🚀 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-multimodal-instruct

Microsoft

Phi-4-multimodal-instruct is a multimodal language model developed by Microsoft. It achieves strong performance with an average score of 72.0% across 15 benchmarks. It excels particularly in ScienceQA Visual (97.5%), DocVQA (93.2%), MMBench (86.7%). The model shows particular specialization in general tasks with an average performance of 75.8%. 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 Microsoft's latest advancement in AI technology.

DeepSeek

DeepSeek-V3.1

DeepSeek

2025-01-10

Microsoft

Phi-4-multimodal-instruct

Microsoft

2025-02-01

22 days newer

Pricing Comparison

Cost per million tokens (USD)

DeepSeek

DeepSeek-V3.1

Input:$0.27
Output:$1.00
Microsoft

Phi-4-multimodal-instruct

$1.12 cheaper
Input:$0.05
Output:$0.10

Performance Metrics

Context window and performance specifications

DeepSeek

DeepSeek-V3.1

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

Phi-4-multimodal-instruct

Max Context:256.0K
Parameters:5.6B

Performance comparison across key benchmark categories

DeepSeek

DeepSeek-V3.1

general
57.3%
math
41.6%
Microsoft

Phi-4-multimodal-instruct

general
+18.5%
75.8%
math
+20.8%
62.4%
Knowledge Cutoff
Training data recency comparison

Phi-4-multimodal-instruct

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-multimodal-instruct

1 providers

DeepInfra

Throughput: 25 tok/s
Latency: 0.5ms
DeepSeek

DeepSeek-V3.1

Avg Score:0.0%
Providers:2
Microsoft

Phi-4-multimodal-instruct

Avg Score:0.0%
Providers:1