Model comparison

GLM-4.6V vs Mistral Medium 3.5

GLM-4.6V is the stronger model overall, scoring 41.3 to 40.2 on the Noometry Index.

Last verified October 11, 2026. 12 shared benchmarks.

GLM-4.6V Z.ai (Zhipu)

41.3

Rank #137 Confirmed

Mistral Medium 3.5

Mistral AI

40.2

Rank #152 Confirmed

Summary

They share 12 benchmarks with published results for both. GLM-4.6V scores higher in 2 categories and Mistral Medium 3.5 in 6 categories; 8 gaps are clear of the uncertainty.
The widest gap is in reasoning, where GLM-4.6V leads 27.6 to 17.3.
GLM-4.6V is cheaper at $0.30 / $0.90 per million input/output tokens, against $1.50 / $7.50 for Mistral Medium 3.5.
Mistral Medium 3.5 accepts more context: 262K tokens versus 128K.

Side by side

GLM-4.6V and Mistral Medium 3.5 specifications
	GLM-4.6V	Mistral Medium 3.5
Provider	Z.ai (Zhipu)	Mistral AI
Noometry Index	41.3	40.2
Released	2025-12-08	—
Weights	Open	Open
Context window	128K	262K
Max output	33K	210K
Input $ / M tokens	$0.30	$1.50
Output $ / M tokens	$0.90	$7.50
Results tracked	12	22

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Category by category

Coding GLM-4.6V leads

GLM-4.6V: 40.9 (#128), Mistral Medium 3.5: 36.0 (#213)

Coding benchmarks
Benchmark	GLM-4.6V	Mistral Medium 3.5
LMArena Coding	1390	1461
LMArena WebDev	—	1264

Reasoning GLM-4.6V leads

GLM-4.6V: 27.6 (#115), Mistral Medium 3.5: 17.3 (#295)

Reasoning benchmarks
Benchmark	GLM-4.6V	Mistral Medium 3.5
LMArena Hard Prompts	1368	1436
Kagi LLM Benchmark	—	41.4%
NYT Connections (extended)	—	12.9%
Epoch Capabilities Index	—	141.35

Math Not comparable

GLM-4.6V: —, Mistral Medium 3.5: 39.1 (#113)

Math benchmarks
Benchmark	GLM-4.6V	Mistral Medium 3.5
LMArena Math	—	1431

Knowledge Mistral Medium 3.5 leads

GLM-4.6V: 38.0 (#149), Mistral Medium 3.5: 40.0 (#126)

Knowledge benchmarks
Benchmark	GLM-4.6V	Mistral Medium 3.5
LMArena Expert	1371	1432

Multimodal Mistral Medium 3.5 leads

GLM-4.6V: 34.8 (#90), Mistral Medium 3.5: 38.3 (#65)

Multimodal benchmarks
Benchmark	GLM-4.6V	Mistral Medium 3.5
LMArena Vision	1164	1223

Multilingual Mistral Medium 3.5 leads

GLM-4.6V: 48.6 (#141), Mistral Medium 3.5: 51.9 (#100)

Multilingual benchmarks
Benchmark	GLM-4.6V	Mistral Medium 3.5
LMArena Non-English	1359	1404
LMArena Chinese	1425	1442
LMArena Russian	1340	1395
LMArena French	—	1448
LMArena German	—	1451
LMArena Korean	—	1385
LMArena Spanish	—	1409

Instruction Following Mistral Medium 3.5 leads

GLM-4.6V: 71.4 (#151), Mistral Medium 3.5: 74.6 (#90)

Instruction Following benchmarks
Benchmark	GLM-4.6V	Mistral Medium 3.5
LMArena Instruction Following	1352	1415

Long Context Mistral Medium 3.5 leads

GLM-4.6V: 41.3 (#143), Mistral Medium 3.5: 43.2 (#103)

Long Context benchmarks
Benchmark	GLM-4.6V	Mistral Medium 3.5
LMArena Longer Query	1358	1415

Writing & Preference Mistral Medium 3.5 leads

GLM-4.6V: 56.6 (#137), Mistral Medium 3.5: 58.5 (#117)

Writing & Preference benchmarks
Benchmark	GLM-4.6V	Mistral Medium 3.5
LMArena Text	1377	1421
LMArena Creative Writing	1347	1374
LMArena Multi-Turn	1360	1423
EQ-Bench 4	—	993

Frequently asked questions

Is GLM-4.6V better than Mistral Medium 3.5?

GLM-4.6V is the stronger model overall, scoring 41.3 to 40.2 on the Noometry Index.

Which is cheaper, GLM-4.6V or Mistral Medium 3.5?

GLM-4.6V is cheaper. It lists at $0.30 per million input tokens and $0.90 per million output tokens; Mistral Medium 3.5 lists at $1.50 and $7.50.

Is GLM-4.6V or Mistral Medium 3.5 better for coding?

GLM-4.6V scores higher on coding benchmarks: 40.9 versus 36.0 in the Noometry coding category.

Which has the bigger context window?

Mistral Medium 3.5 does, with 262K tokens against 128K.

How many benchmarks do GLM-4.6V and Mistral Medium 3.5 share?

12 benchmarks have published results for both models. GLM-4.6V has 12 scored results on Noometry and Mistral Medium 3.5 has 22.