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  4. /Phi-4
Microsoft Phi-4

AI Language Model

AI Language ModelsMicrosoft2024

Microsoft Phi-4

Last updated: April 18, 2026

8.2

VersusMatrix

out of 10

Try or Access API

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API Access

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Detalhamento da Pontuação

Cost EfficiencyCost EfficiencyBenchmark (MMLU)Benchmark (MMLU)Arena ELOArena ELOContext WindowContext WindowSpeed (tok/s)Speed (tok/s)Coding (HumanEval)Coding (HumanEval)
Top 10% Cost Efficiency
Cost Efficiency
9.9
Benchmark (MMLU)
8.3
Arena ELO
7.8

Microsoft Phi-4 — Full Specifications

Input Price
$0.07/1M tokens
Output Price
$0.26/1M tokens

See a missing or incorrect spec? Let us know

About the Microsoft Phi-4

Microsoft's compact 14B model with outstanding math and reasoning performance. Punches well above its weight class for STEM applications.

Reviewed by VersusMatrix Editorial Team

Last updated: April 18, 2026

Editorial guidelines

Methodology: AI-powered analysis of technical specifications from manufacturer data. Scores are calculated by comparing products across multiple dimensions and normalized relative to the full category database. Our editorial process is independent and not influenced by affiliate partnerships.

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FAQ

Is the Microsoft Phi-4 worth buying in 2026?

Microsoft's compact 14B model with outstanding math and reasoning performance. Punches well above its weight class for STEM applications.

🏆 Featured in Rankings

  • Best Budget AI Models 2025 (Low Cost per Token)#3
  • Best Open Source LLMs 2025#6

Comparações Relacionadas

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Anthropic Claude 3.7 Sonnet

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Pontuação

8.2

out of 10

$ Cost Efficiency
20%9.9
Benchmark (MMLU)
30%8.3
Arena ELO
20%7.8

How We Score

Scores are calculated by comparing all ai language models in our database. Each dimension is weighted and normalized relative to the category.

$ Cost Efficiency20%

Based on input_price_per_1m_usd · lower is better

Benchmark (MMLU)30%

Based on mmlu

Arena ELO20%

Based on arena_elo

Context Window10%

Based on context_window_k

Speed (tok/s)10%

Based on speed_tokens_per_sec

Coding (HumanEval)10%

Based on humaneval

Products missing data for a dimension receive the median score. Overall = weighted sum of all dimensions.

Comparar com

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