Model comparison

GLM-4.6V vs Mistral Large 3

GLM-4.6V is the stronger model overall, scoring 41.3 to 39.1 on the Noometry Index.

Last verified October 11, 2026. 12 shared benchmarks.

GLM-4.6V Z.ai (Zhipu)

41.3

Rank #137 Confirmed

Mistral Large 3

Mistral AI

39.1

Rank #176 Confirmed

Summary

They share 12 benchmarks with published results for both. GLM-4.6V scores higher in 3 categories and Mistral Large 3 in 5 categories; 8 gaps are clear of the uncertainty.
The widest gap is in reasoning, where GLM-4.6V leads 27.6 to 15.2.
Mistral Large 3 is cheaper at $0.25 / $0.75 per million input/output tokens, against $0.30 / $0.90 for GLM-4.6V.
Mistral Large 3 accepts more context: 262K tokens versus 128K.

Side by side

GLM-4.6V and Mistral Large 3 specifications
	GLM-4.6V	Mistral Large 3
Provider	Z.ai (Zhipu)	Mistral AI
Noometry Index	41.3	39.1
Released	2025-12-08	2025-12-02
Weights	Open	Open
Context window	128K	262K
Max output	33K	8K
Input $ / M tokens	$0.30	$0.25
Output $ / M tokens	$0.90	$0.75
Results tracked	12	24

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Category by category

Coding GLM-4.6V leads

GLM-4.6V: 40.9 (#128), Mistral Large 3: 34.4 (#237)

Coding benchmarks
Benchmark	GLM-4.6V	Mistral Large 3
LMArena Coding	1390	1448
LMArena WebDev	—	1230

Reasoning GLM-4.6V leads

GLM-4.6V: 27.6 (#115), Mistral Large 3: 15.2 (#319)

Reasoning benchmarks
Benchmark	GLM-4.6V	Mistral Large 3
LMArena Hard Prompts	1368	1429
Kagi LLM Benchmark	—	50.9%
NYT Connections (extended)	—	7.5%
Thematic Generalization	—	23%

Math Not comparable

GLM-4.6V: —, Mistral Large 3: 38.7 (#129)

Math benchmarks
Benchmark	GLM-4.6V	Mistral Large 3
LMArena Math	—	1414

Knowledge GLM-4.6V leads

GLM-4.6V: 38.0 (#149), Mistral Large 3: 36.0 (#177)

Knowledge benchmarks
Benchmark	GLM-4.6V	Mistral Large 3
LMArena Expert	1371	1421
Vectara Hallucination Rate	—	14.5%

Multimodal Mistral Large 3 leads

GLM-4.6V: 34.8 (#90), Mistral Large 3: 38.2 (#66)

Multimodal benchmarks
Benchmark	GLM-4.6V	Mistral Large 3
LMArena Vision	1164	1221

Multilingual Mistral Large 3 leads

GLM-4.6V: 48.6 (#141), Mistral Large 3: 52.5 (#84)

Multilingual benchmarks
Benchmark	GLM-4.6V	Mistral Large 3
LMArena Non-English	1359	1413
LMArena Chinese	1425	1447
LMArena Russian	1340	1411
LMArena French	—	1455
LMArena German	—	1437
LMArena Japanese	—	1394
LMArena Korean	—	1384
LMArena Spanish	—	1440

Instruction Following Mistral Large 3 leads

GLM-4.6V: 71.4 (#151), Mistral Large 3: 74.0 (#108)

Instruction Following benchmarks
Benchmark	GLM-4.6V	Mistral Large 3
LMArena Instruction Following	1352	1403

Long Context Mistral Large 3 leads

GLM-4.6V: 41.3 (#143), Mistral Large 3: 43.1 (#105)

Long Context benchmarks
Benchmark	GLM-4.6V	Mistral Large 3
LMArena Longer Query	1358	1413

Writing & Preference Mistral Large 3 leads

GLM-4.6V: 56.6 (#137), Mistral Large 3: 60.0 (#101)

Writing & Preference benchmarks
Benchmark	GLM-4.6V	Mistral Large 3
LMArena Text	1377	1428
LMArena Creative Writing	1347	1386
LMArena Multi-Turn	1360	1429
EQ-Bench Creative Writing	—	1412

Frequently asked questions

Is GLM-4.6V better than Mistral Large 3?

GLM-4.6V is the stronger model overall, scoring 41.3 to 39.1 on the Noometry Index.

Which is cheaper, GLM-4.6V or Mistral Large 3?

Mistral Large 3 is cheaper. It lists at $0.25 per million input tokens and $0.75 per million output tokens; GLM-4.6V lists at $0.30 and $0.90.

Is GLM-4.6V or Mistral Large 3 better for coding?

GLM-4.6V scores higher on coding benchmarks: 40.9 versus 34.4 in the Noometry coding category.

Which has the bigger context window?

Mistral Large 3 does, with 262K tokens against 128K.

How many benchmarks do GLM-4.6V and Mistral Large 3 share?

12 benchmarks have published results for both models. GLM-4.6V has 12 scored results on Noometry and Mistral Large 3 has 24.