Model Comparison

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

Microsoft

Phi 4

Microsoft

Phi 4 is a language model developed by Microsoft. It achieves strong performance with an average score of 66.0% across 13 benchmarks. It excels particularly in MMLU (84.8%), HumanEval+ (82.8%), HumanEval (82.6%). The model shows particular specialization in math tasks with an average performance of 80.5%. 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

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

Microsoft

Phi 4

Microsoft

2024-12-12

3 months newer

Pricing Comparison

Cost per million tokens (USD)

Microsoft

Phi 4

Input:$0.07
Output:$0.14
Microsoft

Phi-3.5-mini-instruct

$0.01 cheaper
Input:$0.10
Output:$0.10

Performance Metrics

Context window and performance specifications

Microsoft

Phi 4

Max Context:32.0K
Parameters:14.7B
Microsoft

Phi-3.5-mini-instruct

Larger context
Max Context:256.0K
Parameters:3.8B

Average performance across 7 common benchmarks

Microsoft

Phi 4

+26.8%
Average Score:75.8%
Microsoft

Phi-3.5-mini-instruct

Average Score:49.0%

Performance comparison across key benchmark categories

Microsoft

Phi 4

math
+19.6%
80.5%
code
+9.9%
76.1%
general
+4.8%
60.2%
Microsoft

Phi-3.5-mini-instruct

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

Phi 4

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 4

1 providers

DeepInfra

Throughput: 33 tok/s
Latency: 0.2ms
Microsoft

Phi-3.5-mini-instruct

1 providers

Azure

Throughput: 23 tok/s
Latency: 0.52ms
Microsoft

Phi 4

+26.8%
Avg Score:75.8%
Providers:1
Microsoft

Phi-3.5-mini-instruct

Avg Score:49.0%
Providers:1