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

DeepSeek-V3.2 (Thinking) leads the LLM Stats Score 32.9 to 12.3.

DeepSeek · Microsoft · Updated for 2026

Which is better?

DeepSeek-V3.2 (Thinking) leads the overall LLM Stats Score 32.9 to 12.3, ranking #95 overall.

In the 4 individual benchmarks reported for both models, DeepSeek-V3.2 (Thinking) wins 4; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-V3.2 (Thinking)

  • overall performance matters — it scores 32.9 and ranks #95 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 4 of 4 exact shared results
  • you want the most recent training data — it shipped Dec 2025

Choose Phi 4 Reasoning

  • you are already invested in the Microsoft ecosystem

At a glance

The differences that matter most.

Core performance indexes
32.9
#95
12.3
#242
32.9
#94
12.8
#230
22.9
#74
6.5
#182
Cost, coverage & limits
Benchmark wins
4 of 4
0 of 4
Input price
$0.28 / M
— / M
Output price
$0.42 / M
— / M
Context window
131,072

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
DeepSeek-V3.2 (Thinking)
Phi 4 Reasoning
30.6#71
13.9#215
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

14 reported for DeepSeek-V3.2 (Thinking) · 11 for Phi 4 Reasoning

4 shared

DeepSeek-V3.2 (Thinking) outperforms in 4 benchmarks (AIME 2025, GPQA, LiveCodeBench, MMLU-Pro), while Phi 4 Reasoning is better at 0 benchmarks.

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

Sun Sep 06 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

671.0B diff

DeepSeek-V3.2 (Thinking) has 671.0B more parameters than Phi 4 Reasoning, making it 4792.9% larger.

DeepSeek
DeepSeek-V3.2 (Thinking)
685.0Bparameters
Microsoft
Phi 4 Reasoning
14.0Bparameters
685.0B
DeepSeek-V3.2 (Thinking)
14.0B
Phi 4 Reasoning

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 Reasoning
Input- tokens
Output- tokens
Sun Sep 06 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 Reasoning

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2 (Thinking) was released on 2025-12-01, while Phi 4 Reasoning was released on 2025-04-30.

DeepSeek-V3.2 (Thinking) is 7 months newer than Phi 4 Reasoning.

DeepSeek-V3.2 (Thinking)

Dec 1, 2025

9 months ago

7mo newer
Phi 4 Reasoning

Apr 30, 2025

1.4 years ago

Knowledge Cutoff

When training data ends

Phi 4 Reasoning has a documented knowledge cutoff of 2025-03-01, while DeepSeek-V3.2 (Thinking)'s cutoff date is not specified.

We can confirm Phi 4 Reasoning's training data extends to 2025-03-01, but cannot make a direct comparison without DeepSeek-V3.2 (Thinking)'s cutoff date.

DeepSeek-V3.2 (Thinking)

Phi 4 Reasoning

Mar 2025

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against DeepSeek-V3.2 (Thinking) and Phi 4 Reasoning side-by-side, then vote on the output you prefer.

DeepSeek-V3.2 (Thinking)
✓ Preferred
Phi 4 Reasoning
Open in Playground

FAQ

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

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

DeepSeek-V3.2 (Thinking) leads the LLM Stats Score 32.9 to 12.3. DeepSeek-V3.2 (Thinking) is made by DeepSeek and Phi 4 Reasoning is made by Microsoft. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek-V3.2 (Thinking) compare to Phi 4 Reasoning 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 Reasoning scores FlenQA: 97.7%, HumanEval+: 92.9%, IFEval: 83.4%, OmniMath: 76.6%, AIME 2024: 75.3%.

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

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

What are the main differences between DeepSeek-V3.2 (Thinking) and Phi 4 Reasoning?

Key differences include LLM Stats Score (32.9 vs 12.3). See the full comparison above for benchmark-by-benchmark results.

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

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