Model Comparison

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

OpenAI

GPT-5 nano

OpenAI

GPT-5 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 5 benchmarks. It excels particularly in AIME 2025 (85.2%), HMMT 2025 (75.6%), GPQA (71.2%). It supports a 528K token context window for handling large documents. The model is available through 2 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents OpenAI's latest advancement in AI technology.

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-3.5-mini-instruct

Microsoft

2024-08-23

OpenAI

GPT-5 nano

OpenAI

2025-08-07

11 months newer

Pricing Comparison

Cost per million tokens (USD)

OpenAI

GPT-5 nano

Input:$0.05
Output:$0.40
Microsoft

Phi-3.5-mini-instruct

$0.25 cheaper
Input:$0.10
Output:$0.10

Performance Metrics

Context window and performance specifications

OpenAI

GPT-5 nano

Larger context
Max Context:528.0K
Microsoft

Phi-3.5-mini-instruct

Max Context:256.0K
Parameters:3.8B

Average performance across 1 common benchmarks

OpenAI

GPT-5 nano

+40.8%
Average Score:71.2%
Microsoft

Phi-3.5-mini-instruct

Average Score:30.4%

Performance comparison across key benchmark categories

OpenAI

GPT-5 nano

math
9.6%
general
+4.8%
60.2%
Microsoft

Phi-3.5-mini-instruct

math
+51.3%
60.9%
general
55.4%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

GPT-5 nano

2024-05-30

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

OpenAI

GPT-5 nano

2 providers

ZeroEval

Throughput: 500 tok/s
Latency: 0.3ms

OpenAI

Throughput: 500 tok/s
Latency: 0.3ms
Microsoft

Phi-3.5-mini-instruct

1 providers

Azure

Throughput: 23 tok/s
Latency: 0.52ms
OpenAI

GPT-5 nano

+40.8%
Avg Score:71.2%
Providers:2
Microsoft

Phi-3.5-mini-instruct

Avg Score:30.4%
Providers:1