Comprehensive side-by-side LLM comparison
Phi-4-multimodal-instruct leads with 8.2% higher average benchmark score. Both models have similar pricing. Phi-4-multimodal-instruct supports multimodal inputs. Overall, Phi-4-multimodal-instruct is the stronger choice for coding tasks.
Meta
Llama 3.2 3B Instruct is a language model developed by Meta. The model shows competitive results across 15 benchmarks. It excels particularly in NIH/Multi-needle (84.7%), ARC-C (78.6%), GSM8k (77.7%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. Released in 2024, it represents Meta'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.
4 months newer
Llama 3.2 3B Instruct
Meta
2024-09-25
Phi-4-multimodal-instruct
Microsoft
2025-02-01
Cost per million tokens (USD)
Llama 3.2 3B Instruct
Phi-4-multimodal-instruct
Context window and performance specifications
Average performance across 30 common benchmarks
Llama 3.2 3B Instruct
Phi-4-multimodal-instruct
Phi-4-multimodal-instruct
2024-06-01
Available providers and their performance metrics
Llama 3.2 3B Instruct
DeepInfra
Phi-4-multimodal-instruct
Llama 3.2 3B Instruct
Phi-4-multimodal-instruct
Llama 3.2 3B Instruct
Phi-4-multimodal-instruct
DeepInfra