Comprehensive side-by-side LLM comparison
Phi-4-multimodal-instruct leads with 22.2% higher average benchmark score. Claude 3.5 Haiku offers 144.0K more tokens in context window than Phi-4-multimodal-instruct. Phi-4-multimodal-instruct is $4.65 cheaper per million tokens. Phi-4-multimodal-instruct supports multimodal inputs. Claude 3.5 Haiku is available on 3 providers. Overall, Phi-4-multimodal-instruct is the stronger choice for coding tasks.
Anthropic
Claude 3.5 Haiku is a language model developed by Anthropic. It achieves strong performance with an average score of 60.8% across 9 benchmarks. It excels particularly in HumanEval (88.1%), MGSM (85.6%), DROP (83.1%). It supports a 400K token context window for handling large documents. The model is available through 3 API providers. Released in 2024, it represents Anthropic'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.
3 months newer
Claude 3.5 Haiku
Anthropic
2024-10-22
Phi-4-multimodal-instruct
Microsoft
2025-02-01
Cost per million tokens (USD)
Claude 3.5 Haiku
Phi-4-multimodal-instruct
Context window and performance specifications
Average performance across 24 common benchmarks
Claude 3.5 Haiku
Phi-4-multimodal-instruct
Phi-4-multimodal-instruct
2024-06-01
Available providers and their performance metrics
Claude 3.5 Haiku
Anthropic
Bedrock
Claude 3.5 Haiku
Phi-4-multimodal-instruct
Claude 3.5 Haiku
Phi-4-multimodal-instruct
Phi-4-multimodal-instruct
DeepInfra