Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

GLM-4.5V

Zhipu AI

GLM-4.5V is a multimodal language model developed by Zhipu AI. It supports a 197K token context window for handling large documents. The model is available through 2 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Zhipu AI's latest advancement in AI technology.

Llama 3.2 3B Instruct

Meta

Llama 3.2 3B Instruct is a language model developed by Meta. The model shows competitive results across 15 benchmarks. It excels particularly in NIH/Multi-needle (84.7%), ARC-C (78.6%), GSM8k (77.7%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. Released in 2024, it represents Meta's latest advancement in AI technology.

Llama 3.2 3B Instruct

Pricing Comparison

Cost per million tokens (USD)

GLM-4.5V

Input:$0.60

Output:$2.20

Llama 3.2 3B Instruct

$2.77 cheaper

Input:$0.01

Output:$0.02

Performance Metrics

Context window and performance specifications

GLM-4.5V

Max Context:196.6K

Parameters:108.0B

Llama 3.2 3B Instruct

Larger context

Max Context:256.0K

Parameters:3.2B

Average performance across 15 common benchmarks

GLM-4.5V

Average Score:0.0%

Llama 3.2 3B Instruct

+55.6%

Average Score:55.6%

Provider Availability & Performance

Available providers and their performance metrics

GLM-4.5V

2 providers

Novita

ZeroEval

Throughput: 85 tok/s

Latency: 0.7ms

Llama 3.2 3B Instruct

1 providers

DeepInfra

Throughput: 171.5 tok/s

Latency: 0.24ms

GLM-4.5V

Avg Score:0.0%

Providers:2

Llama 3.2 3B Instruct

+55.6%

Avg Score:55.6%

Providers:1