Comprehensive side-by-side LLM comparison
Phi-3.5-mini-instruct leads with 21.5% higher average benchmark score. GLM-4.5 offers 6.1K more tokens in context window than Phi-3.5-mini-instruct. Phi-3.5-mini-instruct is $1.80 cheaper per million tokens. GLM-4.5 is available on 3 providers. Overall, Phi-3.5-mini-instruct is the stronger choice for coding tasks.
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.
Microsoft
Phi-3.5-mini-instruct is a language model developed by Microsoft. The model shows competitive results across 31 benchmarks. It excels particularly in GSM8k (86.2%), ARC-C (84.6%), RULER (84.1%). It supports a 256K 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 2024, it represents Microsoft's latest advancement in AI technology.
11 months newer
Phi-3.5-mini-instruct
Microsoft
2024-08-23
GLM-4.5
Zhipu AI
2025-07-28
Cost per million tokens (USD)
GLM-4.5
Phi-3.5-mini-instruct
Context window and performance specifications
Average performance across 43 common benchmarks
GLM-4.5
Phi-3.5-mini-instruct
Available providers and their performance metrics
GLM-4.5
DeepInfra
Novita
ZeroEval
Phi-3.5-mini-instruct
GLM-4.5
Phi-3.5-mini-instruct
GLM-4.5
Phi-3.5-mini-instruct
Azure