Model comparison

GLM-4.6V vs Mistral 7B

GLM-4.6V is the stronger model overall, scoring 41.3 to 23.0 on the Noometry Index. Mistral 7B costs 1.8× less per token, which makes it the better buy when GLM-4.6V's lead doesn't matter for your workload.

Last verified October 11, 2026. 11 shared benchmarks.

GLM-4.6V Z.ai (Zhipu)

41.3

Rank #137 Confirmed

Mistral 7B

Mistral AI

23.0

Rank #351 Confirmed

Summary

They share 11 benchmarks with published results for both. GLM-4.6V scores higher in 7 categories and Mistral 7B in 0 categories; 7 gaps are clear of the uncertainty.
The widest gap is in knowledge, where GLM-4.6V leads 38.0 to 7.4.
Mistral 7B is cheaper at $0.25 / $0.25 per million input/output tokens, against $0.30 / $0.90 for GLM-4.6V.
GLM-4.6V accepts more context: 128K tokens versus 8K.

Side by side

GLM-4.6V and Mistral 7B specifications
	GLM-4.6V	Mistral 7B
Provider	Z.ai (Zhipu)	Mistral AI
Noometry Index	41.3	23.0
Released	2025-12-08	2023-09-27
Weights	Open	Open
Context window	128K	8K
Max output	33K	8K
Input $ / M tokens	$0.30	$0.25
Output $ / M tokens	$0.90	$0.25
Results tracked	12	37

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Category by category

Coding GLM-4.6V leads

GLM-4.6V: 40.9 (#128), Mistral 7B: 26.4 (#326)

Coding benchmarks
Benchmark	GLM-4.6V	Mistral 7B
LMArena Coding	1390	1082
BigCodeBench Instruct	—	19.5%
BigCodeBench Complete	—	27.3%
HumanEval+	—	36%
MBPP+	—	42.1%

Reasoning GLM-4.6V leads

GLM-4.6V: 27.6 (#115), Mistral 7B: 13.1 (#336)

Reasoning benchmarks
Benchmark	GLM-4.6V	Mistral 7B
LMArena Hard Prompts	1368	1067
Chess Puzzles	—	0%
DTBench	—	42.5%
Adversarial NLI	—	47.1%
BIG-Bench Hard	—	56.1%
Epoch Capabilities Index	—	112.21
HellaSwag	—	81%
PIQA	—	83%
WinoGrande	—	75.3%

Math Not comparable

GLM-4.6V: —, Mistral 7B: 8.1 (#325)

Math benchmarks
Benchmark	GLM-4.6V	Mistral 7B
OTIS Mock AIME 2024-2025	—	0.3%
LMArena Math	—	1085
MATH Level 5	—	3.7%
GSM8K	—	54.4%

Knowledge GLM-4.6V leads

GLM-4.6V: 38.0 (#149), Mistral 7B: 7.4 (#311)

Knowledge benchmarks
Benchmark	GLM-4.6V	Mistral 7B
LMArena Expert	1371	1036
GPQA Diamond	—	15.2%
ARC (AI2) Challenge	—	78.6%
BoolQ	—	87.4%
MMLU	—	62.5%
OpenBookQA	—	79.8%
TriviaQA	—	75.2%

Multimodal Not comparable

GLM-4.6V: 34.8 (#90), Mistral 7B: —

Multimodal benchmarks
Benchmark	GLM-4.6V	Mistral 7B
LMArena Vision	1164	—

Multilingual GLM-4.6V leads

GLM-4.6V: 48.6 (#141), Mistral 7B: 25.8 (#283)

Multilingual benchmarks
Benchmark	GLM-4.6V	Mistral 7B
LMArena Non-English	1359	1012
LMArena Chinese	1425	1009
LMArena Russian	1340	1018
LMArena French	—	1037
LMArena German	—	987
LMArena Japanese	—	878
LMArena Spanish	—	1026

Instruction Following GLM-4.6V leads

GLM-4.6V: 71.4 (#151), Mistral 7B: 54.2 (#280)

Instruction Following benchmarks
Benchmark	GLM-4.6V	Mistral 7B
LMArena Instruction Following	1352	1060

Long Context GLM-4.6V leads

GLM-4.6V: 41.3 (#143), Mistral 7B: 32.2 (#271)

Long Context benchmarks
Benchmark	GLM-4.6V	Mistral 7B
LMArena Longer Query	1358	1060

Writing & Preference GLM-4.6V leads

GLM-4.6V: 56.6 (#137), Mistral 7B: 30.7 (#286)

Writing & Preference benchmarks
Benchmark	GLM-4.6V	Mistral 7B
LMArena Text	1377	1090
LMArena Creative Writing	1347	1068
LMArena Multi-Turn	1360	1062

Frequently asked questions

Is GLM-4.6V better than Mistral 7B?

Which is cheaper, GLM-4.6V or Mistral 7B?

Mistral 7B is cheaper. It lists at $0.25 per million input tokens and $0.25 per million output tokens; GLM-4.6V lists at $0.30 and $0.90.

Is GLM-4.6V or Mistral 7B better for coding?

GLM-4.6V scores higher on coding benchmarks: 40.9 versus 26.4 in the Noometry coding category.

Which has the bigger context window?

GLM-4.6V does, with 128K tokens against 8K.

How many benchmarks do GLM-4.6V and Mistral 7B share?

11 benchmarks have published results for both models. GLM-4.6V has 12 scored results on Noometry and Mistral 7B has 37.