Model Comparison

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

Mistral AI

Mistral Small 3.1 24B Base

Mistral AI

Mistral Small 3.1 24B Base is a multimodal language model developed by Mistral AI. It achieves strong performance with an average score of 62.9% across 5 benchmarks. It excels particularly in MMLU (81.0%), TriviaQA (80.5%), MMMU (59.3%). 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 Mistral AI's latest advancement in AI technology.

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 4

Microsoft

2024-12-12

Mistral AI

Mistral Small 3.1 24B Base

Mistral AI

2025-03-17

3 months newer

Pricing Comparison

Cost per million tokens (USD)

Mistral AI

Mistral Small 3.1 24B Base

Input:$0.10
Output:$0.30
Microsoft

Phi 4

$0.19 cheaper
Input:$0.07
Output:$0.14

Performance Metrics

Context window and performance specifications

Mistral AI

Mistral Small 3.1 24B Base

Larger context
Max Context:256.0K
Parameters:24.0B
Microsoft

Phi 4

Max Context:32.0K
Parameters:14.7B

Average performance across 3 common benchmarks

Mistral AI

Mistral Small 3.1 24B Base

Average Score:58.2%
Microsoft

Phi 4

+12.3%
Average Score:70.4%

Performance comparison across key benchmark categories

Mistral AI

Mistral Small 3.1 24B Base

general
+3.6%
63.8%
Microsoft

Phi 4

general
60.2%
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

Mistral AI

Mistral Small 3.1 24B Base

1 providers

Mistral AI

Throughput: 137.1 tok/s
Latency: 0.23ms
Microsoft

Phi 4

1 providers

DeepInfra

Throughput: 33 tok/s
Latency: 0.2ms
Mistral AI

Mistral Small 3.1 24B Base

Avg Score:58.2%
Providers:1
Microsoft

Phi 4

+12.3%
Avg Score:70.4%
Providers:1