Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

Microsoft

Phi-3.5-mini-instruct

Microsoft

Phi-3.5-mini-instruct is a language model developed by Microsoft. The model shows competitive results across 31 benchmarks. It excels particularly in GSM8k (86.2%), ARC-C (84.6%), RULER (84.1%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Microsoft's latest advancement in AI technology.

Microsoft

Phi-4-multimodal-instruct

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%). The model shows particular specialization in general tasks with an average performance of 75.8%. 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.

Microsoft

Phi-3.5-mini-instruct

Microsoft

2024-08-23

Microsoft

Phi-4-multimodal-instruct

Microsoft

2025-02-01

5 months newer

Pricing Comparison

Cost per million tokens (USD)

Microsoft

Phi-3.5-mini-instruct

Input:$0.10
Output:$0.10
Microsoft

Phi-4-multimodal-instruct

$0.05 cheaper
Input:$0.05
Output:$0.10

Performance Metrics

Context window and performance specifications

Microsoft

Phi-3.5-mini-instruct

Max Context:256.0K
Parameters:3.8B
Microsoft

Phi-4-multimodal-instruct

Max Context:256.0K
Parameters:5.6B

Performance comparison across key benchmark categories

Microsoft

Phi-3.5-mini-instruct

general
55.4%
math
60.9%
Microsoft

Phi-4-multimodal-instruct

general
+20.4%
75.8%
math
+1.5%
62.4%
Knowledge Cutoff
Training data recency comparison

Phi-4-multimodal-instruct

2024-06-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Microsoft

Phi-3.5-mini-instruct

1 providers

Azure

Throughput: 23 tok/s
Latency: 0.52ms
Microsoft

Phi-4-multimodal-instruct

1 providers

DeepInfra

Throughput: 25 tok/s
Latency: 0.5ms
Microsoft

Phi-3.5-mini-instruct

Avg Score:0.0%
Providers:1
Microsoft

Phi-4-multimodal-instruct

Avg Score:0.0%
Providers:1