DeepSeek-V4.1-Flash vs Phi 4
DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 5.4. Phi 4 is 3.8x cheaper per token.
DeepSeek · Microsoft · Updated for 2026
Which is better?
DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to 5.4, 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.
On price, Phi 4 is roughly 3.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4.1-Flash also accepts a larger context window (1,040,000 input tokens), making it the stronger choice for long documents and large codebases.
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 process long inputs — it offers a 1,040,000 token context window
- you want the most recent training data — it shipped Sep 2026
Choose Phi 4
- cost matters — it's about 3.8x cheaper per token
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 · 13 for Phi 4
DeepSeek-V4.1-Flash outperforms in 1 benchmarks (GPQA), while Phi 4 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
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4.1-Flash ($0.22/1M tokens) is 3.1x more expensive than Phi 4 ($0.07/1M tokens).
For output processing, DeepSeek-V4.1-Flash ($0.66/1M tokens) is 4.7x more expensive than Phi 4 ($0.14/1M tokens).
In conclusion, DeepSeek-V4.1-Flash is more expensive than Phi 4.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4.1-Flash has 748.5B more parameters than Phi 4, making it 5091.9% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4.1-Flash accepts 1,040,000 input tokens compared to Phi 4's 16,384 tokens. DeepSeek-V4.1-Flash can generate longer responses up to 393,216 tokens, while Phi 4 is limited to 16,384 tokens.
Input capabilities
Documented input modalities across available providers
DeepSeek-V4.1-Flash supports multimodal inputs, whereas Phi 4 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
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 was released on 2024-12-12.
DeepSeek-V4.1-Flash is 21 months newer than Phi 4.
Sep 10, 2026
3 days ago
1.7yr newerDec 12, 2024
1.8 years ago
Knowledge Cutoff
When training data ends
Phi 4 has a documented knowledge cutoff of 2024-06-01, while DeepSeek-V4.1-Flash's cutoff date is not specified.
We can confirm Phi 4's training data extends to 2024-06-01, but cannot make a direct comparison without DeepSeek-V4.1-Flash's cutoff date.
—
Jun 2024
Provider Availability
DeepSeek-V4.1-Flash is available from Fireworks, DeepInfra, DeepSeek, Novita. Phi 4 is available from DeepInfra.
DeepSeek-V4.1-Flash
Phi 4
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4.1-Flash and Phi 4 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4.1-Flash vs Phi 4.