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Phi-3 MediumvsPhi-4

Microsoft vs Microsoft — Side-by-side model comparison

Phi-4 leads 3/5 categories

Head-to-Head Comparison

MetricPhi-3 MediumPhi-4
Provider
Arena Rank
#28
Context Window
128K
16K
Input Pricing
Free (open)/1M tokens
Free/1M tokens
Output Pricing
Free (open)/1M tokens
Free/1M tokens
Parameters
14B
14B
Open Source
Yes
Yes
Best For
Balanced performance, reasoning, coding
Small model research, edge deployment, reasoning
Release Date
May 21, 2024
Dec 12, 2024

Phi-3 Medium

Phi-3 Medium is Microsoft's 14 billion parameter model in the Phi-3 family, offering a step up in capability from Phi-3 Mini while remaining efficient enough for deployment on consumer hardware. It demonstrates that careful data curation and training methodology can produce models that compete with much larger alternatives, particularly on reasoning and STEM-related tasks.

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Phi-4

Phi-4 is Microsoft's small language model that demonstrates remarkable capability relative to its size, embodying the 'small but mighty' approach to AI. Through innovative training on high-quality synthetic and curated data, Phi-4 achieves performance comparable to much larger models on reasoning, coding, and STEM tasks. As an open-source model, it's ideal for on-device deployment, edge computing, and applications requiring local AI processing without cloud connectivity. Phi-4 has been influential in proving that model quality depends more on data quality and training methodology than raw parameter count.

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Key Differences: Phi-3 Medium vs Phi-4

1

Phi-3 Medium supports a larger context window (128K), allowing it to process longer documents in a single request.

2

Phi-3 Medium has 14B parameters vs Phi-4's 14B, which affects inference speed and capability.

P

When to use Phi-3 Medium

  • +You need to process long documents (128K context)
  • +Your use case involves balanced performance, reasoning, coding
View full Phi-3 Medium specs →
P

When to use Phi-4

  • +Your use case involves small model research, edge deployment, reasoning
View full Phi-4 specs →

The Verdict

Phi-4 wins our head-to-head comparison with 3 out of 5 category wins. It's the stronger choice for small model research, edge deployment, reasoning, though Phi-3 Medium holds an edge in balanced performance, reasoning, coding.

Last compared: March 2026 · Data sourced from public benchmarks and official pricing pages

Frequently Asked Questions

Which is better, Phi-3 Medium or Phi-4?
In our head-to-head comparison, Phi-4 leads in 3 out of 5 categories (arena rank, context window, input pricing, output pricing, and parameters). Phi-4 excels at small model research, edge deployment, reasoning, while Phi-3 Medium is better suited for balanced performance, reasoning, coding. The best choice depends on your specific requirements, budget, and use case.
How does Phi-3 Medium pricing compare to Phi-4?
Phi-3 Medium charges Free (open) per 1M input tokens and Free (open) per 1M output tokens. Phi-4 charges Free per 1M input tokens and Free per 1M output tokens. For high-volume production workloads, the pricing difference can significantly impact total cost of ownership.
What is the context window difference between Phi-3 Medium and Phi-4?
Phi-3 Medium supports a 128K token context window, while Phi-4 supports 16K tokens. Phi-3 Medium can process longer documents, codebases, and conversations in a single request. Context window size matters most for tasks involving long documents, large codebases, or extended conversations.
Can I use Phi-3 Medium or Phi-4 for free?
Phi-3 Medium is a paid API model starting at Free (open) per 1M input tokens. Phi-4 is available for free (open-source). Open-source models can be self-hosted for free but require your own GPU infrastructure.
Which model has better benchmarks, Phi-3 Medium or Phi-4?
Phi-3 Medium's arena rank is not yet available, while Phi-4 holds rank #28. Note that benchmarks don't capture every use case — we recommend testing both models on your specific tasks.
Is Phi-3 Medium or Phi-4 better for coding?
Phi-3 Medium is specifically optimized for coding tasks. Phi-4's primary strength is small model research, edge deployment, reasoning. For coding specifically, arena rank and code-specific benchmarks are the best indicators of performance.