Model Comparison
DeepSeek-R1-0528 vs Gemini 1.5 ProWhich is better in 2026?
DeepSeek-R1-0528 significantly outperforms across most benchmarks. DeepSeek-R1-0528 is 4.8x cheaper per token.
Verdict: DeepSeek-R1-0528 vs Gemini 1.5 Pro — which is better?
DeepSeek-R1-0528 (by DeepSeek) and Gemini 1.5 Pro (by Google) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
DeepSeek-R1-0528 outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Gemini 1.5 Pro is better at 0 benchmarks. DeepSeek-R1-0528 significantly outperforms across most benchmarks.
On price, DeepSeek-R1-0528 is roughly 4.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemini 1.5 Pro also accepts a larger context window (2,097,152 input tokens), making it the stronger choice for long documents and large codebases.
Choose DeepSeek-R1-0528 if…
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- cost matters — it's about 4.8x cheaper per token
- you want the most recent training data — it shipped May 2025
- you need open weights you can self-host or fine-tune
Choose Gemini 1.5 Pro if…
- you process long inputs — it offers a 2,097,152 token context window
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-R1-0528 outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Gemini 1.5 Pro is better at 0 benchmarks.
DeepSeek-R1-0528 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-R1-0528 ($0.50/1M tokens) is 5.0x cheaper than Gemini 1.5 Pro ($2.50/1M tokens).
For output processing, DeepSeek-R1-0528 ($2.15/1M tokens) is 4.7x cheaper than Gemini 1.5 Pro ($10.00/1M tokens).
In conclusion, Gemini 1.5 Pro 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 1.5 Pro accepts 2,097,152 input tokens compared to DeepSeek-R1-0528's 131,072 tokens. DeepSeek-R1-0528 can generate longer responses up to 131,072 tokens, while Gemini 1.5 Pro is limited to 8,192 tokens.
Input Capabilities
Supported data types and modalities
Gemini 1.5 Pro supports multimodal inputs, whereas DeepSeek-R1-0528 does not.
Gemini 1.5 Pro can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-R1-0528
Gemini 1.5 Pro
License
Usage and distribution terms
DeepSeek-R1-0528 is licensed under MIT, while Gemini 1.5 Pro 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 1.5 Pro was released on 2024-05-01.
DeepSeek-R1-0528 is 13 months newer than Gemini 1.5 Pro.
May 28, 2025
1.0 years ago
1.1yr newerMay 1, 2024
2.1 years ago
Knowledge Cutoff
When training data ends
Gemini 1.5 Pro has a documented knowledge cutoff of 2023-11-01, while DeepSeek-R1-0528's cutoff date is not specified.
We can confirm Gemini 1.5 Pro's training data extends to 2023-11-01, but cannot make a direct comparison without DeepSeek-R1-0528's cutoff date.
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Nov 2023
Provider Availability
DeepSeek-R1-0528 is available from DeepInfra, DeepSeek, Novita. Gemini 1.5 Pro is available from Google.
DeepSeek-R1-0528
Gemini 1.5 Pro
Outputs Comparison
Key Takeaways
DeepSeek-R1-0528
View detailsDeepSeek
Detailed Comparison
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FAQ
Common questions about DeepSeek-R1-0528 vs Gemini 1.5 Pro.