena Hard Prompts | — | 1350 |
| Surface Evolver Bench | — | 15.6% |
Math Not comparable
GPT-5.2 Codex: —, Trinity Large Thinking: 37.6 (#149)
| Benchmark | GPT-5.2 Codex | Trinity Large Thinking |
|---|---|---|
| LMArena Math | — | 1366 |
Knowledge Not comparable
GPT-5.2 Codex: —, Trinity Large Thinking: 40.9 (#113)
| Benchmark | GPT-5.2 Codex | Trinity Large Thinking |
|---|---|---|
| Vectara Hallucination Rate | — | 6.9% |
| LMArena Expert | — | 1360 |
Multilingual Not comparable
GPT-5.2 Codex: —, Trinity Large Thinking: 46.2 (#160)
| Benchmark | GPT-5.2 Codex | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | — | 1325 |
| LMArena Chinese | — | 1373 |
| LMArena French | — | 1374 |
| LMArena German | — | 1356 |
| LMArena Japanese | — | 1311 |
| LMArena Korean | — | 1306 |
| LMArena Russian | — | 1337 |
| LMArena Spanish | — | 1357 |
Instruction Following Not comparable
GPT-5.2 Codex: —, Trinity Large Thinking: 70.5 (#162)
| Benchmark | GPT-5.2 Codex | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | — | 1334 |
Long Context Not comparable
GPT-5.2 Codex: —, Trinity Large Thinking: 41.3 (#144)
| Benchmark | GPT-5.2 Codex | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | — | 1355 |
Writing & Preference Not comparable
GPT-5.2 Codex: —, Trinity Large Thinking: 53.8 (#158)
| Benchmark | GPT-5.2 Codex | Trinity Large Thinking |
|---|---|---|
| LMArena Text | — | 1340 |
| LMArena Creative Writing | — | 1320 |
| LMArena Multi-Turn | — | 1342 |
Frequently asked questions
Is GPT-5.2 Codex better than Trinity Large Thinking?
GPT-5.2 Codex is the stronger model overall, scoring 42.6 to 38.6 on the Noometry Index. Trinity Large Thinking costs 12× less per token, which makes it the better buy when GPT-5.2 Codex's lead doesn't matter for your workload.
Which is cheaper, GPT-5.2 Codex or Trinity Large Thinking?
Trinity Large Thinking is cheaper. It lists at $0.25 per million input tokens and $0.80 per million output tokens; GPT-5.2 Codex lists at $1.75 and $14.
Is GPT-5.2 Codex or Trinity Large Thinking better for coding?
GPT-5.2 Codex scores higher on coding benchmarks: 45.5 versus 34.1 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 Trinity Large Thinking share?
1 benchmark has published results for both models. GPT-5.2 Codex has 5 scored results on Noometry and Trinity Large Thinking has 24.