DeepSeek-V4.1-Flash vs Phi 4 Reasoning
DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 12.0.
DeepSeek · Microsoft · Updated for 2026
Which is better?
DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to 12.0, ranking #12 overall.
In the 1 individual benchmarks reported for both models, DeepSeek-V4.1-Flash wins 1; 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-V4.1-Flash
- overall performance matters — it scores 51.8 and ranks #12 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you want the most recent training data — it shipped Sep 2026
Choose Phi 4 Reasoning
- you are already invested in the Microsoft ecosystem
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
20 reported for DeepSeek-V4.1-Flash · 11 for Phi 4 Reasoning
DeepSeek-V4.1-Flash outperforms in 1 benchmarks (GPQA), while Phi 4 Reasoning is better at 0 benchmarks.
DeepSeek-V4.1-Flash significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
DeepSeek-V4.1-Flash has 749.2B more parameters than Phi 4 Reasoning, making it 5351.5% larger.
Context Window
Maximum input and output token capacity
Only DeepSeek-V4.1-Flash specifies input context (1,040,000 tokens). Only DeepSeek-V4.1-Flash specifies output context (393,216 tokens).
Input capabilities
Documented input modalities across available providers
DeepSeek-V4.1-Flash supports multimodal inputs, whereas Phi 4 Reasoning does not.
DeepSeek-V4.1-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4.1-Flash
Phi 4 Reasoning
License
Usage and distribution terms
Both models are licensed under MIT.
Both models share the same licensing terms, providing consistent usage rights.
MIT
Open weights
MIT
Open weights
Release Timeline
When each model was launched
DeepSeek-V4.1-Flash was released on 2026-09-10, while Phi 4 Reasoning was released on 2025-04-30.
DeepSeek-V4.1-Flash is 17 months newer than Phi 4 Reasoning.
Sep 10, 2026
4 days ago
1.4yr newerApr 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-V4.1-Flash'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-V4.1-Flash's cutoff date.
—
Mar 2025
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4.1-Flash and Phi 4 Reasoning side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4.1-Flash vs Phi 4 Reasoning.