DeepSeek-V4-Flash-0731 vs Phi-4-multimodal-instruct
DeepSeek-V4-Flash-0731 leads the LLM Stats Score 44.3 to 2.8. Phi-4-multimodal-instruct is 1.4x cheaper per token.
DeepSeek · Microsoft · Updated for 2026
Which is better?
DeepSeek-V4-Flash-0731 leads the overall LLM Stats Score 44.3 to 2.8, ranking #39 overall.
On price, Phi-4-multimodal-instruct is roughly 1.4x 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.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-V4-Flash-0731
- overall performance matters — it scores 44.3 and ranks #39 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- 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
- cost matters — it's about 1.4x cheaper per token
At a glance
The differences that matter most.
Individual benchmarks
9 reported for DeepSeek-V4-Flash-0731 · 15 for Phi-4-multimodal-instruct
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.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Flash-0731 ($0.06/1M tokens) is 1.2x 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. DeepSeek-V4-Flash-0731 can generate longer responses up to 1,048,576 tokens, while Phi-4-multimodal-instruct is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
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
1 months ago
1.5yr newerFeb 1, 2025
1.6 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, Novita, Fireworks. Phi-4-multimodal-instruct is available from DeepInfra.
DeepSeek-V4-Flash-0731
Phi-4-multimodal-instruct
Outputs Comparison
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.
FAQ
Common questions about DeepSeek-V4-Flash-0731 vs Phi-4-multimodal-instruct.