Model comparison

GLM-4.5V vs Llama 3.2 3B

GLM-4.5V is the stronger model overall, scoring 39.2 to 28.4 on the Noometry Index. Llama 3.2 3B costs 7.5× less per token, which makes it the better buy when GLM-4.5V's lead doesn't matter for your workload.

Last verified October 10, 2026. 12 shared benchmarks.

GLM-4.5V Z.ai (Zhipu)

39.2

Rank #158 Confirmed

Llama 3.2 3B

Summary

They share 12 benchmarks with published results for both. GLM-4.5V scores higher in 8 categories and Llama 3.2 3B in 0 categories; 8 gaps are clear of the uncertainty.
The widest gap is in writing & preference, where GLM-4.5V leads 52.7 to 24.9.
Llama 3.2 3B is cheaper at $0.05 / $0.33 per million input/output tokens, against $0.60 / $1.80 for GLM-4.5V.
Llama 3.2 3B accepts more context: 131K tokens versus 64K.

Side by side

GLM-4.5V and Llama 3.2 3B specifications
	GLM-4.5V	Llama 3.2 3B
Provider	Z.ai (Zhipu)	Meta
Noometry Index	39.2	28.4
Released	2025-08-11	2024-09-24
Weights	Open	Open
Context window	64K	131K
Max output	16K	118K
Input $ / M tokens	$0.60	$0.05
Output $ / M tokens	$1.80	$0.33
Results tracked	15	18

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Category by category

Coding GLM-4.5V leads

GLM-4.5V: 38.9 (#152), Llama 3.2 3B: 27.1 (#314)

Coding benchmarks
Benchmark	GLM-4.5V	Llama 3.2 3B
LMArena Coding	1347	1098
BigCodeBench Instruct	—	23.4%
BigCodeBench Complete	—	28.3%

Agentic & Tool Use Not comparable

GLM-4.5V: —, Llama 3.2 3B: 19.9 (#135)

Agentic & Tool Use benchmarks
Benchmark	GLM-4.5V	Llama 3.2 3B
Berkeley Function Calling Leaderboard	—	21.9%
BALROG	—	10.1%

Reasoning GLM-4.5V leads

GLM-4.5V: 26.5 (#118), Llama 3.2 3B: 20.1 (#225)

Reasoning benchmarks
Benchmark	GLM-4.5V	Llama 3.2 3B
LMArena Hard Prompts	1335	1095
Kagi LLM Benchmark	59.8%	—

Math GLM-4.5V leads

GLM-4.5V: 34.7 (#157), Llama 3.2 3B: 29.9 (#213)

Math benchmarks
Benchmark	GLM-4.5V	Llama 3.2 3B
LMArena Math	1353	1126

Knowledge GLM-4.5V leads

GLM-4.5V: 36.8 (#155), Llama 3.2 3B: 29.1 (#232)

Knowledge benchmarks
Benchmark	GLM-4.5V	Llama 3.2 3B
LMArena Expert	1353	1090

Multimodal Not comparable

GLM-4.5V: 33.6 (#86), Llama 3.2 3B: —

Multimodal benchmarks
Benchmark	GLM-4.5V	Llama 3.2 3B
LMArena Vision	1154	—

Multilingual GLM-4.5V leads

GLM-4.5V: 44.9 (#172), Llama 3.2 3B: 26.4 (#276)

Multilingual benchmarks
Benchmark	GLM-4.5V	Llama 3.2 3B
LMArena Non-English	1304	1019
LMArena Chinese	1338	1017
LMArena Russian	1299	949
LMArena German	—	1056
LMArena Spanish	1335	—

Instruction Following GLM-4.5V leads

GLM-4.5V: 69.4 (#170), Llama 3.2 3B: 56.3 (#270)

Instruction Following benchmarks
Benchmark	GLM-4.5V	Llama 3.2 3B
LMArena Instruction Following	1311	1089

Long Context GLM-4.5V leads

GLM-4.5V: 39.6 (#166), Llama 3.2 3B: 33.4 (#256)

Long Context benchmarks
Benchmark	GLM-4.5V	Llama 3.2 3B
LMArena Longer Query	1305	1101

Writing & Preference GLM-4.5V leads

GLM-4.5V: 52.7 (#162), Llama 3.2 3B: 24.9 (#302)

Writing & Preference benchmarks
Benchmark	GLM-4.5V	Llama 3.2 3B
LMArena Text	1333	1110
LMArena Creative Writing	1295	1094
LMArena Multi-Turn	1333	1105
EQ-Bench Creative Writing	—	595

Frequently asked questions

Is GLM-4.5V better than Llama 3.2 3B?

Which is cheaper, GLM-4.5V or Llama 3.2 3B?

Llama 3.2 3B is cheaper. It lists at $0.05 per million input tokens and $0.33 per million output tokens; GLM-4.5V lists at $0.60 and $1.80.

Is GLM-4.5V or Llama 3.2 3B better for coding?

GLM-4.5V scores higher on coding benchmarks: 38.9 versus 27.1 in the Noometry coding category.

Which has the bigger context window?

Llama 3.2 3B does, with 131K tokens against 64K.

How many benchmarks do GLM-4.5V and Llama 3.2 3B share?

12 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and Llama 3.2 3B has 18.