Comprehensive side-by-side LLM comparison
Phi-3.5-mini-instruct leads with 19.1% higher average benchmark score. DeepSeek-R1-0528 offers 6.1K more tokens in context window than Phi-3.5-mini-instruct. Phi-3.5-mini-instruct is $2.45 cheaper per million tokens. DeepSeek-R1-0528 is available on 3 providers. Overall, Phi-3.5-mini-instruct is the stronger choice for coding tasks.
DeepSeek
DeepSeek-R1-0528 is a language model developed by DeepSeek. It achieves strong performance with an average score of 60.1% across 16 benchmarks. It excels particularly in MMLU-Redux (93.4%), SimpleQA (92.3%), AIME 2024 (91.4%). 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 DeepSeek'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.
9 months newer
Phi-3.5-mini-instruct
Microsoft
2024-08-23
DeepSeek-R1-0528
DeepSeek
2025-05-28
Cost per million tokens (USD)
DeepSeek-R1-0528
Phi-3.5-mini-instruct
Context window and performance specifications
Average performance across 45 common benchmarks
DeepSeek-R1-0528
Phi-3.5-mini-instruct
Available providers and their performance metrics
DeepSeek-R1-0528
DeepInfra
DeepSeek
Novita
DeepSeek-R1-0528
Phi-3.5-mini-instruct
DeepSeek-R1-0528
Phi-3.5-mini-instruct
Phi-3.5-mini-instruct
Azure