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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-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

DeepSeek

DeepSeek-V3.1

DeepSeek

2025-01-10

4 months newer

Pricing Comparison

Cost per million tokens (USD)

DeepSeek

DeepSeek-V3.1

Input:$0.27
Output:$1.00
Microsoft

Phi-3.5-mini-instruct

$1.07 cheaper
Input:$0.10
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-3.5-mini-instruct

Max Context:256.0K
Parameters:3.8B

Average performance across 1 common benchmarks

DeepSeek

DeepSeek-V3.1

+36.3%
Average Score:83.7%
Microsoft

Phi-3.5-mini-instruct

Average Score:47.4%

Performance comparison across key benchmark categories

DeepSeek

DeepSeek-V3.1

factuality
+28.6%
92.6%
reasoning
+0.7%
74.9%
code
56.5%
math
41.6%
general
+1.9%
57.3%
Microsoft

Phi-3.5-mini-instruct

factuality
64.0%
reasoning
74.2%
code
+9.7%
66.2%
math
+19.2%
60.9%
general
55.4%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores

Provider Availability & Performance

Available providers and their performance metrics

DeepSeek

DeepSeek-V3.1

2 providers

DeepInfra

Novita

Microsoft

Phi-3.5-mini-instruct

1 providers

Azure

Throughput: 23 tok/s
Latency: 0.52ms
DeepSeek

DeepSeek-V3.1

+36.3%
Avg Score:83.7%
Providers:2
Microsoft

Phi-3.5-mini-instruct

Avg Score:47.4%
Providers:1