DeepSeek-V4.1-Flash-1017 vs Gemini 2.5 Flash-Lite
DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.0 to 10.1. Gemini 2.5 Flash-Lite is 3.0x cheaper per token.
DeepSeek · Google · Updated for 2026
Which is better?
DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.0 to 10.1, ranking #15 overall.
In the 1 individual benchmarks reported for both models, DeepSeek-V4.1-Flash-1017 wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Gemini 2.5 Flash-Lite is roughly 3.0x 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-V4.1-Flash-1017
- overall performance matters — it scores 51.0 and ranks #15 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you want the most recent training data — it shipped Oct 2026
Choose Gemini 2.5 Flash-Lite
- cost matters — it's about 3.0x cheaper per token
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
11 reported for DeepSeek-V4.1-Flash-1017 · 13 for Gemini 2.5 Flash-Lite
DeepSeek-V4.1-Flash-1017 outperforms in 1 benchmarks (Humanity's Last Exam), while Gemini 2.5 Flash-Lite is better at 0 benchmarks.
DeepSeek-V4.1-Flash-1017 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4.1-Flash-1017 ($0.30/1M tokens) is 3.0x more expensive than Gemini 2.5 Flash-Lite ($0.10/1M tokens).
For output processing, DeepSeek-V4.1-Flash-1017 ($1.20/1M tokens) is 3.0x more expensive than Gemini 2.5 Flash-Lite ($0.40/1M tokens).
In conclusion, DeepSeek-V4.1-Flash-1017 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-V4.1-Flash-1017 can generate longer responses up to 393,216 tokens, while Gemini 2.5 Flash-Lite is limited to 65,536 tokens.
Input capabilities
Documented input modalities across available providers
Both DeepSeek-V4.1-Flash-1017 and Gemini 2.5 Flash-Lite support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
DeepSeek-V4.1-Flash-1017
Gemini 2.5 Flash-Lite
License
Usage and distribution terms
DeepSeek-V4.1-Flash-1017 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-V4.1-Flash-1017 was released on 2026-10-17, while Gemini 2.5 Flash-Lite was released on 2025-06-17.
DeepSeek-V4.1-Flash-1017 is 16 months newer than Gemini 2.5 Flash-Lite.
Oct 17, 2026
0 days ago
1.3yr newerJun 17, 2025
1.3 years ago
Knowledge Cutoff
When training data ends
Gemini 2.5 Flash-Lite has a documented knowledge cutoff of 2025-01-01, while DeepSeek-V4.1-Flash-1017'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-V4.1-Flash-1017's cutoff date.
—
Jan 2025
Provider Availability
DeepSeek-V4.1-Flash-1017 is available from DeepSeek. Gemini 2.5 Flash-Lite is available from Google.
DeepSeek-V4.1-Flash-1017
Gemini 2.5 Flash-Lite
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4.1-Flash-1017 and Gemini 2.5 Flash-Lite side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4.1-Flash-1017 vs Gemini 2.5 Flash-Lite.
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