DeepSeek-R1-0528 vs Gemini 3.8 Flash
Gemini 3.8 Flash leads the LLM Stats Score 51.2 to 24.2. DeepSeek-R1-0528 is 1.6x cheaper per token.
DeepSeek · Google · Updated for 2026
Which is better?
Gemini 3.8 Flash leads the overall LLM Stats Score 51.2 to 24.2, ranking #12 overall.
On price, DeepSeek-R1-0528 is roughly 1.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 3.8 Flash 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-R1-0528
- cost matters — it's about 1.6x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Gemini 3.8 Flash
- overall performance matters — it scores 51.2 and ranks #12 on LLM Stats
- your work emphasizes reasoning and coding — 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 Sep 2026
At a glance
The differences that matter most.
Individual benchmarks
16 reported for DeepSeek-R1-0528 · 13 for Gemini 3.8 Flash
DeepSeek-R1-0528 and Gemini 3.8 Flashdon'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-R1-0528 ($0.50/1M tokens) is 1.5x cheaper than Gemini 3.8 Flash ($0.75/1M tokens).
For output processing, DeepSeek-R1-0528 ($2.15/1M tokens) is 1.7x cheaper than Gemini 3.8 Flash ($3.75/1M tokens).
In conclusion, Gemini 3.8 Flash is more expensive than DeepSeek-R1-0528.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Gemini 3.8 Flash accepts 1,048,576 input tokens compared to DeepSeek-R1-0528's 163,840 tokens. DeepSeek-R1-0528 can generate longer responses up to 163,840 tokens, while Gemini 3.8 Flash is limited to 65,536 tokens.
Input capabilities
Documented input modalities across available providers
Gemini 3.8 Flash supports multimodal inputs, whereas DeepSeek-R1-0528 does not.
Gemini 3.8 Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-R1-0528
Gemini 3.8 Flash
License
Usage and distribution terms
DeepSeek-R1-0528 is licensed under MIT, while Gemini 3.8 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-R1-0528 was released on 2025-05-28, while Gemini 3.8 Flash was released on 2026-09-02.
Gemini 3.8 Flash is 15 months newer than DeepSeek-R1-0528.
May 28, 2025
1.3 years ago
Sep 2, 2026
1 weeks ago
1.3yr newerKnowledge Cutoff
When training data ends
Gemini 3.8 Flash has a documented knowledge cutoff of 2026-03-31, while DeepSeek-R1-0528's cutoff date is not specified.
We can confirm Gemini 3.8 Flash's training data extends to 2026-03-31, but cannot make a direct comparison without DeepSeek-R1-0528's cutoff date.
—
Mar 2026
Provider Availability
DeepSeek-R1-0528 is available from DeepInfra, DeepSeek, Novita. Gemini 3.8 Flash is available from Google.
DeepSeek-R1-0528
Gemini 3.8 Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-R1-0528 and Gemini 3.8 Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-R1-0528 vs Gemini 3.8 Flash.