Comprehensive side-by-side LLM comparison
Phi-4-multimodal-instruct leads with 32.1% higher average benchmark score. Phi-4-multimodal-instruct is $7.85 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
Mistral Large 2 is a language model developed by Mistral AI. This model demonstrates exceptional performance with an average score of 87.6% across 5 benchmarks. It excels particularly in GSM8k (93.0%), HumanEval (92.0%), MT-Bench (86.3%). It supports a 256K token context window for handling large documents. The model is available through 2 API providers. Released in 2024, 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.
6 months newer
Mistral Large 2
Mistral AI
2024-07-24
Phi-4-multimodal-instruct
Microsoft
2025-02-01
Cost per million tokens (USD)
Mistral Large 2
Phi-4-multimodal-instruct
Context window and performance specifications
Average performance across 20 common benchmarks
Mistral Large 2
Phi-4-multimodal-instruct
Phi-4-multimodal-instruct
2024-06-01
Available providers and their performance metrics
Mistral Large 2
Mistral AI
Mistral Large 2
Phi-4-multimodal-instruct
Mistral Large 2
Phi-4-multimodal-instruct
Phi-4-multimodal-instruct
DeepInfra