Comprehensive side-by-side LLM comparison
Phi-4-multimodal-instruct leads with 63.7% higher average benchmark score. Phi-4-multimodal-instruct is $2.25 cheaper per million tokens. Phi-4-multimodal-instruct supports multimodal inputs. Overall, Phi-4-multimodal-instruct is the stronger choice for coding tasks.
Mistral AI
Devstral Medium is a language model developed by Mistral AI. It achieves strong performance with an average score of 61.6% across 1 benchmarks. Notable strengths include SWE-Bench Verified (61.6%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. Released in 2025, it represents Mistral AI'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
Phi-4-multimodal-instruct
Microsoft
2025-02-01
Devstral Medium
Mistral AI
2025-07-10
Cost per million tokens (USD)
Devstral Medium
Phi-4-multimodal-instruct
Context window and performance specifications
Average performance across 16 common benchmarks
Devstral Medium
Phi-4-multimodal-instruct
Phi-4-multimodal-instruct
2024-06-01
Available providers and their performance metrics
Devstral Medium
Mistral AI
Phi-4-multimodal-instruct
Devstral Medium
Phi-4-multimodal-instruct
Devstral Medium
Phi-4-multimodal-instruct
DeepInfra