Model Comparison

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

OpenAI

GPT-3.5 Turbo

OpenAI

GPT-3.5 Turbo is a language model developed by OpenAI. The model shows competitive results across 8 benchmarks. Notable strengths include DROP (70.2%), MMLU (69.8%), HumanEval (68.0%). The model is available through 2 API providers.

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.

OpenAI

GPT-3.5 Turbo

OpenAI

2023-03-21

Microsoft

Phi-4-multimodal-instruct

Microsoft

2025-02-01

1 year newer

Pricing Comparison

Cost per million tokens (USD)

OpenAI

GPT-3.5 Turbo

Input:$0.50
Output:$1.50
Microsoft

Phi-4-multimodal-instruct

$1.85 cheaper
Input:$0.05
Output:$0.10

Performance Metrics

Context window and performance specifications

OpenAI

GPT-3.5 Turbo

Max Context:20.5K
Microsoft

Phi-4-multimodal-instruct

Larger context
Max Context:256.0K
Parameters:5.6B

Average performance across 2 common benchmarks

OpenAI

GPT-3.5 Turbo

Average Score:0.0%
Microsoft

Phi-4-multimodal-instruct

+58.8%
Average Score:58.8%

Performance comparison across key benchmark categories

OpenAI

GPT-3.5 Turbo

general
56.9%
math
33.1%
Microsoft

Phi-4-multimodal-instruct

general
+18.8%
75.8%
math
+29.3%
62.4%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

GPT-3.5 Turbo

2021-09-30

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

OpenAI

GPT-3.5 Turbo

2 providers

Azure

Throughput: 90 tok/s
Latency: 0.8ms

OpenAI

Throughput: 100 tok/s
Latency: 0.5ms
Microsoft

Phi-4-multimodal-instruct

1 providers

DeepInfra

Throughput: 25 tok/s
Latency: 0.5ms
OpenAI

GPT-3.5 Turbo

Avg Score:0.0%
Providers:2
Microsoft

Phi-4-multimodal-instruct

+58.8%
Avg Score:58.8%
Providers:1