Model comparison

Gemma 3n E4b IT vs GLM-4.6V

GLM-4.6V is the stronger model overall, scoring 40.9 to 36.7 on the Noometry Index. Gemma 3n E4b IT costs 6.0× less per token, which makes it the better buy when GLM-4.6V's lead doesn't matter for your workload.

Last verified October 10, 2026. 11 shared benchmarks.

Gemma 3n E4b IT

Google

36.7

Rank #203 Confirmed

GLM-4.6V Z.ai (Zhipu)

40.9

Rank #133 Confirmed

Summary

They share 11 benchmarks with published results for both. Gemma 3n E4b IT scores higher in 0 categories and GLM-4.6V in 7 categories; 7 gaps are clear of the uncertainty.
The widest gap is in reasoning, where GLM-4.6V leads 26.5 to 19.2.
Gemma 3n E4b IT is cheaper at $0.06 / $0.12 per million input/output tokens, against $0.30 / $0.90 for GLM-4.6V.
GLM-4.6V accepts more context: 128K tokens versus 33K.

Side by side

Gemma 3n E4b IT and GLM-4.6V specifications
	Gemma 3n E4b IT	GLM-4.6V
Provider	Google	Z.ai (Zhipu)
Noometry Index	36.7	40.9
Released	2025-05-20	2025-12-08
Weights	Open	Open
Context window	33K	128K
Max output	33K	33K
Input $ / M tokens	$0.06	$0.30
Output $ / M tokens	$0.12	$0.90
Results tracked	18	12

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Category by category

Coding GLM-4.6V leads

Gemma 3n E4b IT: 36.4 (#193), GLM-4.6V: 40.2 (#128)

Coding benchmarks
Benchmark	Gemma 3n E4b IT	GLM-4.6V
LMArena Coding	1269	1390

Reasoning GLM-4.6V leads

Gemma 3n E4b IT: 19.2 (#239), GLM-4.6V: 26.5 (#117)

Reasoning benchmarks
Benchmark	Gemma 3n E4b IT	GLM-4.6V
LMArena Hard Prompts	1284	1368
Kagi LLM Benchmark	31.5%	—

Math Not comparable

Gemma 3n E4b IT: 32.5 (#186), GLM-4.6V: —

Math benchmarks
Benchmark	Gemma 3n E4b IT	GLM-4.6V
LMArena Math	1251	—

Knowledge GLM-4.6V leads

Gemma 3n E4b IT: 33.6 (#193), GLM-4.6V: 37.4 (#148)

Knowledge benchmarks
Benchmark	Gemma 3n E4b IT	GLM-4.6V
LMArena Expert	1245	1372

Multimodal Not comparable

Gemma 3n E4b IT: —, GLM-4.6V: 34.2 (#83)

Multimodal benchmarks
Benchmark	Gemma 3n E4b IT	GLM-4.6V
LMArena Vision	—	1164

Multilingual GLM-4.6V leads

Gemma 3n E4b IT: 43.5 (#179), GLM-4.6V: 48.8 (#135)

Multilingual benchmarks
Benchmark	Gemma 3n E4b IT	GLM-4.6V
LMArena Non-English	1285	1359
LMArena Chinese	1310	1426
LMArena Russian	1288	1341
LMArena French	1330	—
LMArena German	1312	—
LMArena Japanese	1274	—
LMArena Korean	1259	—
LMArena Spanish	1305	—

Instruction Following GLM-4.6V leads

Gemma 3n E4b IT: 66.3 (#205), GLM-4.6V: 71.6 (#145)

Instruction Following benchmarks
Benchmark	Gemma 3n E4b IT	GLM-4.6V
LMArena Instruction Following	1255	1351

Long Context GLM-4.6V leads

Gemma 3n E4b IT: 38.8 (#185), GLM-4.6V: 41.3 (#138)

Long Context benchmarks
Benchmark	Gemma 3n E4b IT	GLM-4.6V
LMArena Longer Query	1277	1358

Writing & Preference GLM-4.6V leads

Gemma 3n E4b IT: 50.3 (#181), GLM-4.6V: 56.8 (#132)

Writing & Preference benchmarks
Benchmark	Gemma 3n E4b IT	GLM-4.6V
LMArena Text	1306	1377
LMArena Creative Writing	1287	1347
LMArena Multi-Turn	1276	1359

Frequently asked questions

Is Gemma 3n E4b IT better than GLM-4.6V?

Which is cheaper, Gemma 3n E4b IT or GLM-4.6V?

Gemma 3n E4b IT is cheaper. It lists at $0.06 per million input tokens and $0.12 per million output tokens; GLM-4.6V lists at $0.30 and $0.90.

Is Gemma 3n E4b IT or GLM-4.6V better for coding?

GLM-4.6V scores higher on coding benchmarks: 40.2 versus 36.4 in the Noometry coding category.

Which has the bigger context window?

GLM-4.6V does, with 128K tokens against 33K.

How many benchmarks do Gemma 3n E4b IT and GLM-4.6V share?

11 benchmarks have published results for both models. Gemma 3n E4b IT has 18 scored results on Noometry and GLM-4.6V has 12.