Comprehensive side-by-side LLM comparison
GLM-4.5 leads with 3.8% higher average benchmark score. Llama 4 Scout offers 19.7M more tokens in context window than GLM-4.5. Llama 4 Scout is $1.62 cheaper per million tokens. Llama 4 Scout supports multimodal inputs. Llama 4 Scout is available on 6 providers. Both models have their strengths depending on your specific coding needs.
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 3 API providers. 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.
Meta
Llama 4 Scout is a multimodal language model developed by Meta. It achieves strong performance with an average score of 67.3% across 12 benchmarks. It excels particularly in DocVQA (94.4%), MGSM (90.6%), ChartQA (88.8%). With a 20.0M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 6 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Meta's latest advancement in AI technology.
3 months newer
Llama 4 Scout
Meta
2025-04-05
GLM-4.5
Zhipu AI
2025-07-28
Cost per million tokens (USD)
GLM-4.5
Llama 4 Scout
Context window and performance specifications
Average performance across 23 common benchmarks
GLM-4.5
Llama 4 Scout
Available providers and their performance metrics
GLM-4.5
DeepInfra
Novita
ZeroEval
Llama 4 Scout
GLM-4.5
Llama 4 Scout
GLM-4.5
Llama 4 Scout
DeepInfra
Fireworks
Groq
Lambda
Novita
Together