Model Comparison
DeepSeek-V4-Flash-0731 vs Phi-4-multimodal-instructWhich is better in 2026?
Comparing DeepSeek-V4-Flash-0731 and Phi-4-multimodal-instruct across benchmarks, pricing, and capabilities.
Verdict: DeepSeek-V4-Flash-0731 vs Phi-4-multimodal-instruct — which is better?
DeepSeek-V4-Flash-0731 (by DeepSeek) and Phi-4-multimodal-instruct (by Microsoft) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
On price, Phi-4-multimodal-instruct is roughly 1.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Flash-0731 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose DeepSeek-V4-Flash-0731 if…
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Jul 2026
Choose Phi-4-multimodal-instruct if…
- cost matters — it's about 1.8x cheaper per token
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Flash-0731 and Phi-4-multimodal-instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Flash-0731 ($0.09/1M tokens) is 1.8x more expensive than Phi-4-multimodal-instruct ($0.05/1M tokens).
For output processing, DeepSeek-V4-Flash-0731 ($0.18/1M tokens) is 1.8x more expensive than Phi-4-multimodal-instruct ($0.10/1M tokens).
In conclusion, DeepSeek-V4-Flash-0731 is more expensive than Phi-4-multimodal-instruct.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4-Flash-0731 has 298.4B more parameters than Phi-4-multimodal-instruct, making it 5328.6% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4-Flash-0731 accepts 1,048,576 input tokens compared to Phi-4-multimodal-instruct's 128,000 tokens. Phi-4-multimodal-instruct can generate longer responses up to 128,000 tokens, while DeepSeek-V4-Flash-0731 is limited to 65,536 tokens.
Input Capabilities
Supported data types and modalities
Phi-4-multimodal-instruct supports multimodal inputs, whereas DeepSeek-V4-Flash-0731 does not.
Phi-4-multimodal-instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Flash-0731
Phi-4-multimodal-instruct
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-Flash-0731 was released on 2026-07-31, while Phi-4-multimodal-instruct was released on 2025-02-01.
DeepSeek-V4-Flash-0731 is 18 months newer than Phi-4-multimodal-instruct.
Jul 31, 2026
3 days ago
1.5yr newerFeb 1, 2025
1.5 years ago
Knowledge Cutoff
When training data ends
Phi-4-multimodal-instruct has a documented knowledge cutoff of 2024-06-01, while DeepSeek-V4-Flash-0731's cutoff date is not specified.
We can confirm Phi-4-multimodal-instruct's training data extends to 2024-06-01, but cannot make a direct comparison without DeepSeek-V4-Flash-0731's cutoff date.
—
Jun 2024
Provider Availability
DeepSeek-V4-Flash-0731 is available from DeepInfra, Fireworks, Novita. Phi-4-multimodal-instruct is available from DeepInfra.
DeepSeek-V4-Flash-0731
Phi-4-multimodal-instruct
Outputs Comparison
Key Takeaways
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-0731 and Phi-4-multimodal-instruct side-by-side, then vote on the output you prefer.
| Feature | | |
|---|
FAQ
Common questions about DeepSeek-V4-Flash-0731 vs Phi-4-multimodal-instruct.