Model Comparison

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

OpenAI

GPT-4

OpenAI

GPT-4 is a multimodal language model developed by OpenAI. It achieves strong performance with an average score of 77.7% across 12 benchmarks. It excels particularly in AI2 Reasoning Challenge (ARC) (96.3%), HellaSwag (95.3%), Uniform Bar Exam (90.0%). The model shows particular specialization in reasoning tasks with an average performance of 93.0%. The model is available through 2 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly.

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.

OpenAI

GPT-4

OpenAI

2023-06-13

Microsoft

Phi-3.5-mini-instruct

Microsoft

2024-08-23

1 year newer

Pricing Comparison

Cost per million tokens (USD)

OpenAI

GPT-4

Input:$30.00
Output:$60.00
Microsoft

Phi-3.5-mini-instruct

$89.80 cheaper
Input:$0.10
Output:$0.10

Performance Metrics

Context window and performance specifications

OpenAI

GPT-4

Max Context:65.5K
Microsoft

Phi-3.5-mini-instruct

Larger context
Max Context:256.0K
Parameters:3.8B

Average performance across 7 common benchmarks

OpenAI

GPT-4

+13.1%
Average Score:69.8%
Microsoft

Phi-3.5-mini-instruct

Average Score:56.6%

Performance comparison across key benchmark categories

OpenAI

GPT-4

reasoning
+18.9%
93.0%
general
+20.8%
76.2%
math
+7.6%
68.5%
code
+0.8%
67.0%
Microsoft

Phi-3.5-mini-instruct

reasoning
74.2%
general
55.4%
math
60.9%
code
66.2%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

GPT-4

2022-12-31

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

OpenAI

GPT-4

2 providers

Azure

Throughput: 104 tok/s
Latency: 0.3ms

OpenAI

Throughput: 100 tok/s
Latency: 0.5ms
Microsoft

Phi-3.5-mini-instruct

1 providers

Azure

Throughput: 23 tok/s
Latency: 0.52ms
OpenAI

GPT-4

+13.1%
Avg Score:69.8%
Providers:2
Microsoft

Phi-3.5-mini-instruct

Avg Score:56.6%
Providers:1