Comprehensive side-by-side LLM comparison
Phi-4-multimodal-instruct leads with 38.4% higher average benchmark score. Phi-4-multimodal-instruct offers 120.0K more tokens in context window than Grok-3 Mini. Phi-4-multimodal-instruct is $0.65 cheaper per million tokens. Overall, Phi-4-multimodal-instruct is the stronger choice for coding tasks.
xAI
Grok-3 Mini is a multimodal language model developed by xAI. This model demonstrates exceptional performance with an average score of 87.8% across 4 benchmarks. It excels particularly in AIME 2024 (95.8%), AIME 2025 (90.8%), GPQA (84.0%). It supports a 136K token context window for handling large documents. 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 xAI's latest advancement in AI technology.
Microsoft
Phi-4-multimodal-instruct is a multimodal language model developed by Microsoft. It achieves strong performance with an average score of 72.0% across 15 benchmarks. It excels particularly in ScienceQA Visual (97.5%), DocVQA (93.2%), MMBench (86.7%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Microsoft's latest advancement in AI technology.
16 days newer
Phi-4-multimodal-instruct
Microsoft
2025-02-01
Grok-3 Mini
xAI
2025-02-17
Cost per million tokens (USD)
Grok-3 Mini
Phi-4-multimodal-instruct
Context window and performance specifications
Average performance across 19 common benchmarks
Grok-3 Mini
Phi-4-multimodal-instruct
Phi-4-multimodal-instruct
2024-06-01
Grok-3 Mini
2024-11-17
Available providers and their performance metrics
Grok-3 Mini
xAI
Phi-4-multimodal-instruct
Grok-3 Mini
Phi-4-multimodal-instruct
Grok-3 Mini
Phi-4-multimodal-instruct
DeepInfra