Comprehensive side-by-side LLM comparison
Phi-4-multimodal-instruct leads with 30.1% higher average benchmark score. Phi-4-multimodal-instruct is $1.10 cheaper per million tokens. Phi-4-multimodal-instruct supports multimodal inputs. Overall, Phi-4-multimodal-instruct is the stronger choice for coding tasks.
Cohere
Command R+ is a language model developed by Cohere. It achieves strong performance with an average score of 74.6% across 6 benchmarks. It excels particularly in HellaSwag (88.6%), Winogrande (85.4%), MMLU (75.7%). It supports a 256K token context window for handling large documents. The model is available through 2 API providers. Released in 2024, it represents Cohere'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.
5 months newer
Command R+
Cohere
2024-08-30
Phi-4-multimodal-instruct
Microsoft
2025-02-01
Cost per million tokens (USD)
Command R+
Phi-4-multimodal-instruct
Context window and performance specifications
Average performance across 21 common benchmarks
Command R+
Phi-4-multimodal-instruct
Phi-4-multimodal-instruct
2024-06-01
Available providers and their performance metrics
Command R+
Bedrock
Cohere
Command R+
Phi-4-multimodal-instruct
Command R+
Phi-4-multimodal-instruct
Phi-4-multimodal-instruct
DeepInfra