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.

Mistral AI

Pixtral-12B

Mistral AI

Pixtral-12B is a multimodal language model developed by Mistral AI. It achieves strong performance with an average score of 66.8% across 12 benchmarks. It excels particularly in DocVQA (90.7%), ChartQA (81.8%), VQAv2 (78.6%). The model shows particular specialization in general tasks with an average performance of 75.5%. It supports a 136K 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 2024, it represents Mistral AI's latest advancement in AI technology.

Mistral AI

Pixtral-12B

Mistral AI

2024-09-17

Microsoft

Phi 4

Microsoft

2024-12-12

2 months newer

Pricing Comparison

Cost per million tokens (USD)

Microsoft

Phi 4

$0.09 cheaper
Input:$0.07
Output:$0.14
Mistral AI

Pixtral-12B

Input:$0.15
Output:$0.15

Performance Metrics

Context window and performance specifications

Microsoft

Phi 4

Max Context:32.0K
Parameters:14.7B
Mistral AI

Pixtral-12B

Larger context
Max Context:136.2K
Parameters:12.4B

Average performance across 4 common benchmarks

Microsoft

Phi 4

+15.0%
Average Score:77.7%
Mistral AI

Pixtral-12B

Average Score:62.7%

Performance comparison across key benchmark categories

Microsoft

Phi 4

math
+27.5%
80.5%
code
+14.1%
76.1%
general
60.2%
roleplay
47.6%
Mistral AI

Pixtral-12B

math
53.0%
code
62.0%
general
+15.3%
75.5%
roleplay
+21.1%
68.7%
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
Mistral AI

Pixtral-12B

1 providers

Mistral AI

Throughput: 0.1 tok/s
Latency: 0.5ms
Microsoft

Phi 4

+15.0%
Avg Score:77.7%
Providers:1
Mistral AI

Pixtral-12B

Avg Score:62.7%
Providers:1