DeepSeek-V4-Pro-0813 vs Gemini 2.5 Flash-Lite
DeepSeek-V4-Pro-0813 significantly outperforms across most benchmarks. Gemini 2.5 Flash-Lite is 3.1x 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-Lite is better at 0 benchmarks. DeepSeek-V4-Pro-0813 significantly outperforms across most benchmarks.
On price, Gemini 2.5 Flash-Lite is roughly 3.1x 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
- you want the most recent training data — it shipped Aug 2026
Choose Gemini 2.5 Flash-Lite
- cost matters — it's about 3.1x cheaper per token
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-Lite 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 4.3x more expensive than Gemini 2.5 Flash-Lite ($0.10/1M tokens).
For output processing, DeepSeek-V4-Pro-0813 ($0.87/1M tokens) is 2.2x more expensive than Gemini 2.5 Flash-Lite ($0.40/1M tokens).
In conclusion, DeepSeek-V4-Pro-0813 is more expensive than Gemini 2.5 Flash-Lite.*
* 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-Lite is limited to 65,536 tokens.
Input Capabilities
Supported data types and modalities
Gemini 2.5 Flash-Lite supports multimodal inputs, whereas DeepSeek-V4-Pro-0813 does not.
Gemini 2.5 Flash-Lite 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-Lite
License
Usage and distribution terms
DeepSeek-V4-Pro-0813 is licensed under MIT, while Gemini 2.5 Flash-Lite uses Creative Commons Attribution 4.0 License.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Creative Commons Attribution 4.0 License
Open weights
Release Timeline
When each model was launched
DeepSeek-V4-Pro-0813 was released on 2026-08-13, while Gemini 2.5 Flash-Lite was released on 2025-06-17.
DeepSeek-V4-Pro-0813 is 14 months newer than Gemini 2.5 Flash-Lite.
Aug 13, 2026
1 weeks ago
1.2yr newerJun 17, 2025
1.2 years ago
Knowledge Cutoff
When training data ends
Gemini 2.5 Flash-Lite has a documented knowledge cutoff of 2025-01-01, while DeepSeek-V4-Pro-0813's cutoff date is not specified.
We can confirm Gemini 2.5 Flash-Lite's training data extends to 2025-01-01, 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-Lite is available from Google.
DeepSeek-V4-Pro-0813
Gemini 2.5 Flash-Lite
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Pro-0813 and Gemini 2.5 Flash-Lite side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Pro-0813 vs Gemini 2.5 Flash-Lite.