Model comparison

GLM-4.6V vs Trinity Large Thinking

GLM-4.6V is the stronger model overall, scoring 41.3 to 38.6 on the Noometry Index.

Last verified October 11, 2026. 11 shared benchmarks.

GLM-4.6V Z.ai (Zhipu)

41.3

Rank #137 Confirmed

Trinity Large Thinking

Arcee AI

38.6

Rank #185 Confirmed

Summary

They share 11 benchmarks with published results for both. GLM-4.6V scores higher in 6 categories and Trinity Large Thinking in 1 category; 5 gaps are clear of the uncertainty.
The widest gap is in reasoning, where GLM-4.6V leads 27.6 to 16.9.
Trinity Large Thinking is cheaper at $0.25 / $0.80 per million input/output tokens, against $0.30 / $0.90 for GLM-4.6V.
Trinity Large Thinking accepts more context: 262K tokens versus 128K.

Side by side

GLM-4.6V and Trinity Large Thinking specifications
	GLM-4.6V	Trinity Large Thinking
Provider	Z.ai (Zhipu)	Arcee AI
Noometry Index	41.3	38.6
Released	2025-12-08	2026-04-01
Weights	Open	Open
Context window	128K	262K
Max output	33K	80K
Input $ / M tokens	$0.30	$0.25
Output $ / M tokens	$0.90	$0.80
Results tracked	12	24

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Category by category

Coding GLM-4.6V leads

GLM-4.6V: 40.9 (#128), Trinity Large Thinking: 34.1 (#244)

Coding benchmarks
Benchmark	GLM-4.6V	Trinity Large Thinking
LMArena Coding	1390	1381
LMArena WebDev	—	1238
SciCode	—	36.1%

Reasoning GLM-4.6V leads

GLM-4.6V: 27.6 (#115), Trinity Large Thinking: 16.9 (#298)

Reasoning benchmarks
Benchmark	GLM-4.6V	Trinity Large Thinking
LMArena Hard Prompts	1368	1350
NYT Connections (extended)	—	16.5%
CritPt	—	0.9%
Thematic Generalization	—	41.6%
Surface Evolver Bench	—	15.6%

Math Not comparable

GLM-4.6V: —, Trinity Large Thinking: 37.6 (#149)

Math benchmarks
Benchmark	GLM-4.6V	Trinity Large Thinking
LMArena Math	—	1366

Knowledge Trinity Large Thinking leads

GLM-4.6V: 38.0 (#149), Trinity Large Thinking: 40.9 (#113)

Knowledge benchmarks
Benchmark	GLM-4.6V	Trinity Large Thinking
LMArena Expert	1371	1360
Vectara Hallucination Rate	—	6.9%

Multimodal Not comparable

GLM-4.6V: 34.8 (#90), Trinity Large Thinking: —

Multimodal benchmarks
Benchmark	GLM-4.6V	Trinity Large Thinking
LMArena Vision	1164	—

Multilingual GLM-4.6V leads

GLM-4.6V: 48.6 (#141), Trinity Large Thinking: 46.2 (#160)

Multilingual benchmarks
Benchmark	GLM-4.6V	Trinity Large Thinking
LMArena Non-English	1359	1325
LMArena Chinese	1425	1373
LMArena Russian	1340	1337
LMArena French	—	1374
LMArena German	—	1356
LMArena Japanese	—	1311
LMArena Korean	—	1306
LMArena Spanish	—	1357

Instruction Following Too close to call

GLM-4.6V: 71.4 (#151), Trinity Large Thinking: 70.5 (#162)

Instruction Following benchmarks
Benchmark	GLM-4.6V	Trinity Large Thinking
LMArena Instruction Following	1352	1334

Long Context Too close to call

GLM-4.6V: 41.3 (#143), Trinity Large Thinking: 41.3 (#144)

Long Context benchmarks
Benchmark	GLM-4.6V	Trinity Large Thinking
LMArena Longer Query	1358	1355

Writing & Preference GLM-4.6V leads

GLM-4.6V: 56.6 (#137), Trinity Large Thinking: 53.8 (#158)

Writing & Preference benchmarks
Benchmark	GLM-4.6V	Trinity Large Thinking
LMArena Text	1377	1340
LMArena Creative Writing	1347	1320
LMArena Multi-Turn	1360	1342

Frequently asked questions

Is GLM-4.6V better than Trinity Large Thinking?

GLM-4.6V is the stronger model overall, scoring 41.3 to 38.6 on the Noometry Index.

Which is cheaper, GLM-4.6V 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; GLM-4.6V lists at $0.30 and $0.90.

Is GLM-4.6V or Trinity Large Thinking better for coding?

GLM-4.6V scores higher on coding benchmarks: 40.9 versus 34.1 in the Noometry coding category.

Which has the bigger context window?

Trinity Large Thinking does, with 262K tokens against 128K.

How many benchmarks do GLM-4.6V and Trinity Large Thinking share?

11 benchmarks have published results for both models. GLM-4.6V has 12 scored results on Noometry and Trinity Large Thinking has 24.