🚀 Website under development • Launching soon

Model Comparison

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

DeepSeek

DeepSeek-V3.1

DeepSeek

DeepSeek-V3.1 is a language model developed by DeepSeek. The model shows competitive results across 16 benchmarks. It excels particularly in SimpleQA (93.4%), MMLU-Redux (91.8%), MMLU-Pro (83.7%). The model shows particular specialization in factuality tasks with an average performance of 92.6%. It supports a 328K token context window for handling large documents. The model is available through 2 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents DeepSeek'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

DeepSeek

DeepSeek-V3.1

DeepSeek

2025-01-10

29 days newer

Pricing Comparison

Cost per million tokens (USD)

DeepSeek

DeepSeek-V3.1

Input:$0.27
Output:$1.00
Microsoft

Phi 4

$1.06 cheaper
Input:$0.07
Output:$0.14

Performance Metrics

Context window and performance specifications

DeepSeek

DeepSeek-V3.1

Larger context
Max Context:327.7K
Parameters:671.0B
Microsoft

Phi 4

Max Context:32.0K
Parameters:14.7B

Average performance across 2 common benchmarks

DeepSeek

DeepSeek-V3.1

+51.8%
Average Score:88.5%
Microsoft

Phi 4

Average Score:36.7%

Performance comparison across key benchmark categories

DeepSeek

DeepSeek-V3.1

factuality
+89.6%
92.6%
math
41.6%
code
56.5%
general
57.3%
Microsoft

Phi 4

factuality
3.0%
math
+38.9%
80.5%
code
+19.7%
76.1%
general
+9.3%
66.6%
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

DeepSeek

DeepSeek-V3.1

2 providers

DeepInfra

Novita

Microsoft

Phi 4

1 providers

DeepInfra

Throughput: 33 tok/s
Latency: 0.2ms
DeepSeek

DeepSeek-V3.1

+51.8%
Avg Score:88.5%
Providers:2
Microsoft

Phi 4

Avg Score:36.7%
Providers:1