DeepSeek-V4-Flash-0731 vs Gemini 2.5 Flash-Lite
DeepSeek-V4-Flash-0731 leads the LLM Stats Score 44.7 to 10.4. DeepSeek-V4-Flash-0731 is 1.9x cheaper per token.
DeepSeek · Google · Updated for 2026
Which is better?
DeepSeek-V4-Flash-0731 leads the overall LLM Stats Score 44.7 to 10.4, ranking #35 overall.
On price, DeepSeek-V4-Flash-0731 is roughly 1.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-V4-Flash-0731
- overall performance matters — it scores 44.7 and ranks #35 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- cost matters — it's about 1.9x cheaper per token
- you want the most recent training data — it shipped Jul 2026
Choose Gemini 2.5 Flash-Lite
- you want predictable pricing at $0.10/M input and $0.40/M output
At a glance
The differences that matter most.
Individual benchmarks
9 reported for DeepSeek-V4-Flash-0731 · 13 for Gemini 2.5 Flash-Lite
DeepSeek-V4-Flash-0731 and Gemini 2.5 Flash-Litedon'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 1.7x cheaper than Gemini 2.5 Flash-Lite ($0.10/1M tokens).
For output processing, DeepSeek-V4-Flash-0731 ($0.18/1M tokens) is 2.2x cheaper than Gemini 2.5 Flash-Lite ($0.40/1M tokens).
In conclusion, Gemini 2.5 Flash-Lite is more expensive than DeepSeek-V4-Flash-0731.*
* 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-Flash-0731 can generate longer responses up to 1,048,576 tokens, while Gemini 2.5 Flash-Lite is limited to 65,536 tokens.
Input capabilities
Documented input modalities across available providers
Gemini 2.5 Flash-Lite supports multimodal inputs, whereas DeepSeek-V4-Flash-0731 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-Flash-0731
Gemini 2.5 Flash-Lite
License
Usage and distribution terms
DeepSeek-V4-Flash-0731 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-Flash-0731 was released on 2026-07-31, while Gemini 2.5 Flash-Lite was released on 2025-06-17.
DeepSeek-V4-Flash-0731 is 14 months newer than Gemini 2.5 Flash-Lite.
Jul 31, 2026
1 months ago
1.1yr 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-Flash-0731'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-Flash-0731's cutoff date.
—
Jan 2025
Provider Availability
DeepSeek-V4-Flash-0731 is available from DeepInfra, Novita, Fireworks. Gemini 2.5 Flash-Lite is available from Google.
DeepSeek-V4-Flash-0731
Gemini 2.5 Flash-Lite
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-0731 and Gemini 2.5 Flash-Lite side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Flash-0731 vs Gemini 2.5 Flash-Lite.