Model Comparison

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

GLM-4.5

Zhipu AI

GLM-4.5 is a language model developed by Zhipu AI. It achieves strong performance with an average score of 64.0% across 14 benchmarks. It excels particularly in MATH-500 (98.2%), AIME 2024 (91.0%), MMLU-Pro (84.6%). It supports a 262K token context window for handling large documents. The model is available through 1 API provider. 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.

Qwen2.5-Coder 32B Instruct

Alibaba Cloud / Qwen Team

Qwen2.5-Coder 32B Instruct is a language model developed by Alibaba Cloud / Qwen Team. It achieves strong performance with an average score of 64.9% across 15 benchmarks. It excels particularly in HumanEval (92.7%), GSM8k (91.1%), MBPP (90.2%). The model shows particular specialization in reasoning tasks with an average performance of 78.1%. It supports a 256K token context window for handling large documents. The model is available through 4 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Alibaba Cloud / Qwen Team's latest advancement in AI technology.

Qwen2.5-Coder 32B Instruct

Alibaba Cloud / Qwen Team

2024-09-19

GLM-4.5

Zhipu AI

2025-07-28

10 months newer

Pricing Comparison

Cost per million tokens (USD)

GLM-4.5

Input:$0.40

Output:$1.60

Qwen2.5-Coder 32B Instruct

$1.82 cheaper

Input:$0.09

Output:$0.09

Performance Metrics

Context window and performance specifications

GLM-4.5

Larger context

Max Context:262.1K

Parameters:355.0B

Qwen2.5-Coder 32B Instruct

Max Context:256.0K

Parameters:32.0B

Average performance across 2 common benchmarks

GLM-4.5

+37.8%

Average Score:78.8%

Qwen2.5-Coder 32B Instruct

Average Score:40.9%

Performance comparison across key benchmark categories

GLM-4.5

math

+24.0%

98.2%

general

+23.1%

79.3%

reasoning

41.1%

code

50.7%

Qwen2.5-Coder 32B Instruct

math

74.2%

general

56.2%

reasoning

+37.1%

78.1%

code

+7.5%

58.2%

Benchmark Scores - Detailed View

Side-by-side comparison of all benchmark scores

Provider Availability & Performance

Available providers and their performance metrics

GLM-4.5

1 providers

DeepInfra

Qwen2.5-Coder 32B Instruct

4 providers

Hyperbolic

Throughput: 100 tok/s

Latency: 0.5ms

DeepInfra

Throughput: 44 tok/s

Latency: 0.5ms

Fireworks

Throughput: 110 tok/s

Latency: 0.26ms

Lambda

Throughput: 42 tok/s

Latency: 0.5ms

GLM-4.5

+37.8%

Avg Score:78.8%

Providers:1

Qwen2.5-Coder 32B Instruct

Avg Score:40.9%

Providers:4