DeepSeek-V4-Pro-0813 vs Gemini 2.5 Flash
DeepSeek-V4-Pro-0813 significantly outperforms across most benchmarks. DeepSeek-V4-Pro-0813 is 1.6x cheaper per token.
DeepSeek · Google · Updated for 2026
Which is better?
DeepSeek-V4-Pro-0813 outperforms in 1 benchmarks (Humanity's Last Exam), while Gemini 2.5 Flash is better at 0 benchmarks. DeepSeek-V4-Pro-0813 significantly outperforms across most benchmarks.
On price, DeepSeek-V4-Pro-0813 is roughly 1.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current benchmark, pricing, and model metadata for 2026.
Choose DeepSeek-V4-Pro-0813
- you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
- cost matters — it's about 1.6x cheaper per token
- you want the most recent training data — it shipped Aug 2026
- you need open weights you can self-host or fine-tune
Choose Gemini 2.5 Flash
- you want predictable pricing at $0.30/M input and $2.50/M output
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Pro-0813 outperforms in 1 benchmarks (Humanity's Last Exam), while Gemini 2.5 Flash is better at 0 benchmarks.
DeepSeek-V4-Pro-0813 significantly outperforms across most benchmarks.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Pro-0813 ($0.43/1M tokens) is 1.4x more expensive than Gemini 2.5 Flash ($0.30/1M tokens).
For output processing, DeepSeek-V4-Pro-0813 ($0.87/1M tokens) is 2.9x cheaper than Gemini 2.5 Flash ($2.50/1M tokens).
In conclusion, Gemini 2.5 Flash is more expensive than DeepSeek-V4-Pro-0813.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Both models have the same input context window of 1,048,576 tokens. DeepSeek-V4-Pro-0813 can generate longer responses up to 393,216 tokens, while Gemini 2.5 Flash is limited to 65,536 tokens.
Input Capabilities
Supported data types and modalities
Gemini 2.5 Flash supports multimodal inputs, whereas DeepSeek-V4-Pro-0813 does not.
Gemini 2.5 Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Pro-0813
Gemini 2.5 Flash
License
Usage and distribution terms
DeepSeek-V4-Pro-0813 is licensed under MIT, while Gemini 2.5 Flash uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-V4-Pro-0813 was released on 2026-08-13, while Gemini 2.5 Flash was released on 2025-05-20.
DeepSeek-V4-Pro-0813 is 15 months newer than Gemini 2.5 Flash.
Aug 13, 2026
1 weeks ago
1.2yr newerMay 20, 2025
1.3 years ago
Knowledge Cutoff
When training data ends
Gemini 2.5 Flash has a documented knowledge cutoff of 2025-01-31, while DeepSeek-V4-Pro-0813's cutoff date is not specified.
We can confirm Gemini 2.5 Flash's training data extends to 2025-01-31, but cannot make a direct comparison without DeepSeek-V4-Pro-0813's cutoff date.
—
Jan 2025
Provider Availability
DeepSeek-V4-Pro-0813 is available from DeepSeek, DeepInfra, Novita, Together. Gemini 2.5 Flash is available from Google.
DeepSeek-V4-Pro-0813
Gemini 2.5 Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Pro-0813 and Gemini 2.5 Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Pro-0813 vs Gemini 2.5 Flash.