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Model Comparison

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

Google

Gemini 2.0 Flash-Lite

Google

Gemini 2.0 Flash-Lite is a multimodal language model developed by Google. The model shows competitive results across 13 benchmarks. It excels particularly in MATH (86.8%), FACTS Grounding (83.6%), Global-MMLU-Lite (78.2%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Google's latest advancement in AI technology.

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.

Google

Gemini 2.0 Flash-Lite

Google

2025-02-05

GLM-4.5

Zhipu AI

2025-07-28

5 months newer

Pricing Comparison

Cost per million tokens (USD)

Google

Gemini 2.0 Flash-Lite

$1.63 cheaper
Input:$0.07
Output:$0.30

GLM-4.5

Input:$0.40
Output:$1.60

Performance Metrics

Context window and performance specifications

Google

Gemini 2.0 Flash-Lite

Larger context
Max Context:1.1M

GLM-4.5

Max Context:262.1K
Parameters:355.0B

Average performance across 2 common benchmarks

Google

Gemini 2.0 Flash-Lite

Average Score:61.5%

GLM-4.5

+20.3%
Average Score:81.8%

Performance comparison across key benchmark categories

Google

Gemini 2.0 Flash-Lite

math
71.0%
general
60.3%
code
28.9%

GLM-4.5

math
+27.2%
98.2%
general
+19.0%
79.3%
code
+21.8%
50.7%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Gemini 2.0 Flash-Lite

2024-06-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Google

Gemini 2.0 Flash-Lite

1 providers

Google

Throughput: 85 tok/s
Latency: 0.7ms

GLM-4.5

1 providers

DeepInfra

Google

Gemini 2.0 Flash-Lite

Avg Score:61.5%
Providers:1

GLM-4.5

+20.3%
Avg Score:81.8%
Providers:1