Trinity Large Thinking — Benchmarks

Benchmark scores for Trinity Large Thinking aggregated from public leaderboards (5 boards), with how it ranks among open models and how it compares with its nearest neighbours. See hardware requirements for what you need to run it.

No llmrun Composite Score for Trinity Large Thinking: the score is only published for a model measured on at least 4 of the boards in the score panel, spanning at least 2 benchmark categories and including a reasoning or coding board — or on 3 boards that narrow its score to a 90% range of at most 15.6 points. Either way the results must come from at least two different benchmarks. Its individual scores below stand on their own — see how the llmrun Composite Score gets calculated.

Trinity Large Thinking reasoning benchmarks

Multi-step logic and problem-solving — can the model think through a hard problem rather than recall an answer.

CritPt
CritPt (Critical Points) tests graduate-level physics problem-solving on research-style questions spanning mechanics, electromagnetism, quantum mechanics, and more. It was created by physicists to probe whether a model can reason through multi-step physics rather than pattern-match textbook answers.
0.9%
0.9%
median 1.1%open leader 26.6%
Overall best: GPT 5.6 Sol Max 32.3%
46th percentile · #35 of 66 open · #162 of 219 all
#35 of 66
#162 of 219
Lab-reported
Epoch AI · Apr 2026

Trinity Large Thinking coding benchmarks

Writing, editing, and fixing real code — measured by whether the resulting program actually runs and passes tests.

SciCode
SciCode asks a model to write real scientific-computing code — implementing multi-step numerical methods drawn from physics, chemistry, biology, and math research — and checks the output against reference solutions. It was built by a team of scientists and ML researchers to test coding ability on genuine research problems, not typical software tasks.
36.1%
36.1%
median 38.7%open leader 60.9%
Overall best: Claude Opus 5.5 Max 66.9%
38th percentile · #41 of 66 open · #177 of 207 all
#41 of 66
#177 of 207
Lab-reported
Epoch AI · Apr 2026
Surface Evolver Bench
Surface Evolver Bench tests whether a model can write a correct simulation file for Surface Evolver, a physics tool that models surfaces shaped by tension, gravity and volume constraints, defining a 3D structure in its domain-specific format from only a few examples. Scores compare the resulting geometry — volume, area and energy — against reference solutions; the benchmark was built by an independent developer (GitHub: yhenon).
15.6%
15.6%
median 45.0%open leader 95.0%
4th percentile · #12 of 13 open · #27 of 28 all
#12 of 13
#27 of 28
Lab-reported
Epoch AI · Apr 2026

Other results (1)· leaderboard-only, not part of the llmrun Score

LMArena WebDev
Code Arena (formerly WebDev Arena) is Arena's head-to-head coding leaderboard: two models each build a real web app or UI from the same prompt, and people vote blind on which result is better. The rating shown is a relative Bradley-Terry score, not a percentage — compare it only to other models on this board.
1237.9
1237.9
median 1411.4open leader 1655.2
Overall best: Claude Opus 5.5 (Max) 1807.3
6th percentile · #49 of 52 open · #129 of 138 all
#49 of 52
#129 of 138
Arena
Arena · Oct 2026

Trinity Large Thinking instruction following benchmarks

How precisely a model obeys explicit, verifiable instructions — format, length, and content constraints — and, more broadly, how much people prefer its responses head-to-head in blind human voting.

LMArena Text
Arena (arena.ai, formerly LMArena / Chatbot Arena) ranks models by millions of blind, head-to-head human votes on real prompts. The Arena Score shown here is a Bradley-Terry rating computed with Arena's default style control, so higher means people preferred that model's answers more often — it's a relative rating, not a percentage, so compare it only to other models on this board.
1367.3
1367.3
median 1321.5open leader 1487.1
Overall best: Gemini 4 Argon (High) 1523.9
66th percentile · #65 of 187 open · #190 of 405 all
#65 of 187
#190 of 405
Arena
Arena · Oct 2026

Scores aggregated from public benchmark sources (Epoch AI: 3 boards, Arena: 2 boards) — each linked from the benchmark pages. llmrun does not run these benchmarks. Percentiles and ranks are among open models in the llmrun catalogue; the median and leader marks refer to the same field.