Model Comparison

DeepSeek-V3.2 (Thinking) vs Phi 4 Mini

DeepSeek-V3.2 (Thinking) significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DeepSeek-V3.2 (Thinking) outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Phi 4 Mini is better at 0 benchmarks.

DeepSeek-V3.2 (Thinking) significantly outperforms across most benchmarks.

Wed May 27 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

681.2B diff

DeepSeek-V3.2 (Thinking) has 681.2B more parameters than Phi 4 Mini, making it 17738.5% larger.

DeepSeek
DeepSeek-V3.2 (Thinking)
685.0Bparameters
Microsoft
Phi 4 Mini
3.8Bparameters
685.0B
DeepSeek-V3.2 (Thinking)
3.8B
Phi 4 Mini

Context Window

Maximum input and output token capacity

Only DeepSeek-V3.2 (Thinking) specifies input context (131,072 tokens). Only DeepSeek-V3.2 (Thinking) specifies output context (65,536 tokens).

DeepSeek
DeepSeek-V3.2 (Thinking)
Input131,072 tokens
Output65,536 tokens
Microsoft
Phi 4 Mini
Input- tokens
Output- tokens
Wed May 27 2026 • llm-stats.com

License

Usage and distribution terms

Both models are licensed under MIT.

Both models share the same licensing terms, providing consistent usage rights.

DeepSeek-V3.2 (Thinking)

MIT

Open weights

Phi 4 Mini

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2 (Thinking) was released on 2025-12-01, while Phi 4 Mini was released on 2025-02-01.

DeepSeek-V3.2 (Thinking) is 10 months newer than Phi 4 Mini.

DeepSeek-V3.2 (Thinking)

Dec 1, 2025

5 months ago

10mo newer
Phi 4 Mini

Feb 1, 2025

1.3 years ago

Knowledge Cutoff

When training data ends

Phi 4 Mini has a documented knowledge cutoff of 2024-06-01, while DeepSeek-V3.2 (Thinking)'s cutoff date is not specified.

We can confirm Phi 4 Mini's training data extends to 2024-06-01, but cannot make a direct comparison without DeepSeek-V3.2 (Thinking)'s cutoff date.

DeepSeek-V3.2 (Thinking)

—

Phi 4 Mini

Jun 2024

Outputs Comparison

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Key Takeaways

DeepSeek
Larger context window (131,072 tokens)
Higher GPQA score (82.4% vs 25.2%)
Higher MMLU-Pro score (85.0% vs 52.8%)
Microsoft

No standout differentiators in the data we have for this pair.

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2 (Thinking)
Microsoft
Phi 4 Mini

FAQ

Common questions about DeepSeek-V3.2 (Thinking) vs Phi 4 Mini.

Which is better, DeepSeek-V3.2 (Thinking) or Phi 4 Mini?

DeepSeek-V3.2 (Thinking) significantly outperforms across most benchmarks. DeepSeek-V3.2 (Thinking) is made by DeepSeek and Phi 4 Mini is made by Microsoft. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek-V3.2 (Thinking) compare to Phi 4 Mini in benchmarks?

DeepSeek-V3.2 (Thinking) scores AIME 2025: 93.1%, HMMT 2025: 90.2%, MMLU-Pro: 85.0%, LiveCodeBench: 83.3%, GPQA: 82.4%. Phi 4 Mini scores GSM8k: 88.6%, ARC-C: 83.7%, BoolQ: 81.2%, OpenBookQA: 79.2%, PIQA: 77.6%.

What are the context window sizes for DeepSeek-V3.2 (Thinking) and Phi 4 Mini?

DeepSeek-V3.2 (Thinking) supports 131K tokens and Phi 4 Mini supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

Who makes DeepSeek-V3.2 (Thinking) and Phi 4 Mini?

DeepSeek-V3.2 (Thinking) is developed by DeepSeek and Phi 4 Mini is developed by Microsoft.