Model comparison
GPT-5.1-Codex vs Trinity Large Thinking
GPT-5.1-Codex and Trinity Large Thinking score almost the same on the Noometry Index (38.6 vs 38.6), so choose on price, context window or the category you care about most.
Last verified . 1 shared benchmarks.
Arcee AISummary
- They share 1 benchmark with published results for both. GPT-5.1-Codex scores higher in 1 category and Trinity Large Thinking in 1 category; 2 gaps are clear of the uncertainty.
- The widest gap is in coding, where GPT-5.1-Codex leads 41.9 to 34.1.
- Trinity Large Thinking is cheaper at $0.25 / $0.80 per million input/output tokens, against $1.25 / $10 for GPT-5.1-Codex.
- GPT-5.1-Codex accepts more context: 400K tokens versus 262K.
- Trinity Large Thinking has downloadable open weights; the other is API-only.
Side by side
| GPT-5.1-Codex | Trinity Large Thinking | |
|---|---|---|
| Provider | OpenAI | Arcee AI |
| Noometry Index | 38.6 | 38.6 |
| Released | 2025-11-12 | 2026-04-01 |
| Weights | Proprietary | Open |
| Context window | 400K | 262K |
| Max output | 128K | 80K |
| Input $ / M tokens | $1.25 | $0.25 |
| Output $ / M tokens | $10 | $0.80 |
| Results tracked | 6 | 24 |
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Category by category
Coding GPT-5.1-Codex leads
GPT-5.1-Codex: 41.9 (#116), Trinity Large Thinking: 34.1 (#244)
| Benchmark | GPT-5.1-Codex | Trinity Large Thinking |
|---|---|---|
| LMArena WebDev | 1337 | 1238 |
| SWE-bench Verified (bash only) | 66% | — |
| SciCode | — | 36.1% |
| LMArena Coding | — | 1381 |
| ALE-Bench | 1,245 | — |
Agentic & Tool Use Not comparable
GPT-5.1-Codex: 38.0 (#33), Trinity Large Thinking: —
| Benchmark | GPT-5.1-Codex | Trinity Large Thinking |
|---|---|---|
| Terminal-Bench | 60.4% | — |
| METR Time Horizons | 70.8% | — |
Reasoning Not comparable
GPT-5.1-Codex: —, Trinity Large Thinking: 16.9 (#298)
| Benchmark | GPT-5.1-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 Trinity Large Thinking leads
GPT-5.1-Codex: 30.3 (#235), Trinity Large Thinking: 37.6 (#149)
| Benchmark | GPT-5.1-Codex | Trinity Large Thinking |
|---|---|---|
| ProofBench | 9% | — |
| LMArena Math | — | 1366 |
Knowledge Not comparable
GPT-5.1-Codex: —, Trinity Large Thinking: 40.9 (#113)
| Benchmark | GPT-5.1-Codex | Trinity Large Thinking |
|---|---|---|
| Vectara Hallucination Rate | — | 6.9% |
| LMArena Expert | — | 1360 |
Multilingual Not comparable
GPT-5.1-Codex: —, Trinity Large Thinking: 46.2 (#160)
| Benchmark | GPT-5.1-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-5.1-Codex: —, Trinity Large Thinking: 70.5 (#162)
| Benchmark | GPT-5.1-Codex | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | — | 1334 |
Long Context Not comparable
GPT-5.1-Codex: —, Trinity Large Thinking: 41.3 (#144)
| Benchmark | GPT-5.1-Codex | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | — | 1355 |
Writing & Preference Not comparable
GPT-5.1-Codex: —, Trinity Large Thinking: 53.8 (#158)
| Benchmark | GPT-5.1-Codex | Trinity Large Thinking |
|---|---|---|
| LMArena Text | — | 1340 |
| LMArena Creative Writing | — | 1320 |
| LMArena Multi-Turn | — | 1342 |
Frequently asked questions
Is GPT-5.1-Codex better than Trinity Large Thinking?
GPT-5.1-Codex and Trinity Large Thinking score almost the same on the Noometry Index (38.6 vs 38.6), so choose on price, context window or the category you care about most.
Which is cheaper, GPT-5.1-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-5.1-Codex lists at $1.25 and $10.
Is GPT-5.1-Codex or Trinity Large Thinking better for coding?
GPT-5.1-Codex scores higher on coding benchmarks: 41.9 versus 34.1 in the Noometry coding category.
Which has the bigger context window?
GPT-5.1-Codex does, with 400K tokens against 262K.
How many benchmarks do GPT-5.1-Codex and Trinity Large Thinking share?
1 benchmark has published results for both models. GPT-5.1-Codex has 6 scored results on Noometry and Trinity Large Thinking has 24.